https://wiki.ivir.nl/api.php?action=feedcontributions&feedformat=atom&user=Isiklar+CerenTechnology Governance Wiki - User contributions [en]2026-10-16T01:14:55ZUser contributionsMediaWiki 1.46.0https://wiki.ivir.nl/index.php?title=Data:_Data_Portability&diff=124239Data: Data Portability2026-10-07T11:58:01Z<p>Isiklar Ceren: /* 5. Implementation and Case Law */</p>
<hr />
<div>= <span dir="ltr" lang="en"><span class="mw-page-title-main">Data: Data Portability</span></span> =<br />
<br />
According to [https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng#art_20 Article 20] of the General Data Protection Regulation, "[the data subject shall have the right to receive the personal data concerning him or her, which he or she has provided to a controller, in a structured, commonly used and machine-readable format and have the right to transmit those data to another controller without hindrance from the controller to which the personal data have been provided" where processing is based on consent or contract and is carried out by automated means. Additionally, the [https://eur-lex.europa.eu/eli/reg/2023/2854/oj/eng Data Act ] foresees that data portability should support interoperability of data processing services, while data portability should also be ensured as part of the [https://eur-lex.europa.eu/eli/reg/2022/1925/oj/eng Digital Markets Act] gatekeeper obligations.<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">Brazil</span></span> ==<br />
<span dir="ltr" lang="en"><span class="mw-page-title-main">in progress</span></span><br />
<br />
= China - Ceren, Sergey, Juliette =<br />
== 1. Overview ==<br />
<p>The Personal Information Protection Law ([https://en.spp.gov.cn/2021-12/29/c_948419.htm PIPL])&nbsp; came into effect on 1 November 2021, much later than the General Data Protection Regulation ([https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02016R0679-20160504 GDPR]) which came into force on 24 May 2016. PIPL is China’s primary legal framework for personal information protection and has notable parallels with the GDPR, while reflecting distinctly Chinese regulatory priorities.</p><br />
<br />
== 2. Key Terms and Definitions in the PIPL are as follows ==<br />
<p>PIPL Article 2: “The '''personal information of natural persons''' shall be protected by law. No organization or individual may infringe upon natural persons’ rights and interests on their personal information.”</p><br />
<p>'''Personal information processor''' (Article 73(1)): “any organization or individual that independently determines the purpose and method of processing personal information.” The term personal information processor is functionally equivalent to the GDPR concept of a data controller.</p><br />
<p>'''Personal information''' (Article 4): “information related to an identified or identifiable natural person, recorded electronically or by other means, excluding anonymized information.”</p><br />
<br />
== 3. The Scope of PIPL ==<br />
<p>PIPL applies to the processing of personal information of natural persons within China (Article 3), while also having explicit extraterritorial reach, applying to processing outside China where:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*the purpose is to provide products or services to persons within China;<br />
*the purpose is to analyze or assess the behavior of persons within China; or<br />
*other circumstances provided by law or administrative regulations [https://www.dlapiperdataprotection.com/index.html?c=CN apply].<br />
<br />
== 4. Data Portability under PIPL Article 45 ==<br />
<p>Article 45 of the PIPL sets out China’s primary data-portability terms:</p><br />
<p>“Individuals have the right to access and copy their personal information from personal information processors, except where laws or administrative regulations provide otherwise. Where an individual requests access to or copying of personal information, the personal information processor shall provide it in a timely manner.</p><br />
<p>Where an individual requests the transfer of personal information to a personal information processor designated by the individual, where the conditions set by the national cyberspace authority (hereon abbreviated as “CAC”) are met, the personal information processor shall provide a means for such transfer.”</p><br />
<p>When the scope of Article 45 of the PIPL is reviewed, it is seen that the data portability right:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*- applies to all personal information processors;<br />
*- has no size threshold or gatekeeper designation, whereby a small enterprises to large platforms are, in principle, equally subject to the provision;<br />
*- is limited to personal information;<br />
*- does not encompass non-personal data, including machine-generated, anonymized and IoT data.<br />
*- not confined to processing based on consent or contract (until the DSMR clarified, as elaborated below),<br />
*- not expressly limited to data “provided by” the individual (until the DSMR clarified, as elaborated below)<br />
<p>At first, the PIPL was construed to be vague in terms of this data portability clause, since the data portability conditions were awaited to be announced by CAC. The conditions referred to in PIPL Article 45 have since been elaborated in Article 25 of the Network Data Security Management Regulations ([https://www.gov.cn/zhengce/content/202409/content_6977766.htm DSMR]), (Official English Ministry of Justice [https://en.moj.gov.cn/pdf/RegulationsonNetworkDataSecurityManagement.pdf text]) promulgated by the State Council on 30 September 2024 and effective from 1 January 2025. The Regulations are a State Council administrative regulation, not an instrument issued solely by the CAC. They nonetheless respond to PIPL Art. 45’s reference to conditions set by the CAC and operate within China’s broader CAC-centred data-governance framework.</p><br />
<p>Article 25 is [https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902 widely understood] as implementing and further specifying the PIPL’s data-portability right. Nonetheless, the provision does not itself establish a fully mature interoperability regime comparable to the EU framework: further technical standards, procedural guidance, and enforcement practice remain relevant to the right’s practical exercise.</p><br />
<p>DSMR Article 25 reads as follows:</p><br />
<p>“For requests for transferring personal information that meets the following conditions, a network data processor shall provide means for other network data processors designated by the individual to access and obtain relevant personal information:</p><br />
<p>(1) the true identity of the requester can be verified;</p><br />
<p>(2) the requested transfer involves personal information provided with the individual's consent or collected based on a contract;</p><br />
<p>(3) the transfer of personal information is technically feasible; and</p><br />
<p>(4) the transfer of personal information does not harm the legitimate rights and interests of others. Where the number of transfer requests significantly exceeds a reasonable limit, the network data processor may charge necessary fees based on the cost of transferring personal information.”</p><br />
<p>'''Lack of Direction in Implementation'''</p><br />
<p>Implementation is lacking, although lawyers’ [https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902 commentary] describes Article 25 as an “expansion and further specification” of the portability right under PIPL Art. 45.&nbsp;</p><br />
<p>Article 25 of the DSMR does not by itself create a fully mature interoperability regime. Further CAC rules, technical standards, transfer formats, authentication procedures, and enforcement practice may still be needed for the right to operate consistently in practice. We distinguish between: (1) the existence of regulatory conditions, which Article 25 of the DSMR supplies; and (2) complete operational implementation, which remains dependent on technical and administrative development.</p><br />
<br />
== 5. Implementation and Case Law ==<br />
<p>We identified no published Chinese judgment directly applying the transfer right in PIPL Art. 45(3). Indeed, Courts have addressed portability indirectly, mainly through unfair competition law. On 28 August 2025 the Supreme People's Court, released their [https://www.court.gov.cn/zixun/xiangqing/474431.html first batch of guiding cases] devoted to data rights. Two of these stand out in terms of data portability, and are discussed below, although the rulings are not based on data portability provisions under the PIPL:</p><br />
#Guiding Case No. 263: The case concerned a dispute between two recruitment platforms and was decided before the PIPL entered into force, on the basis of Art. 2 of the Anti-Unfair Competition Law. The court held that a platform which, with the user's authorization, transfers data that user obtained on another platform does not engage in unfair competition, provided it does not disrupt market order. The original platform holds protected interests in data it has invested in, but it may not prevent users from transferring data they lawfully hold.<br />
<p><br></p><br />
#Guiding Case No. [https://www.court.gov.cn/zixun/xiangqing/474431.html 262], states that unauthorized scraping that substantially replaces the original platform's service is unfair competition[https://cms.law/en/chn/legal-updates/china-s-supreme-court-releases-six-guiding-cases-on-data-rights-providing-insights-for-corporate-counsels .]<br />
<p>In a judgment of 8 September 2023, the Guangzhou Internet [https://www.hunton.com/privacy-and-information-security-law/the-first-case-in-china-on-personal-information-protection-in-cross-border-transfer-scenario Court] held that the rights to be informed and to decide are the core personal information rights, whereas the rights of access, copy, portability, correction, supplementation and explanation are instrumental rights. This case pertained to the necessity of the personal information processor’s (in GDPR terms, data controller’s) transfer of data abroad. Albeit not being directly related to data portability, this case classified data portability as a supplementary right.</p><br />
<p>Overall, there is no evidence yet that the individual transfer right works in practice. Data portability in China has so far been developed by the courts and framed by competition and data-circulation concerns rather than by data protection.</p><br />
<p>In their [https://doi.org/10.1016/j.clsr.2024.105994 article] “''From brussels effect to gravity assists: Understanding the evolution of the GDPR-inspired personal information protection law in China''”, Wenlong Li and Jiahong Chen have stated that there is much space left for local courts to decide on the nature, scope and impact of data portability rights on a case-by-case basis. It should be noted, as a significant caveat, that there exists a scant corpus of case-law, and the few decisions that are publicly accessible are inadequate to form a coherent pattern.</p><br />
<p>Despite the interpretative powers granted by the PIPL to the CAC, the authority remains relatively passive in elucidating and detailing the provisions of the PIPL through official guidelines.</p><br />
<br />
== 6. Public and Private Sector ==<br />
<p>PIPL applies to both public and private sector processors.</p><br />
<p>State organs are specifically addressed in Articles 33 through 38 of the [https://en.spp.gov.cn/2021-12/29/c_948419.htm PIPL] and receive some exemptions, such as the absence of a consent requirement where processing is necessary to perform statutory duties or obligations. PIPL’s Article 45 on data portability does not expressly exclude state organs, but has a very broad general carve-out “except where laws or administrative regulations provide otherwise”. In terms of setting out a broad exception regime, this article may be construed as similar to the exceptions under GDPR Article 23 (this subject as a topic exceeds the scope of this research).</p><br />
<br />
== 7. Related Legislation: Data Security Law (DSL, 2021) ==<br />
<p>The [https://www.chinalawtranslate.com/en/anti-monopoly-law-2022/ DSL] classifies data into tiers: general, important, and core national data. It imposes corresponding security obligations. It contains no portability right. Restrictions on cross-border transfers of “important data” may limit the practical exercise of portability. We will not delve into this piece of legislation and its application, as it vastly remains outside the scope of this research.</p><br />
<p>A related legislative framework is also encountered in Article 9 of the 2022 Anti-Monopoly Law, providing that undertakings must not use data and algorithms, technology, capital advantages, platform rules, or similar means to engage in monopolistic conduct prohibited by the law.</p><br />
<br />
== 8. Comparison of the Chinese Data Portability Regime with the EU Data Portability Regime ==<br />
<br />
#''' ''''''The EU'''<br />
<p>The EU portability right [https://ejlt.org/index.php/ejlt/article/view/988 originated] in Article 18(1) of the draft GDPR as a way to facilitate switching between online services, although the final provision narrowed its scope. GDPR’s Article 20 gives individuals more control over personal data and can support data flows within the EU by enabling the provision of a copy of personal data or a direct transfer between controllers.</p><br />
<p>The scope of the GDPR based data portability right encompasses the [https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:02016R0679-20160504 following]:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*personal data processed on the basis of consent or a contract:&nbsp;<br />
*non-personal data falls outside the scope of the GDPR entirely,<br />
*the right applies to SMEs as well as large technology firms (similar to the Chinese scope).<br />
*the right is free of charge and may be exercised at any time (subject to limits such as deletion/anonymization of the data, interference with a public-interest task, and the rights and freedoms of others).<br />
<p><br></p><br />
<p>The EU’s [https://ec.europa.eu/newsroom/article29/items/611233 Article 29 Working Party Guidelines on the right to "data portability"] shed light on the application and intent of the data portability right, as quoted below:</p><br />
<p>“It allows for data subjects to receive the personal data that they have provided to a controller, in a structured, commonly used and machine-readable format, and to transmit those data to another data controller. The purpose of this new right is to empower the data subject and give him/her more control over the personal data concerning him or her. Since it allows the direct transmission of personal data from one data controller to another, the right to data portability is also an important tool that will support the free flow of personal data in the EU and foster competition between controllers. It will facilitate switching between different service providers, and will therefore foster the development of new services in the context of the digital single market strategy.”</p><br />
<p><br></p><br />
'''Comparative analysis of GDPR and PIPL:'''<p>Compared with the EU framework, China’s Article 25 is a significant move from a high-level statutory portability clause toward specified regulatory conditions. Yet the availability of concrete technical standards and consistent enforcement remains a central practical question.</p><br />
<p>As [https://doi.org/10.1016/j.clsr.2024.105994 identified by Wenlong Li and Jiahong Chen]:</p><br />
<p>“unlike the EU's cherishment of data protection as a freestanding, fundamental right, China's placement of personal information protection as a legally protectable interest in its legal order is further down the legal hierarchy to such an extent that its legal position has significantly affected how personal information protection is balanced against other rights and interests. Particularly relevant rights include the right to conduct a business (not formulated explicitly in China), economic growth, as well as cyber sovereignty. Personal information protection, even combined with the right to privacy, has never been elevated to the highest level of hierarchy as a fundamental or constitutional right in China.”</p><br />
<p>&nbsp;“…China navigates through a patchwork of internal considerations, international standards, and strategic choices, ultimately sculpting a data protection regime that has a similar appearance to the GDPR but aligns with its distinct political, cultural and legal landscape.”</p><br />
<p>“Unlike the US, China is not a major exporter of digital services to the EU, which gives the country a much weaker incentive to align its data privacy law in an attempt to facilitate the free flow of personal data from the EU.”</p><br />
<p>In light of these valuable considerations, it is concluded that in the EU, data protection is recognized as an autonomous fundamental right. In China, by contrast, personal information protection is treated as a ''legally protected interest'', which places it much lower in the legal hierarchy. This weaker status shapes how it is weighed against competing considerations, such as the freedom to conduct a business, economic development and cyber sovereignty. Neither personal information protection nor the right to privacy, whether taken separately or together, has ever been raised to the rank of a fundamental or constitutional right in China. China's approach results from a combination of domestic priorities, international models and strategic decisions. The outcome is a data protection framework that looks similar to the GDPR on the surface but is adapted to China's own political, cultural and legal context. Unlike the United States, China exports few digital services to the EU. It therefore has much less reason to bring its data protection law into line with EU standards in order to secure the free flow of personal data from Europe[https://doi.org/10.1016/j.clsr.2024.105994 .]</p><br />
<p><br></p><br />
#''' '''Portability of Non-personal data<br />
#China has no direct equivalent to the EU Data Act’s internet of things data portability regime.<br />
#National security is at the forefront of considerations playing into information transfers abroad.<br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*Unlike the EU legislation’s motto of “free flow of data in the internal market”, China is guarding sovereignty concerns when thinking of the transfer of data.<br />
<p>While data transfers outside of China should not be confused with the general right to data portability, the interplay between the two could be considered. A limitation, or a lack in the adoption of the right to data portability results in less flow of data both within China, and outside of China. While data transfers abroad do not form part of this exercise, it should also be noted that the main driving factor of EU’s data protection regime is the free flow of information within the internal market, while China does not take part in such a union and is therefore not incentivized by such a market goal.</p><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">[[Data:India|India]]</span></span> ==<br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">United States</span></span> ==<br />
in progress</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Data:_Data_Portability&diff=124238Data: Data Portability2026-10-07T11:56:34Z<p>Isiklar Ceren: /* 4. Data Portability under PIPL Article 45 */</p>
<hr />
<div>= <span dir="ltr" lang="en"><span class="mw-page-title-main">Data: Data Portability</span></span> =<br />
<br />
According to [https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng#art_20 Article 20] of the General Data Protection Regulation, "[the data subject shall have the right to receive the personal data concerning him or her, which he or she has provided to a controller, in a structured, commonly used and machine-readable format and have the right to transmit those data to another controller without hindrance from the controller to which the personal data have been provided" where processing is based on consent or contract and is carried out by automated means. Additionally, the [https://eur-lex.europa.eu/eli/reg/2023/2854/oj/eng Data Act ] foresees that data portability should support interoperability of data processing services, while data portability should also be ensured as part of the [https://eur-lex.europa.eu/eli/reg/2022/1925/oj/eng Digital Markets Act] gatekeeper obligations.<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">Brazil</span></span> ==<br />
<span dir="ltr" lang="en"><span class="mw-page-title-main">in progress</span></span><br />
<br />
= China - Ceren, Sergey, Juliette =<br />
== 1. Overview ==<br />
<p>The Personal Information Protection Law ([https://en.spp.gov.cn/2021-12/29/c_948419.htm PIPL])&nbsp; came into effect on 1 November 2021, much later than the General Data Protection Regulation ([https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02016R0679-20160504 GDPR]) which came into force on 24 May 2016. PIPL is China’s primary legal framework for personal information protection and has notable parallels with the GDPR, while reflecting distinctly Chinese regulatory priorities.</p><br />
<br />
== 2. Key Terms and Definitions in the PIPL are as follows ==<br />
<p>PIPL Article 2: “The '''personal information of natural persons''' shall be protected by law. No organization or individual may infringe upon natural persons’ rights and interests on their personal information.”</p><br />
<p>'''Personal information processor''' (Article 73(1)): “any organization or individual that independently determines the purpose and method of processing personal information.” The term personal information processor is functionally equivalent to the GDPR concept of a data controller.</p><br />
<p>'''Personal information''' (Article 4): “information related to an identified or identifiable natural person, recorded electronically or by other means, excluding anonymized information.”</p><br />
<br />
== 3. The Scope of PIPL ==<br />
<p>PIPL applies to the processing of personal information of natural persons within China (Article 3), while also having explicit extraterritorial reach, applying to processing outside China where:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*the purpose is to provide products or services to persons within China;<br />
*the purpose is to analyze or assess the behavior of persons within China; or<br />
*other circumstances provided by law or administrative regulations [https://www.dlapiperdataprotection.com/index.html?c=CN apply].<br />
<br />
== 4. Data Portability under PIPL Article 45 ==<br />
<p>Article 45 of the PIPL sets out China’s primary data-portability terms:</p><br />
<p>“Individuals have the right to access and copy their personal information from personal information processors, except where laws or administrative regulations provide otherwise. Where an individual requests access to or copying of personal information, the personal information processor shall provide it in a timely manner.</p><br />
<p>Where an individual requests the transfer of personal information to a personal information processor designated by the individual, where the conditions set by the national cyberspace authority (hereon abbreviated as “CAC”) are met, the personal information processor shall provide a means for such transfer.”</p><br />
<p>When the scope of Article 45 of the PIPL is reviewed, it is seen that the data portability right:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*- applies to all personal information processors;<br />
*- has no size threshold or gatekeeper designation, whereby a small enterprises to large platforms are, in principle, equally subject to the provision;<br />
*- is limited to personal information;<br />
*- does not encompass non-personal data, including machine-generated, anonymized and IoT data.<br />
*- not confined to processing based on consent or contract (until the DSMR clarified, as elaborated below),<br />
*- not expressly limited to data “provided by” the individual (until the DSMR clarified, as elaborated below)<br />
<p>At first, the PIPL was construed to be vague in terms of this data portability clause, since the data portability conditions were awaited to be announced by CAC. The conditions referred to in PIPL Article 45 have since been elaborated in Article 25 of the Network Data Security Management Regulations ([https://www.gov.cn/zhengce/content/202409/content_6977766.htm DSMR]), (Official English Ministry of Justice [https://en.moj.gov.cn/pdf/RegulationsonNetworkDataSecurityManagement.pdf text]) promulgated by the State Council on 30 September 2024 and effective from 1 January 2025. The Regulations are a State Council administrative regulation, not an instrument issued solely by the CAC. They nonetheless respond to PIPL Art. 45’s reference to conditions set by the CAC and operate within China’s broader CAC-centred data-governance framework.</p><br />
<p>Article 25 is [https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902 widely understood] as implementing and further specifying the PIPL’s data-portability right. Nonetheless, the provision does not itself establish a fully mature interoperability regime comparable to the EU framework: further technical standards, procedural guidance, and enforcement practice remain relevant to the right’s practical exercise.</p><br />
<p>DSMR Article 25 reads as follows:</p><br />
<p>“For requests for transferring personal information that meets the following conditions, a network data processor shall provide means for other network data processors designated by the individual to access and obtain relevant personal information:</p><br />
<p>(1) the true identity of the requester can be verified;</p><br />
<p>(2) the requested transfer involves personal information provided with the individual's consent or collected based on a contract;</p><br />
<p>(3) the transfer of personal information is technically feasible; and</p><br />
<p>(4) the transfer of personal information does not harm the legitimate rights and interests of others. Where the number of transfer requests significantly exceeds a reasonable limit, the network data processor may charge necessary fees based on the cost of transferring personal information.”</p><br />
<p>'''Lack of Direction in Implementation'''</p><br />
<p>Implementation is lacking, although lawyers’ [https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902 commentary] describes Article 25 as an “expansion and further specification” of the portability right under PIPL Art. 45.&nbsp;</p><br />
<p>Article 25 of the DSMR does not by itself create a fully mature interoperability regime. Further CAC rules, technical standards, transfer formats, authentication procedures, and enforcement practice may still be needed for the right to operate consistently in practice. We distinguish between: (1) the existence of regulatory conditions, which Article 25 of the DSMR supplies; and (2) complete operational implementation, which remains dependent on technical and administrative development.</p><br />
<br />
== 5. Implementation and Case Law ==<br />
<p>We identified no published Chinese judgment directly applying the transfer right in PIPL Art. 45(3). Indeed, Courts have addressed portability indirectly, mainly through unfair competition law. On 28 August 2025 the Supreme People's Court (https://www.court.gov.cn/zixun/xiangqing/474431.html), released their first batch of guiding cases devoted to data rights. Two of these stand out in terms of data portability, and are discussed below, although the rulings are not based on data portability provisions under the PIPL:</p><br />
#Guiding Case No. 263: The case concerned a dispute between two recruitment platforms and was decided before the PIPL entered into force, on the basis of Art. 2 of the Anti-Unfair Competition Law. The court held that a platform which, with the user's authorization, transfers data that user obtained on another platform does not engage in unfair competition, provided it does not disrupt market order. The original platform holds protected interests in data it has invested in, but it may not prevent users from transferring data they lawfully hold.<br />
<p><br></p><br />
#Guiding Case No. 262 (https://www.court.gov.cn/zixun/xiangqing/474431.html), states that unauthorized scraping that substantially replaces the original platform's service is unfair competition (https://cms.law/en/chn/legal-updates/china-s-supreme-court-releases-six-guiding-cases-on-data-rights-providing-insights-for-corporate-counsels).<br />
<p>In a judgment of 8 September 2023, the Guangzhou Internet [https://www.hunton.com/privacy-and-information-security-law/the-first-case-in-china-on-personal-information-protection-in-cross-border-transfer-scenario Court] held that the rights to be informed and to decide are the core personal information rights, whereas the rights of access, copy, portability, correction, supplementation and explanation are instrumental rights. This case pertained to the necessity of the personal information processor’s (in GDPR terms, data controller’s) transfer of data abroad. Albeit not being directly related to data portability, this case classified data portability as a supplementary right.</p><br />
<p>Overall, there is no evidence yet that the individual transfer right works in practice. Data portability in China has so far been developed by the courts and framed by competition and data-circulation concerns rather than by data protection.</p><br />
<p>In their [https://doi.org/10.1016/j.clsr.2024.105994 article] “''From brussels effect to gravity assists: Understanding the evolution of the GDPR-inspired personal information protection law in China''”, Wenlong Li and Jiahong Chen have stated that there is much space left for local courts to decide on the nature, scope and impact of data portability rights on a case-by-case basis. It should be noted, as a significant caveat, that there exists a scant corpus of case-law, and the few decisions that are publicly accessible are inadequate to form a coherent pattern.</p><br />
<p>Despite the interpretative powers granted by the PIPL to the CAC, the authority remains relatively passive in elucidating and detailing the provisions of the PIPL through official guidelines.</p><br />
<br />
== 6. Public and Private Sector ==<br />
<p>PIPL applies to both public and private sector processors.</p><br />
<p>State organs are specifically addressed in Articles 33 through 38 of the [https://en.spp.gov.cn/2021-12/29/c_948419.htm PIPL] and receive some exemptions, such as the absence of a consent requirement where processing is necessary to perform statutory duties or obligations. PIPL’s Article 45 on data portability does not expressly exclude state organs, but has a very broad general carve-out “except where laws or administrative regulations provide otherwise”. In terms of setting out a broad exception regime, this article may be construed as similar to the exceptions under GDPR Article 23 (this subject as a topic exceeds the scope of this research).</p><br />
<br />
== 7. Related Legislation: Data Security Law (DSL, 2021) ==<br />
<p>The [https://www.chinalawtranslate.com/en/anti-monopoly-law-2022/ DSL] classifies data into tiers: general, important, and core national data. It imposes corresponding security obligations. It contains no portability right. Restrictions on cross-border transfers of “important data” may limit the practical exercise of portability. We will not delve into this piece of legislation and its application, as it vastly remains outside the scope of this research.</p><br />
<p>A related legislative framework is also encountered in Article 9 of the 2022 Anti-Monopoly Law, providing that undertakings must not use data and algorithms, technology, capital advantages, platform rules, or similar means to engage in monopolistic conduct prohibited by the law.</p><br />
<br />
== 8. Comparison of the Chinese Data Portability Regime with the EU Data Portability Regime ==<br />
<br />
#''' ''''''The EU'''<br />
<p>The EU portability right [https://ejlt.org/index.php/ejlt/article/view/988 originated] in Article 18(1) of the draft GDPR as a way to facilitate switching between online services, although the final provision narrowed its scope. GDPR’s Article 20 gives individuals more control over personal data and can support data flows within the EU by enabling the provision of a copy of personal data or a direct transfer between controllers.</p><br />
<p>The scope of the GDPR based data portability right encompasses the [https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:02016R0679-20160504 following]:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*personal data processed on the basis of consent or a contract:&nbsp;<br />
*non-personal data falls outside the scope of the GDPR entirely,<br />
*the right applies to SMEs as well as large technology firms (similar to the Chinese scope).<br />
*the right is free of charge and may be exercised at any time (subject to limits such as deletion/anonymization of the data, interference with a public-interest task, and the rights and freedoms of others).<br />
<p><br></p><br />
<p>The EU’s [https://ec.europa.eu/newsroom/article29/items/611233 Article 29 Working Party Guidelines on the right to "data portability"] shed light on the application and intent of the data portability right, as quoted below:</p><br />
<p>“It allows for data subjects to receive the personal data that they have provided to a controller, in a structured, commonly used and machine-readable format, and to transmit those data to another data controller. The purpose of this new right is to empower the data subject and give him/her more control over the personal data concerning him or her. Since it allows the direct transmission of personal data from one data controller to another, the right to data portability is also an important tool that will support the free flow of personal data in the EU and foster competition between controllers. It will facilitate switching between different service providers, and will therefore foster the development of new services in the context of the digital single market strategy.”</p><br />
<p><br></p><br />
'''Comparative analysis of GDPR and PIPL:'''<p>Compared with the EU framework, China’s Article 25 is a significant move from a high-level statutory portability clause toward specified regulatory conditions. Yet the availability of concrete technical standards and consistent enforcement remains a central practical question.</p><br />
<p>As [https://doi.org/10.1016/j.clsr.2024.105994 identified by Wenlong Li and Jiahong Chen]:</p><br />
<p>“unlike the EU's cherishment of data protection as a freestanding, fundamental right, China's placement of personal information protection as a legally protectable interest in its legal order is further down the legal hierarchy to such an extent that its legal position has significantly affected how personal information protection is balanced against other rights and interests. Particularly relevant rights include the right to conduct a business (not formulated explicitly in China), economic growth, as well as cyber sovereignty. Personal information protection, even combined with the right to privacy, has never been elevated to the highest level of hierarchy as a fundamental or constitutional right in China.”</p><br />
<p>&nbsp;“…China navigates through a patchwork of internal considerations, international standards, and strategic choices, ultimately sculpting a data protection regime that has a similar appearance to the GDPR but aligns with its distinct political, cultural and legal landscape.”</p><br />
<p>“Unlike the US, China is not a major exporter of digital services to the EU, which gives the country a much weaker incentive to align its data privacy law in an attempt to facilitate the free flow of personal data from the EU.”</p><br />
<p>In light of these valuable considerations, it is concluded that in the EU, data protection is recognized as an autonomous fundamental right. In China, by contrast, personal information protection is treated as a ''legally protected interest'', which places it much lower in the legal hierarchy. This weaker status shapes how it is weighed against competing considerations, such as the freedom to conduct a business, economic development and cyber sovereignty. Neither personal information protection nor the right to privacy, whether taken separately or together, has ever been raised to the rank of a fundamental or constitutional right in China. China's approach results from a combination of domestic priorities, international models and strategic decisions. The outcome is a data protection framework that looks similar to the GDPR on the surface but is adapted to China's own political, cultural and legal context. Unlike the United States, China exports few digital services to the EU. It therefore has much less reason to bring its data protection law into line with EU standards in order to secure the free flow of personal data from Europe[https://doi.org/10.1016/j.clsr.2024.105994 .]</p><br />
<p><br></p><br />
#''' '''Portability of Non-personal data<br />
#China has no direct equivalent to the EU Data Act’s internet of things data portability regime.<br />
#National security is at the forefront of considerations playing into information transfers abroad.<br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*Unlike the EU legislation’s motto of “free flow of data in the internal market”, China is guarding sovereignty concerns when thinking of the transfer of data.<br />
<p>While data transfers outside of China should not be confused with the general right to data portability, the interplay between the two could be considered. A limitation, or a lack in the adoption of the right to data portability results in less flow of data both within China, and outside of China. While data transfers abroad do not form part of this exercise, it should also be noted that the main driving factor of EU’s data protection regime is the free flow of information within the internal market, while China does not take part in such a union and is therefore not incentivized by such a market goal.</p><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">[[Data:India|India]]</span></span> ==<br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">United States</span></span> ==<br />
in progress</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Data:_Data_Portability&diff=124218Data: Data Portability2026-10-07T10:21:37Z<p>Isiklar Ceren: /* China - Ceren, Sergey, Juliette */</p>
<hr />
<div>= <span dir="ltr" lang="en"><span class="mw-page-title-main">Data: Data Portability</span></span> =<br />
<br />
According to [https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng#art_20 Article 20] of the General Data Protection Regulation, "[the data subject shall have the right to receive the personal data concerning him or her, which he or she has provided to a controller, in a structured, commonly used and machine-readable format and have the right to transmit those data to another controller without hindrance from the controller to which the personal data have been provided" where processing is based on consent or contract and is carried out by automated means. Additionally, the [https://eur-lex.europa.eu/eli/reg/2023/2854/oj/eng Data Act ] foresees that data portability should support interoperability of data processing services, while data portability should also be ensured as part of the [https://eur-lex.europa.eu/eli/reg/2022/1925/oj/eng Digital Markets Act] gatekeeper obligations.<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">Brazil</span></span> ==<br />
<span dir="ltr" lang="en"><span class="mw-page-title-main">in progress</span></span><br />
<br />
= China - Ceren, Sergey, Juliette =<br />
== 1. Overview ==<br />
<p>The Personal Information Protection Law ([https://en.spp.gov.cn/2021-12/29/c_948419.htm PIPL])&nbsp; came into effect on 1 November 2021, much later than the General Data Protection Regulation ([https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02016R0679-20160504 GDPR]) which came into force on 24 May 2016. PIPL is China’s primary legal framework for personal information protection and has notable parallels with the GDPR, while reflecting distinctly Chinese regulatory priorities.</p><br />
<br />
== 2. Key Terms and Definitions in the PIPL are as follows ==<br />
<p>PIPL Article 2: “The '''personal information of natural persons''' shall be protected by law. No organization or individual may infringe upon natural persons’ rights and interests on their personal information.”</p><br />
<p>'''Personal information processor''' (Article 73(1)): “any organization or individual that independently determines the purpose and method of processing personal information.” The term personal information processor is functionally equivalent to the GDPR concept of a data controller.</p><br />
<p>'''Personal information''' (Article 4): “information related to an identified or identifiable natural person, recorded electronically or by other means, excluding anonymized information.”</p><br />
<br />
== 3. The Scope of PIPL ==<br />
<p>PIPL applies to the processing of personal information of natural persons within China (Article 3), while also having explicit extraterritorial reach, applying to processing outside China where:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*the purpose is to provide products or services to persons within China;<br />
*the purpose is to analyze or assess the behavior of persons within China; or<br />
*other circumstances provided by law or administrative regulations [https://www.dlapiperdataprotection.com/index.html?c=CN apply].<br />
<br />
== 4. Data Portability under PIPL Article 45 ==<br />
<p>Article 45 of the PIPL sets out China’s primary data-portability terms:</p><br />
<p>“Individuals have the right to access and copy their personal information from personal information processors, except where laws or administrative regulations provide otherwise. Where an individual requests access to or copying of personal information, the personal information processor shall provide it in a timely manner.</p><br />
<p>Where an individual requests the transfer of personal information to a personal information processor designated by the individual, where the conditions set by the national cyberspace authority (hereon abbreviated as “CAC”) are met, the personal information processor shall provide a means for such transfer.”</p><br />
<p>When the scope of Article 45 of the PIPL is reviewed, it is seen that the data portability right:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*- applies to all personal information processors;<br />
*- has no size threshold or gatekeeper designation, whereby a small enterprises to large platforms are, in principle, equally subject to the provision;<br />
*- is limited to personal information;<br />
*- does not encompass non-personal data, including machine-generated, anonymized and IoT data.<br />
*- not confined to processing based on consent or contract (until the DSMR clarified, as elaborated below),<br />
*- not expressly limited to data “provided by” the individual (until the DSMR clarified, as elaborated below)<br />
<p>At first, the PIPL was construed to be vague in terms of this data portability clause, since the data portability conditions were awaited to be announced by CAC. The conditions referred to in PIPL Article 45 have since been elaborated in Article 25 of the Network Data Security Management Regulations ([https://www.gov.cn/zhengce/content/202409/content_6977766.htm DSMR]), (Official English Ministry of Justice [https://en.moj.gov.cn/pdf/RegulationsonNetworkDataSecurityManagement.pdf text]) promulgated by the State Council on 30 September 2024 and effective from 1 January 2025. The Regulations are a State Council administrative regulation, not an instrument issued solely by the CAC. They nonetheless respond to PIPL Art. 45’s reference to conditions set by the CAC and operate within China’s broader CAC-centred data-governance framework.</p><br />
<p>Article 25 is [https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902 widely understood] as implementing and further specifying the PIPL’s data-portability right. Nonetheless, the provision does not itself establish a fully mature interoperability regime comparable to the EU framework: further technical standards, procedural guidance, and enforcement practice remain relevant to the right’s practical exercise.</p><br />
<p>DSMR Article 25 reads as follows:</p><br />
<p>“For requests for transferring personal information that meets the following conditions, a network data processor shall provide means for other network data processors designated by the individual to access and obtain relevant personal information:</p><br />
<p>(1) the true identity of the requester can be verified;</p><br />
<p>(2) the requested transfer involves personal information provided with the individual's consent or collected based on a contract;</p><br />
<p>(3) the transfer of personal information is technically feasible; and</p><br />
<p>(4) the transfer of personal information does not harm the legitimate rights and interests of others. Where the number of transfer requests significantly exceeds a reasonable limit, the network data processor may charge necessary fees based on the cost of transferring personal information.”</p><br />
<p>'''Lack of Direction in Implementation'''</p><br />
<p>Implementation is lacking, although lawyers’ commentary describes Article 25 as an “expansion and further specification” of the portability right under PIPL Art. 45. (https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902)</p><br />
<p>Article 25 of the DSMR does not by itself create a fully mature interoperability regime. Further CAC rules, technical standards, transfer formats, authentication procedures, and enforcement practice may still be needed for the right to operate consistently in practice. We distinguish between: (1) the existence of regulatory conditions, which Article 25 of the DSMR supplies; and (2) complete operational implementation, which remains dependent on technical and administrative development.</p><br />
<br />
== 5. Implementation and Case Law ==<br />
<p>We identified no published Chinese judgment directly applying the transfer right in PIPL Art. 45(3). Indeed, Courts have addressed portability indirectly, mainly through unfair competition law. On 28 August 2025 the Supreme People's Court (https://www.court.gov.cn/zixun/xiangqing/474431.html), released their first batch of guiding cases devoted to data rights. Two of these stand out in terms of data portability, and are discussed below, although the rulings are not based on data portability provisions under the PIPL:</p><br />
#Guiding Case No. 263: The case concerned a dispute between two recruitment platforms and was decided before the PIPL entered into force, on the basis of Art. 2 of the Anti-Unfair Competition Law. The court held that a platform which, with the user's authorization, transfers data that user obtained on another platform does not engage in unfair competition, provided it does not disrupt market order. The original platform holds protected interests in data it has invested in, but it may not prevent users from transferring data they lawfully hold.<br />
<p><br></p><br />
#Guiding Case No. 262 (https://www.court.gov.cn/zixun/xiangqing/474431.html), states that unauthorized scraping that substantially replaces the original platform's service is unfair competition (https://cms.law/en/chn/legal-updates/china-s-supreme-court-releases-six-guiding-cases-on-data-rights-providing-insights-for-corporate-counsels).<br />
<p>In a judgment of 8 September 2023, the Guangzhou Internet [https://www.hunton.com/privacy-and-information-security-law/the-first-case-in-china-on-personal-information-protection-in-cross-border-transfer-scenario Court] held that the rights to be informed and to decide are the core personal information rights, whereas the rights of access, copy, portability, correction, supplementation and explanation are instrumental rights. This case pertained to the necessity of the personal information processor’s (in GDPR terms, data controller’s) transfer of data abroad. Albeit not being directly related to data portability, this case classified data portability as a supplementary right.</p><br />
<p>Overall, there is no evidence yet that the individual transfer right works in practice. Data portability in China has so far been developed by the courts and framed by competition and data-circulation concerns rather than by data protection.</p><br />
<p>In their [https://doi.org/10.1016/j.clsr.2024.105994 article] “''From brussels effect to gravity assists: Understanding the evolution of the GDPR-inspired personal information protection law in China''”, Wenlong Li and Jiahong Chen have stated that there is much space left for local courts to decide on the nature, scope and impact of data portability rights on a case-by-case basis. It should be noted, as a significant caveat, that there exists a scant corpus of case-law, and the few decisions that are publicly accessible are inadequate to form a coherent pattern.</p><br />
<p>Despite the interpretative powers granted by the PIPL to the CAC, the authority remains relatively passive in elucidating and detailing the provisions of the PIPL through official guidelines.</p><br />
<br />
== 6. Public and Private Sector ==<br />
<p>PIPL applies to both public and private sector processors.</p><br />
<p>State organs are specifically addressed in Articles 33 through 38 of the [https://en.spp.gov.cn/2021-12/29/c_948419.htm PIPL] and receive some exemptions, such as the absence of a consent requirement where processing is necessary to perform statutory duties or obligations. PIPL’s Article 45 on data portability does not expressly exclude state organs, but has a very broad general carve-out “except where laws or administrative regulations provide otherwise”. In terms of setting out a broad exception regime, this article may be construed as similar to the exceptions under GDPR Article 23 (this subject as a topic exceeds the scope of this research).</p><br />
<br />
== 7. Related Legislation: Data Security Law (DSL, 2021) ==<br />
<p>The [https://www.chinalawtranslate.com/en/anti-monopoly-law-2022/ DSL] classifies data into tiers: general, important, and core national data. It imposes corresponding security obligations. It contains no portability right. Restrictions on cross-border transfers of “important data” may limit the practical exercise of portability. We will not delve into this piece of legislation and its application, as it vastly remains outside the scope of this research.</p><br />
<p>A related legislative framework is also encountered in Article 9 of the 2022 Anti-Monopoly Law, providing that undertakings must not use data and algorithms, technology, capital advantages, platform rules, or similar means to engage in monopolistic conduct prohibited by the law.</p><br />
<br />
== 8. Comparison of the Chinese Data Portability Regime with the EU Data Portability Regime ==<br />
<br />
#''' ''''''The EU'''<br />
<p>The EU portability right [https://ejlt.org/index.php/ejlt/article/view/988 originated] in Article 18(1) of the draft GDPR as a way to facilitate switching between online services, although the final provision narrowed its scope. GDPR’s Article 20 gives individuals more control over personal data and can support data flows within the EU by enabling the provision of a copy of personal data or a direct transfer between controllers.</p><br />
<p>The scope of the GDPR based data portability right encompasses the [https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:02016R0679-20160504 following]:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*personal data processed on the basis of consent or a contract:&nbsp;<br />
*non-personal data falls outside the scope of the GDPR entirely,<br />
*the right applies to SMEs as well as large technology firms (similar to the Chinese scope).<br />
*the right is free of charge and may be exercised at any time (subject to limits such as deletion/anonymization of the data, interference with a public-interest task, and the rights and freedoms of others).<br />
<p><br></p><br />
<p>The EU’s [https://ec.europa.eu/newsroom/article29/items/611233 Article 29 Working Party Guidelines on the right to "data portability"] shed light on the application and intent of the data portability right, as quoted below:</p><br />
<p>“It allows for data subjects to receive the personal data that they have provided to a controller, in a structured, commonly used and machine-readable format, and to transmit those data to another data controller. The purpose of this new right is to empower the data subject and give him/her more control over the personal data concerning him or her. Since it allows the direct transmission of personal data from one data controller to another, the right to data portability is also an important tool that will support the free flow of personal data in the EU and foster competition between controllers. It will facilitate switching between different service providers, and will therefore foster the development of new services in the context of the digital single market strategy.”</p><br />
<p><br></p><br />
'''Comparative analysis of GDPR and PIPL:'''<p>Compared with the EU framework, China’s Article 25 is a significant move from a high-level statutory portability clause toward specified regulatory conditions. Yet the availability of concrete technical standards and consistent enforcement remains a central practical question.</p><br />
<p>As [https://doi.org/10.1016/j.clsr.2024.105994 identified by Wenlong Li and Jiahong Chen]:</p><br />
<p>“unlike the EU's cherishment of data protection as a freestanding, fundamental right, China's placement of personal information protection as a legally protectable interest in its legal order is further down the legal hierarchy to such an extent that its legal position has significantly affected how personal information protection is balanced against other rights and interests. Particularly relevant rights include the right to conduct a business (not formulated explicitly in China), economic growth, as well as cyber sovereignty. Personal information protection, even combined with the right to privacy, has never been elevated to the highest level of hierarchy as a fundamental or constitutional right in China.”</p><br />
<p>&nbsp;“…China navigates through a patchwork of internal considerations, international standards, and strategic choices, ultimately sculpting a data protection regime that has a similar appearance to the GDPR but aligns with its distinct political, cultural and legal landscape.”</p><br />
<p>“Unlike the US, China is not a major exporter of digital services to the EU, which gives the country a much weaker incentive to align its data privacy law in an attempt to facilitate the free flow of personal data from the EU.”</p><br />
<p>In light of these valuable considerations, it is concluded that in the EU, data protection is recognized as an autonomous fundamental right. In China, by contrast, personal information protection is treated as a ''legally protected interest'', which places it much lower in the legal hierarchy. This weaker status shapes how it is weighed against competing considerations, such as the freedom to conduct a business, economic development and cyber sovereignty. Neither personal information protection nor the right to privacy, whether taken separately or together, has ever been raised to the rank of a fundamental or constitutional right in China. China's approach results from a combination of domestic priorities, international models and strategic decisions. The outcome is a data protection framework that looks similar to the GDPR on the surface but is adapted to China's own political, cultural and legal context. Unlike the United States, China exports few digital services to the EU. It therefore has much less reason to bring its data protection law into line with EU standards in order to secure the free flow of personal data from Europe[https://doi.org/10.1016/j.clsr.2024.105994 .]</p><br />
<p><br></p><br />
#''' '''Portability of Non-personal data<br />
#China has no direct equivalent to the EU Data Act’s internet of things data portability regime.<br />
#National security is at the forefront of considerations playing into information transfers abroad.<br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*Unlike the EU legislation’s motto of “free flow of data in the internal market”, China is guarding sovereignty concerns when thinking of the transfer of data.<br />
<p>While data transfers outside of China should not be confused with the general right to data portability, the interplay between the two could be considered. A limitation, or a lack in the adoption of the right to data portability results in less flow of data both within China, and outside of China. While data transfers abroad do not form part of this exercise, it should also be noted that the main driving factor of EU’s data protection regime is the free flow of information within the internal market, while China does not take part in such a union and is therefore not incentivized by such a market goal.</p><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">[[Data:India|India]]</span></span> ==<br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">United States</span></span> ==<br />
in progress</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Data:_Data_Portability&diff=124217Data: Data Portability2026-10-07T09:51:22Z<p>Isiklar Ceren: /* China */</p>
<hr />
<div>= <span dir="ltr" lang="en"><span class="mw-page-title-main">Data: Data Portability</span></span> =<br />
<br />
According to [https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng#art_20 Article 20] of the General Data Protection Regulation, "[the data subject shall have the right to receive the personal data concerning him or her, which he or she has provided to a controller, in a structured, commonly used and machine-readable format and have the right to transmit those data to another controller without hindrance from the controller to which the personal data have been provided" where processing is based on consent or contract and is carried out by automated means. Additionally, the [https://eur-lex.europa.eu/eli/reg/2023/2854/oj/eng Data Act ] foresees that data portability should support interoperability of data processing services, while data portability should also be ensured as part of the [https://eur-lex.europa.eu/eli/reg/2022/1925/oj/eng Digital Markets Act] gatekeeper obligations.<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">Brazil</span></span> ==<br />
<span dir="ltr" lang="en"><span class="mw-page-title-main">in progress</span></span><br />
<br />
= China - Ceren, Sergey, Juliette =<br />
== 1. Overview ==<br />
<p>The Personal Information Protection Law ([https://en.spp.gov.cn/2021-12/29/c_948419.htm PIPL])&nbsp; came into effect on 1 November 2021, much later than the General Data Protection Regulation ([https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02016R0679-20160504 GDPR]) which came into force on 24 May 2016. PIPL is China’s primary legal framework for personal information protection and has notable parallels with the GDPR, while reflecting distinctly Chinese regulatory priorities.</p><br />
<br />
== 2. Key Terms and Definitions in the PIPL are as follows ==<br />
<p>PIPL Article 2: “The '''personal information of natural persons''' shall be protected by law. No organization or individual may infringe upon natural persons’ rights and interests on their personal information.”</p><br />
<p>'''Personal information processor''' (Article 73(1)): “any organization or individual that independently determines the purpose and method of processing personal information.” The term personal information processor is functionally equivalent to the GDPR concept of a data controller.</p><br />
<p>'''Personal information''' (Article 4): “information related to an identified or identifiable natural person, recorded electronically or by other means, excluding anonymized information.”</p><br />
<br />
== 3. The Scope of PIPL ==<br />
<p>PIPL applies to the processing of personal information of natural persons within China (Article 3), while also having explicit extraterritorial reach, applying to processing outside China where:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*the purpose is to provide products or services to persons within China;<br />
*the purpose is to analyze or assess the behavior of persons within China; or<br />
*other circumstances provided by law or administrative regulations [https://www.dlapiperdataprotection.com/index.html?c=CN apply].<br />
<br />
== 4. Data Portability under PIPL Article 45 ==<br />
<p>Article 45 of the PIPL sets out China’s primary data-portability terms:</p><br />
<p>“Individuals have the right to access and copy their personal information from personal information processors, except where laws or administrative regulations provide otherwise. Where an individual requests access to or copying of personal information, the personal information processor shall provide it in a timely manner.</p><br />
<p>Where an individual requests the transfer of personal information to a personal information processor designated by the individual, where the conditions set by the national cyberspace authority (hereon abbreviated as “CAC”) are met, the personal information processor shall provide a means for such transfer.”</p><br />
<p>When the scope of Article 45 of the PIPL is reviewed, it is seen that the data portability right:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*- applies to all personal information processors;<br />
*- has no size threshold or gatekeeper designation, whereby a small enterprises to large platforms are, in principle, equally subject to the provision;<br />
*- is limited to personal information;<br />
*- does not encompass non-personal data, including machine-generated, anonymized and IoT data.<br />
*- not confined to processing based on consent or contract (until the DSMR clarified, as elaborated below),<br />
*- not expressly limited to data “provided by” the individual (until the DSMR clarified, as elaborated below)<br />
<p>At first, the PIPL was construed to be vague in terms of this data portability clause, since the data portability conditions were awaited to be announced by CAC. The conditions referred to in PIPL Article 45 have since been elaborated in Article 25 of the Network Data Security Management Regulations ([https://www.gov.cn/zhengce/content/202409/content_6977766.htm DSMR]), (Official English Ministry of Justice [https://en.moj.gov.cn/pdf/RegulationsonNetworkDataSecurityManagement.pdf text]) promulgated by the State Council on 30 September 2024 and effective from 1 January 2025. The Regulations are a State Council administrative regulation, not an instrument issued solely by the CAC. They nonetheless respond to PIPL Art. 45’s reference to conditions set by the CAC and operate within China’s broader CAC-centred data-governance framework.</p><br />
<p>Article 25 is [https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902 widely understood] as implementing and further specifying the PIPL’s data-portability right. Nonetheless, the provision does not itself establish a fully mature interoperability regime comparable to the EU framework: further technical standards, procedural guidance, and enforcement practice remain relevant to the right’s practical exercise.</p><br />
<p>DSMR Article 25 reads as follows:</p><br />
<p>“For requests for transferring personal information that meets the following conditions, a network data processor shall provide means for other network data processors designated by the individual to access and obtain relevant personal information:</p><br />
<p>(1) the true identity of the requester can be verified;</p><br />
<p>(2) the requested transfer involves personal information provided with the individual's consent or collected based on a contract;</p><br />
<p>(3) the transfer of personal information is technically feasible; and</p><br />
<p>(4) the transfer of personal information does not harm the legitimate rights and interests of others. Where the number of transfer requests significantly exceeds a reasonable limit, the network data processor may charge necessary fees based on the cost of transferring personal information.”</p><br />
<p>'''Lack of Direction in Implementation'''</p><br />
<p>Implementation is lacking, although lawyers’ commentary describes Article 25 as an “expansion and further specification” of the portability right under PIPL Art. 45. (https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902)</p><br />
<p>Article 25 of the DSMR does not by itself create a fully mature interoperability regime. Further CAC rules, technical standards, transfer formats, authentication procedures, and enforcement practice may still be needed for the right to operate consistently in practice. We distinguish between: (1) the existence of regulatory conditions, which Article 25 of the DSMR supplies; and (2) complete operational implementation, which remains dependent on technical and administrative development.</p><br />
<br />
== 5. Implementation and Case Law ==<br />
<p>We identified no published Chinese judgment directly applying the transfer right in PIPL Art. 45(3). Indeed, Courts have addressed portability indirectly, mainly through unfair competition law. On 28 August 2025 the Supreme People's Court (https://www.court.gov.cn/zixun/xiangqing/474431.html), released their first batch of guiding cases devoted to data rights. Two of these stand out in terms of data portability, and are discussed below, although the rulings are not based on data portability provisions under the PIPL:</p><br />
#Guiding Case No. 263: The case concerned a dispute between two recruitment platforms and was decided before the PIPL entered into force, on the basis of Art. 2 of the Anti-Unfair Competition Law. The court held that a platform which, with the user's authorization, transfers data that user obtained on another platform does not engage in unfair competition, provided it does not disrupt market order. The original platform holds protected interests in data it has invested in, but it may not prevent users from transferring data they lawfully hold.<br />
<p><br></p><br />
#Guiding Case No. 262 (https://www.court.gov.cn/zixun/xiangqing/474431.html), states that unauthorized scraping that substantially replaces the original platform's service is unfair competition (https://cms.law/en/chn/legal-updates/china-s-supreme-court-releases-six-guiding-cases-on-data-rights-providing-insights-for-corporate-counsels).<br />
<p>In a judgment of 8 September 2023, the Guangzhou Internet Court (https://www.hunton.com/privacy-and-information-security-law/the-first-case-in-china-on-personal-information-protection-in-cross-border-transfer-scenario) held that the rights to be informed and to decide are the core personal information rights, whereas the rights of access, copy, portability, correction, supplementation and explanation are instrumental rights. This case pertained to the necessity of the personal information processor’s (in GDPR terms, data controller’s) transfer of data abroad. Albeit not being directly related to data portability, this case classified data portability as a supplementary right.</p><br />
<p>Overall, there is no evidence yet that the individual transfer right works in practice. Data portability in China has so far been developed by the courts and framed by competition and data-circulation concerns rather than by data protection.</p><br />
<p>https://doi.org/10.1016/j.clsr.2024.105994 -&nbsp; In their article “''From brussels effect to gravity assists: Understanding the evolution of the GDPR-inspired personal information protection law in China''”, Wenlong Li and Jiahong Chen have stated that there is much space left for local courts to decide on the nature, scope and impact of data portability rights on a case-by-case basis. It should be noted, as a significant caveat, that there exists a scant corpus of case-law, and the few decisions that are publicly accessible are inadequate to form a coherent pattern.</p><br />
<p>Despite the interpretative powers granted by the PIPL to the CAC, the authority remains relatively passive in elucidating and detailing the provisions of the PIPL through official guidelines.</p><br />
<br />
== 6. Public and Private Sector ==<br />
<p>PIPL applies to both public and private sector processors.</p><br />
<p>State organs are specifically addressed in Articles 33 through 38 of the PIPL https://en.spp.gov.cn/2021-12/29/c_948419.htm and receive some exemptions, such as the absence of a consent requirement where processing is necessary to perform statutory duties or obligations. PIPL’s Article 45 on data portability does not expressly exclude state organs, but has a very broad general carve-out “except where laws or administrative regulations provide otherwise”. In terms of setting out a broad exception regime, this article may be construed as similar to the exceptions under GDPR Article 23 (this subject as a topic exceeds the scope of this research).</p><br />
<br />
== 7. Related Legislation: Data Security Law (DSL, 2021) ==<br />
<p>The DSL https://www.chinalawtranslate.com/en/anti-monopoly-law-2022/ classifies data into tiers: general, important, and core national data. It imposes corresponding security obligations. It contains no portability right. Restrictions on cross-border transfers of “important data” may limit the practical exercise of portability. We will not delve into this piece of legislation and its application, as it vastly remains outside the scope of this research.</p><br />
<p>A related legislative framework is also encountered in Article 9 of the 2022 Anti-Monopoly Law, providing that undertakings must not use data and algorithms, technology, capital advantages, platform rules, or similar means to engage in monopolistic conduct prohibited by the law.</p><br />
<br />
== 8. Comparison of the Chinese Data Portability Regime with the EU Data Portability Regime ==<br />
<br />
#''' ''''''The EU'''<br />
<p>The EU portability right originated in Article 18(1) of the draft GDPR as a way to facilitate switching between online services, although the final provision narrowed its scope. https://ejlt.org/index.php/ejlt/article/view/988. GDPR’s Article 20 gives individuals more control over personal data and can support data flows within the EU by enabling the provision of a copy of personal data or a direct transfer between controllers.</p><br />
<p>The scope of the GDPR based data portability right encompasses the following:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*personal data processed on the basis of consent or a contract: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:02016R0679-20160504<br />
*non-personal data falls outside the scope of the GDPR entirely,<br />
*the right applies to SMEs as well as large technology firms (similar to the Chinese scope).<br />
*the right is free of charge and may be exercised at any time (subject to limits such as deletion/anonymization of the data, interference with a public-interest task, and the rights and freedoms of others).<br />
<p><br></p><br />
<p>The EU’s Article 29 Working Party Guidelines on the right to "data portability" https://ec.europa.eu/newsroom/article29/items/611233 shed light on the application and intent of the data portability right, as quoted below:</p><br />
<p>“It allows for data subjects to receive the personal data that they have provided to a controller, in a structured, commonly used and machine-readable format, and to transmit those data to another data controller. The purpose of this new right is to empower the data subject and give him/her more control over the personal data concerning him or her. Since it allows the direct transmission of personal data from one data controller to another, the right to data portability is also an important tool that will support the free flow of personal data in the EU and foster competition between controllers. It will facilitate switching between different service providers, and will therefore foster the development of new services in the context of the digital single market strategy.”</p><br />
<p><br></p><br />
'''Comparative analysis of GDPR and PIPL:'''<p>Compared with the EU framework, China’s Article 25 is a significant move from a high-level statutory portability clause toward specified regulatory conditions. Yet the availability of concrete technical standards and consistent enforcement remains a central practical question.</p><br />
<p>https://doi.org/10.1016/j.clsr.2024.105994 - As identified by Wenlong Li and Jiahong Chen:</p><br />
<p>“unlike the EU's cherishment of data protection as a freestanding, fundamental right, China's placement of personal information protection as a legally protectable interest in its legal order is further down the legal hierarchy to such an extent that its legal position has significantly affected how personal information protection is balanced against other rights and interests. Particularly relevant rights include the right to conduct a business (not formulated explicitly in China), economic growth, as well as cyber sovereignty. Personal information protection, even combined with the right to privacy, has never been elevated to the highest level of hierarchy as a fundamental or constitutional right in China.”</p><br />
<p>&nbsp;“…China navigates through a patchwork of internal considerations, international standards, and strategic choices, ultimately sculpting a data protection regime that has a similar appearance to the GDPR but aligns with its distinct political, cultural and legal landscape.”</p><br />
<p>“Unlike the US, China is not a major exporter of digital services to the EU, which gives the country a much weaker incentive to align its data privacy law in an attempt to facilitate the free flow of personal data from the EU.”</p><br />
<p>In light of these valuable considerations, it is concluded that in the EU, data protection is recognized as an autonomous fundamental right. In China, by contrast, personal information protection is treated as a ''legally protected interest'', which places it much lower in the legal hierarchy. This weaker status shapes how it is weighed against competing considerations, such as the freedom to conduct a business, economic development and cyber sovereignty. Neither personal information protection nor the right to privacy, whether taken separately or together, has ever been raised to the rank of a fundamental or constitutional right in China. China's approach results from a combination of domestic priorities, international models and strategic decisions. The outcome is a data protection framework that looks similar to the GDPR on the surface but is adapted to China's own political, cultural and legal context. Unlike the United States, China exports few digital services to the EU. It therefore has much less reason to bring its data protection law into line with EU standards in order to secure the free flow of personal data from Europe. (https://doi.org/10.1016/j.clsr.2024.105994)</p><br />
<p><br></p><br />
#''' '''Portability of Non-personal data<br />
#China has no direct equivalent to the EU Data Act’s internet of things data portability regime.<br />
#National security is at the forefront of considerations playing into information transfers abroad.<br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*Unlike the EU legislation’s motto of “free flow of data in the internal market”, China is guarding sovereignty concerns when thinking of the transfer of data.<br />
<p>While data transfers outside of China should not be confused with the general right to data portability, the interplay between the two could be considered. A limitation, or a lack in the adoption of the right to data portability results in less flow of data both within China, and outside of China. While data transfers abroad do not form part of this exercise, it should also be noted that the main driving factor of EU’s data protection regime is the free flow of information within the internal market, while China does not take part in such a union and is therefore not incentivized by such a market goal.</p><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">[[Data:India|India]]</span></span> ==<br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">United States</span></span> ==<br />
in progress</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Data:_Data_Portability&diff=124216Data: Data Portability2026-10-07T09:51:06Z<p>Isiklar Ceren: /* China Personal Information Protection Law (PIPL) Data Portability Summary */</p>
<hr />
<div>= <span dir="ltr" lang="en"><span class="mw-page-title-main">Data: Data Portability</span></span> =<br />
<br />
According to [https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng#art_20 Article 20] of the General Data Protection Regulation, "[the data subject shall have the right to receive the personal data concerning him or her, which he or she has provided to a controller, in a structured, commonly used and machine-readable format and have the right to transmit those data to another controller without hindrance from the controller to which the personal data have been provided" where processing is based on consent or contract and is carried out by automated means. Additionally, the [https://eur-lex.europa.eu/eli/reg/2023/2854/oj/eng Data Act ] foresees that data portability should support interoperability of data processing services, while data portability should also be ensured as part of the [https://eur-lex.europa.eu/eli/reg/2022/1925/oj/eng Digital Markets Act] gatekeeper obligations.<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">Brazil</span></span> ==<br />
<span dir="ltr" lang="en"><span class="mw-page-title-main">in progress</span></span><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">China</span></span> ==<br />
= China - Ceren, Sergey, Juliette =<br />
== 1. Overview ==<br />
<p>The Personal Information Protection Law ([https://en.spp.gov.cn/2021-12/29/c_948419.htm PIPL])&nbsp; came into effect on 1 November 2021, much later than the General Data Protection Regulation ([https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02016R0679-20160504 GDPR]) which came into force on 24 May 2016. PIPL is China’s primary legal framework for personal information protection and has notable parallels with the GDPR, while reflecting distinctly Chinese regulatory priorities.</p><br />
<br />
== 2. Key Terms and Definitions in the PIPL are as follows ==<br />
<p>PIPL Article 2: “The '''personal information of natural persons''' shall be protected by law. No organization or individual may infringe upon natural persons’ rights and interests on their personal information.”</p><br />
<p>'''Personal information processor''' (Article 73(1)): “any organization or individual that independently determines the purpose and method of processing personal information.” The term personal information processor is functionally equivalent to the GDPR concept of a data controller.</p><br />
<p>'''Personal information''' (Article 4): “information related to an identified or identifiable natural person, recorded electronically or by other means, excluding anonymized information.”</p><br />
<br />
== 3. The Scope of PIPL ==<br />
<p>PIPL applies to the processing of personal information of natural persons within China (Article 3), while also having explicit extraterritorial reach, applying to processing outside China where:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*the purpose is to provide products or services to persons within China;<br />
*the purpose is to analyze or assess the behavior of persons within China; or<br />
*other circumstances provided by law or administrative regulations [https://www.dlapiperdataprotection.com/index.html?c=CN apply].<br />
<br />
== 4. Data Portability under PIPL Article 45 ==<br />
<p>Article 45 of the PIPL sets out China’s primary data-portability terms:</p><br />
<p>“Individuals have the right to access and copy their personal information from personal information processors, except where laws or administrative regulations provide otherwise. Where an individual requests access to or copying of personal information, the personal information processor shall provide it in a timely manner.</p><br />
<p>Where an individual requests the transfer of personal information to a personal information processor designated by the individual, where the conditions set by the national cyberspace authority (hereon abbreviated as “CAC”) are met, the personal information processor shall provide a means for such transfer.”</p><br />
<p>When the scope of Article 45 of the PIPL is reviewed, it is seen that the data portability right:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*- applies to all personal information processors;<br />
*- has no size threshold or gatekeeper designation, whereby a small enterprises to large platforms are, in principle, equally subject to the provision;<br />
*- is limited to personal information;<br />
*- does not encompass non-personal data, including machine-generated, anonymized and IoT data.<br />
*- not confined to processing based on consent or contract (until the DSMR clarified, as elaborated below),<br />
*- not expressly limited to data “provided by” the individual (until the DSMR clarified, as elaborated below)<br />
<p>At first, the PIPL was construed to be vague in terms of this data portability clause, since the data portability conditions were awaited to be announced by CAC. The conditions referred to in PIPL Article 45 have since been elaborated in Article 25 of the Network Data Security Management Regulations ([https://www.gov.cn/zhengce/content/202409/content_6977766.htm DSMR]), (Official English Ministry of Justice [https://en.moj.gov.cn/pdf/RegulationsonNetworkDataSecurityManagement.pdf text]) promulgated by the State Council on 30 September 2024 and effective from 1 January 2025. The Regulations are a State Council administrative regulation, not an instrument issued solely by the CAC. They nonetheless respond to PIPL Art. 45’s reference to conditions set by the CAC and operate within China’s broader CAC-centred data-governance framework.</p><br />
<p>Article 25 is [https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902 widely understood] as implementing and further specifying the PIPL’s data-portability right. Nonetheless, the provision does not itself establish a fully mature interoperability regime comparable to the EU framework: further technical standards, procedural guidance, and enforcement practice remain relevant to the right’s practical exercise.</p><br />
<p>DSMR Article 25 reads as follows:</p><br />
<p>“For requests for transferring personal information that meets the following conditions, a network data processor shall provide means for other network data processors designated by the individual to access and obtain relevant personal information:</p><br />
<p>(1) the true identity of the requester can be verified;</p><br />
<p>(2) the requested transfer involves personal information provided with the individual's consent or collected based on a contract;</p><br />
<p>(3) the transfer of personal information is technically feasible; and</p><br />
<p>(4) the transfer of personal information does not harm the legitimate rights and interests of others. Where the number of transfer requests significantly exceeds a reasonable limit, the network data processor may charge necessary fees based on the cost of transferring personal information.”</p><br />
<p>'''Lack of Direction in Implementation'''</p><br />
<p>Implementation is lacking, although lawyers’ commentary describes Article 25 as an “expansion and further specification” of the portability right under PIPL Art. 45. (https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902)</p><br />
<p>Article 25 of the DSMR does not by itself create a fully mature interoperability regime. Further CAC rules, technical standards, transfer formats, authentication procedures, and enforcement practice may still be needed for the right to operate consistently in practice. We distinguish between: (1) the existence of regulatory conditions, which Article 25 of the DSMR supplies; and (2) complete operational implementation, which remains dependent on technical and administrative development.</p><br />
<br />
== 5. Implementation and Case Law ==<br />
<p>We identified no published Chinese judgment directly applying the transfer right in PIPL Art. 45(3). Indeed, Courts have addressed portability indirectly, mainly through unfair competition law. On 28 August 2025 the Supreme People's Court (https://www.court.gov.cn/zixun/xiangqing/474431.html), released their first batch of guiding cases devoted to data rights. Two of these stand out in terms of data portability, and are discussed below, although the rulings are not based on data portability provisions under the PIPL:</p><br />
#Guiding Case No. 263: The case concerned a dispute between two recruitment platforms and was decided before the PIPL entered into force, on the basis of Art. 2 of the Anti-Unfair Competition Law. The court held that a platform which, with the user's authorization, transfers data that user obtained on another platform does not engage in unfair competition, provided it does not disrupt market order. The original platform holds protected interests in data it has invested in, but it may not prevent users from transferring data they lawfully hold.<br />
<p><br></p><br />
#Guiding Case No. 262 (https://www.court.gov.cn/zixun/xiangqing/474431.html), states that unauthorized scraping that substantially replaces the original platform's service is unfair competition (https://cms.law/en/chn/legal-updates/china-s-supreme-court-releases-six-guiding-cases-on-data-rights-providing-insights-for-corporate-counsels).<br />
<p>In a judgment of 8 September 2023, the Guangzhou Internet Court (https://www.hunton.com/privacy-and-information-security-law/the-first-case-in-china-on-personal-information-protection-in-cross-border-transfer-scenario) held that the rights to be informed and to decide are the core personal information rights, whereas the rights of access, copy, portability, correction, supplementation and explanation are instrumental rights. This case pertained to the necessity of the personal information processor’s (in GDPR terms, data controller’s) transfer of data abroad. Albeit not being directly related to data portability, this case classified data portability as a supplementary right.</p><br />
<p>Overall, there is no evidence yet that the individual transfer right works in practice. Data portability in China has so far been developed by the courts and framed by competition and data-circulation concerns rather than by data protection.</p><br />
<p>https://doi.org/10.1016/j.clsr.2024.105994 -&nbsp; In their article “''From brussels effect to gravity assists: Understanding the evolution of the GDPR-inspired personal information protection law in China''”, Wenlong Li and Jiahong Chen have stated that there is much space left for local courts to decide on the nature, scope and impact of data portability rights on a case-by-case basis. It should be noted, as a significant caveat, that there exists a scant corpus of case-law, and the few decisions that are publicly accessible are inadequate to form a coherent pattern.</p><br />
<p>Despite the interpretative powers granted by the PIPL to the CAC, the authority remains relatively passive in elucidating and detailing the provisions of the PIPL through official guidelines.</p><br />
<br />
== 6. Public and Private Sector ==<br />
<p>PIPL applies to both public and private sector processors.</p><br />
<p>State organs are specifically addressed in Articles 33 through 38 of the PIPL https://en.spp.gov.cn/2021-12/29/c_948419.htm and receive some exemptions, such as the absence of a consent requirement where processing is necessary to perform statutory duties or obligations. PIPL’s Article 45 on data portability does not expressly exclude state organs, but has a very broad general carve-out “except where laws or administrative regulations provide otherwise”. In terms of setting out a broad exception regime, this article may be construed as similar to the exceptions under GDPR Article 23 (this subject as a topic exceeds the scope of this research).</p><br />
<br />
== 7. Related Legislation: Data Security Law (DSL, 2021) ==<br />
<p>The DSL https://www.chinalawtranslate.com/en/anti-monopoly-law-2022/ classifies data into tiers: general, important, and core national data. It imposes corresponding security obligations. It contains no portability right. Restrictions on cross-border transfers of “important data” may limit the practical exercise of portability. We will not delve into this piece of legislation and its application, as it vastly remains outside the scope of this research.</p><br />
<p>A related legislative framework is also encountered in Article 9 of the 2022 Anti-Monopoly Law, providing that undertakings must not use data and algorithms, technology, capital advantages, platform rules, or similar means to engage in monopolistic conduct prohibited by the law.</p><br />
<br />
== 8. Comparison of the Chinese Data Portability Regime with the EU Data Portability Regime ==<br />
<br />
#''' ''''''The EU'''<br />
<p>The EU portability right originated in Article 18(1) of the draft GDPR as a way to facilitate switching between online services, although the final provision narrowed its scope. https://ejlt.org/index.php/ejlt/article/view/988. GDPR’s Article 20 gives individuals more control over personal data and can support data flows within the EU by enabling the provision of a copy of personal data or a direct transfer between controllers.</p><br />
<p>The scope of the GDPR based data portability right encompasses the following:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*personal data processed on the basis of consent or a contract: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:02016R0679-20160504<br />
*non-personal data falls outside the scope of the GDPR entirely,<br />
*the right applies to SMEs as well as large technology firms (similar to the Chinese scope).<br />
*the right is free of charge and may be exercised at any time (subject to limits such as deletion/anonymization of the data, interference with a public-interest task, and the rights and freedoms of others).<br />
<p><br></p><br />
<p>The EU’s Article 29 Working Party Guidelines on the right to "data portability" https://ec.europa.eu/newsroom/article29/items/611233 shed light on the application and intent of the data portability right, as quoted below:</p><br />
<p>“It allows for data subjects to receive the personal data that they have provided to a controller, in a structured, commonly used and machine-readable format, and to transmit those data to another data controller. The purpose of this new right is to empower the data subject and give him/her more control over the personal data concerning him or her. Since it allows the direct transmission of personal data from one data controller to another, the right to data portability is also an important tool that will support the free flow of personal data in the EU and foster competition between controllers. It will facilitate switching between different service providers, and will therefore foster the development of new services in the context of the digital single market strategy.”</p><br />
<p><br></p><br />
'''Comparative analysis of GDPR and PIPL:'''<p>Compared with the EU framework, China’s Article 25 is a significant move from a high-level statutory portability clause toward specified regulatory conditions. Yet the availability of concrete technical standards and consistent enforcement remains a central practical question.</p><br />
<p>https://doi.org/10.1016/j.clsr.2024.105994 - As identified by Wenlong Li and Jiahong Chen:</p><br />
<p>“unlike the EU's cherishment of data protection as a freestanding, fundamental right, China's placement of personal information protection as a legally protectable interest in its legal order is further down the legal hierarchy to such an extent that its legal position has significantly affected how personal information protection is balanced against other rights and interests. Particularly relevant rights include the right to conduct a business (not formulated explicitly in China), economic growth, as well as cyber sovereignty. Personal information protection, even combined with the right to privacy, has never been elevated to the highest level of hierarchy as a fundamental or constitutional right in China.”</p><br />
<p>&nbsp;“…China navigates through a patchwork of internal considerations, international standards, and strategic choices, ultimately sculpting a data protection regime that has a similar appearance to the GDPR but aligns with its distinct political, cultural and legal landscape.”</p><br />
<p>“Unlike the US, China is not a major exporter of digital services to the EU, which gives the country a much weaker incentive to align its data privacy law in an attempt to facilitate the free flow of personal data from the EU.”</p><br />
<p>In light of these valuable considerations, it is concluded that in the EU, data protection is recognized as an autonomous fundamental right. In China, by contrast, personal information protection is treated as a ''legally protected interest'', which places it much lower in the legal hierarchy. This weaker status shapes how it is weighed against competing considerations, such as the freedom to conduct a business, economic development and cyber sovereignty. Neither personal information protection nor the right to privacy, whether taken separately or together, has ever been raised to the rank of a fundamental or constitutional right in China. China's approach results from a combination of domestic priorities, international models and strategic decisions. The outcome is a data protection framework that looks similar to the GDPR on the surface but is adapted to China's own political, cultural and legal context. Unlike the United States, China exports few digital services to the EU. It therefore has much less reason to bring its data protection law into line with EU standards in order to secure the free flow of personal data from Europe. (https://doi.org/10.1016/j.clsr.2024.105994)</p><br />
<p><br></p><br />
#''' '''Portability of Non-personal data<br />
#China has no direct equivalent to the EU Data Act’s internet of things data portability regime.<br />
#National security is at the forefront of considerations playing into information transfers abroad.<br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*Unlike the EU legislation’s motto of “free flow of data in the internal market”, China is guarding sovereignty concerns when thinking of the transfer of data.<br />
<p>While data transfers outside of China should not be confused with the general right to data portability, the interplay between the two could be considered. A limitation, or a lack in the adoption of the right to data portability results in less flow of data both within China, and outside of China. While data transfers abroad do not form part of this exercise, it should also be noted that the main driving factor of EU’s data protection regime is the free flow of information within the internal market, while China does not take part in such a union and is therefore not incentivized by such a market goal.</p><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">[[Data:India|India]]</span></span> ==<br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">United States</span></span> ==<br />
in progress</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Data:_Data_Portability&diff=124215Data: Data Portability2026-10-07T09:48:13Z<p>Isiklar Ceren: Undid revision 124214 by Isiklar Ceren (talk)</p>
<hr />
<div>= <span dir="ltr" lang="en"><span class="mw-page-title-main">Data: Data Portability</span></span> =<br />
<br />
According to [https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng#art_20 Article 20] of the General Data Protection Regulation, "[the data subject shall have the right to receive the personal data concerning him or her, which he or she has provided to a controller, in a structured, commonly used and machine-readable format and have the right to transmit those data to another controller without hindrance from the controller to which the personal data have been provided" where processing is based on consent or contract and is carried out by automated means. Additionally, the [https://eur-lex.europa.eu/eli/reg/2023/2854/oj/eng Data Act ] foresees that data portability should support interoperability of data processing services, while data portability should also be ensured as part of the [https://eur-lex.europa.eu/eli/reg/2022/1925/oj/eng Digital Markets Act] gatekeeper obligations.<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">Brazil</span></span> ==<br />
<span dir="ltr" lang="en"><span class="mw-page-title-main">in progress</span></span><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">China</span></span> ==<br />
= China Personal Information Protection Law (PIPL) Data Portability Summary =<br />
<p>Ceren, Sergey, Juliette</p><p>Word count: 2364</p><p><br></p><br />
== 1. Overview ==<br />
<p>The Personal Information Protection Law (PIPL) https://en.spp.gov.cn/2021-12/29/c_948419.htm came into effect on 1 November 2021, much later than the General Data Protection Regulation (GDPR) https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02016R0679-20160504 which came into force &nbsp;on 24 May 2016. PIPL is China’s primary legal framework for personal information protection and has notable parallels with the GDPR, while reflecting distinctly Chinese regulatory priorities.</p><br />
== 2. Key Terms and Definitions in the PIPL are as follows ==<br />
<p>PIPL Article 2: “The '''personal information of natural persons''' shall be protected by law. No organization or individual may infringe upon natural persons’ rights and interests on their personal information.”</p><p>'''Personal information processor''' (Article 73(1)): “any organization or individual that independently determines the purpose and method of processing personal information.” The term personal information processor is functionally equivalent to the GDPR concept of a data controller.</p><p>'''Personal information''' (Article 4): “information related to an identified or identifiable natural person, recorded electronically or by other means, excluding anonymized information.”</p><br />
== 3. The Scope of PIPL ==<br />
<p>PIPL applies to the processing of personal information of natural persons within China (Article 3), while also having explicit extraterritorial reach, applying to processing outside China where:</p><br />
<br />
<span ><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*the purpose is to provide products or services to persons within China;<br />
*the purpose is to analyze or assess the behavior of persons within China; or<br />
*other circumstances provided by law or administrative regulations apply.<br />
<p>https://www.dlapiperdataprotection.com/index.html?c=CN</p><br />
== 4. Data Portability under PIPL Article 45 ==<br />
<p>Article 45 of the PIPL sets out China’s primary data-portability terms:</p><p>“Individuals have the right to access and copy their personal information from personal information processors, except where laws or administrative regulations provide otherwise. Where an individual requests access to or copying of personal information, the personal information processor shall provide it in a timely manner.</p><p>Where an individual requests the transfer of personal information to a personal information processor designated by the individual, where the conditions set by the national cyberspace authority (hereon abbreviated as “CAC”) are met, the personal information processor shall provide a means for such transfer.”</p><p>When the scope of Article 45 of the PIPL is reviewed, it is seen that the data portability right:</p><br />
<br />
<span ><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*- applies to all personal information processors;<br />
*- has no size threshold or gatekeeper designation, whereby a small enterprises to large platforms are, in principle, equally subject to the provision;<br />
*- is limited to personal information;<br />
*- does not encompass non-personal data, including machine-generated, anonymized and IoT data.<br />
*- not confined to processing based on consent or contract (until the DSMR clarified, as elaborated below),<br />
*- not expressly limited to data “provided by” the individual (until the DSMR clarified, as elaborated below)<br />
<p>At first, the PIPL was construed to be vague in terms of this data portability clause, since the data portability conditions were awaited to be announced by CAC. The conditions referred to in PIPL Article 45 have since been elaborated in Article 25 of the Network Data Security Management Regulations (DSMR) https://www.gov.cn/zhengce/content/202409/content_6977766.htm, (Official English Ministry of Justice text: https://en.moj.gov.cn/pdf/RegulationsonNetworkDataSecurityManagement.pdf) promulgated by the State Council on 30 September 2024 and effective from 1 January 2025. The Regulations are a State Council administrative regulation, not an instrument issued solely by the CAC. They nonetheless respond to PIPL Art. 45’s reference to conditions set by the CAC and operate within China’s broader CAC-centred data-governance framework.</p><p>Article 25 is widely understood as implementing and further specifying the PIPL’s data-portability right. Nonetheless, the provision does not itself establish a fully mature interoperability regime comparable to the EU framework: further technical standards, procedural guidance, and enforcement practice remain relevant to the right’s practical exercise. (https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902)</p><p>DSMR Article 25 reads as follows:</p><p>“For requests for transferring personal information that meets the following conditions, a network data processor shall provide means for other network data processors designated by the individual to access and obtain relevant personal information:</p><p>(1) the true identity of the requester can be verified;</p><p>(2) the requested transfer involves personal information provided with the individual's consent or collected based on a contract;</p><p>(3) the transfer of personal information is technically feasible; and</p><p>(4) the transfer of personal information does not harm the legitimate rights and interests of others. Where the number of transfer requests significantly exceeds a reasonable limit, the network data processor may charge necessary fees based on the cost of transferring personal information.”</p><p>'''Lack of Direction in Implementation'''</p><p>Implementation is lacking, although lawyers’ commentary describes Article 25 as an “expansion and further specification” of the portability right under PIPL Art. 45. (https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902)</p><p>Article 25 of the DSMR does not by itself create a fully mature interoperability regime. Further CAC rules, technical standards, transfer formats, authentication procedures, and enforcement practice may still be needed for the right to operate consistently in practice. We distinguish between: (1) the existence of regulatory conditions, which Article 25 of the DSMR supplies; and (2) complete operational implementation, which remains dependent on technical and administrative development.</p><br />
== 5. Implementation and Case Law ==<br />
<p>We identified no published Chinese judgment directly applying the transfer right in PIPL Art. 45(3). Indeed, Courts have addressed portability indirectly, mainly through unfair competition law. On 28 August 2025 the Supreme People's Court (https://www.court.gov.cn/zixun/xiangqing/474431.html), released their first batch of guiding cases devoted to data rights. Two of these stand out in terms of data portability, and are discussed below, although the rulings are not based on data portability provisions under the PIPL:</p><br />
#Guiding Case No. 263: The case concerned a dispute between two recruitment platforms and was decided before the PIPL entered into force, on the basis of Art. 2 of the Anti-Unfair Competition Law. The court held that a platform which, with the user's authorization, transfers data that user obtained on another platform does not engage in unfair competition, provided it does not disrupt market order. The original platform holds protected interests in data it has invested in, but it may not prevent users from transferring data they lawfully hold.<br />
<p><br></p><br />
#Guiding Case No. 262 (https://www.court.gov.cn/zixun/xiangqing/474431.html), states that unauthorized scraping that substantially replaces the original platform's service is unfair competition (https://cms.law/en/chn/legal-updates/china-s-supreme-court-releases-six-guiding-cases-on-data-rights-providing-insights-for-corporate-counsels).<br />
<p>In a judgment of 8 September 2023, the Guangzhou Internet Court (https://www.hunton.com/privacy-and-information-security-law/the-first-case-in-china-on-personal-information-protection-in-cross-border-transfer-scenario) held that the rights to be informed and to decide are the core personal information rights, whereas the rights of access, copy, portability, correction, supplementation and explanation are instrumental rights. This case pertained to the necessity of the personal information processor’s (in GDPR terms, data controller’s) transfer of data abroad. Albeit not being directly related to data portability, this case classified data portability as a supplementary right.</p><p>Overall, there is no evidence yet that the individual transfer right works in practice. Data portability in China has so far been developed by the courts and framed by competition and data-circulation concerns rather than by data protection.</p><p>https://doi.org/10.1016/j.clsr.2024.105994 -&nbsp; In their article “''From brussels effect to gravity assists: Understanding the evolution of the GDPR-inspired personal information protection law in China''”, Wenlong Li and Jiahong Chen have stated that there is much space left for local courts to decide on the nature, scope and impact of data portability rights on a case-by-case basis. It should be noted, as a significant caveat, that there exists a scant corpus of case-law, and the few decisions that are publicly accessible are inadequate to form a coherent pattern.</p><p>Despite the interpretative powers granted by the PIPL to the CAC, the authority remains relatively passive in elucidating and detailing the provisions of the PIPL through official guidelines.</p><br />
== 6. Public and Private Sector ==<br />
<p>PIPL applies to both public and private sector processors.</p><p>State organs are specifically addressed in Articles 33 through 38 of the PIPL https://en.spp.gov.cn/2021-12/29/c_948419.htm and receive some exemptions, such as the absence of a consent requirement where processing is necessary to perform statutory duties or obligations. PIPL’s Article 45 on data portability does not expressly exclude state organs, but has a very broad general carve-out “except where laws or administrative regulations provide otherwise”. In terms of setting out a broad exception regime, this article may be construed as similar to the exceptions under GDPR Article 23 (this subject as a topic exceeds the scope of this research).</p><br />
== 7. Related Legislation: Data Security Law (DSL, 2021) ==<br />
<p>The DSL https://www.chinalawtranslate.com/en/anti-monopoly-law-2022/ classifies data into tiers: general, important, and core national data. It imposes corresponding security obligations. It contains no portability right. Restrictions on cross-border transfers of “important data” may limit the practical exercise of portability. We will not delve into this piece of legislation and its application, as it vastly remains outside the scope of this research.</p><p>A related legislative framework is also encountered in Article 9 of the 2022 Anti-Monopoly Law, providing that undertakings must not use data and algorithms, technology, capital advantages, platform rules, or similar means to engage in monopolistic conduct prohibited by the law.</p><br />
== 8. Comparison of the Chinese Data Portability Regime with the EU Data Portability Regime ==<br />
<br />
#''' ''''''The EU'''<br />
<p>The EU portability right originated in Article 18(1) of the draft GDPR as a way to facilitate switching between online services, although the final provision narrowed its scope. https://ejlt.org/index.php/ejlt/article/view/988. GDPR’s Article 20 gives individuals more control over personal data and can support data flows within the EU by enabling the provision of a copy of personal data or a direct transfer between controllers.</p><p>The scope of the GDPR based data portability right encompasses the following:</p><br />
<br />
<span ><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*personal data processed on the basis of consent or a contract: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:02016R0679-20160504<br />
*non-personal data falls outside the scope of the GDPR entirely,<br />
*the right applies to SMEs as well as large technology firms (similar to the Chinese scope).<br />
*the right is free of charge and may be exercised at any time (subject to limits such as deletion/anonymization of the data, interference with a public-interest task, and the rights and freedoms of others).<br />
<p><br></p><p>The EU’s Article 29 Working Party Guidelines on the right to "data portability" https://ec.europa.eu/newsroom/article29/items/611233 shed light on the application and intent of the data portability right, as quoted below:</p><p>“It allows for data subjects to receive the personal data that they have provided to a controller, in a structured, commonly used and machine-readable format, and to transmit those data to another data controller. The purpose of this new right is to empower the data subject and give him/her more control over the personal data concerning him or her. Since it allows the direct transmission of personal data from one data controller to another, the right to data portability is also an important tool that will support the free flow of personal data in the EU and foster competition between controllers. It will facilitate switching between different service providers, and will therefore foster the development of new services in the context of the digital single market strategy.”</p><p><br></p><br />
<br />
'''Comparative analysis of GDPR and PIPL:'''<p>Compared with the EU framework, China’s Article 25 is a significant move from a high-level statutory portability clause toward specified regulatory conditions. Yet the availability of concrete technical standards and consistent enforcement remains a central practical question.</p><p>https://doi.org/10.1016/j.clsr.2024.105994 - As identified by Wenlong Li and Jiahong Chen:</p><p>“unlike the EU's cherishment of data protection as a freestanding, fundamental right, China's placement of personal information protection as a legally protectable interest in its legal order is further down the legal hierarchy to such an extent that its legal position has significantly affected how personal information protection is balanced against other rights and interests. Particularly relevant rights include the right to conduct a business (not formulated explicitly in China), economic growth, as well as cyber sovereignty. Personal information protection, even combined with the right to privacy, has never been elevated to the highest level of hierarchy as a fundamental or constitutional right in China.”</p><p>&nbsp;“…China navigates through a patchwork of internal considerations, international standards, and strategic choices, ultimately sculpting a data protection regime that has a similar appearance to the GDPR but aligns with its distinct political, cultural and legal landscape.”</p><p>“Unlike the US, China is not a major exporter of digital services to the EU, which gives the country a much weaker incentive to align its data privacy law in an attempt to facilitate the free flow of personal data from the EU.”</p><p>In light of these valuable considerations, it is concluded that in the EU, data protection is recognized as an autonomous fundamental right. In China, by contrast, personal information protection is treated as a ''legally protected interest'', which places it much lower in the legal hierarchy. This weaker status shapes how it is weighed against competing considerations, such as the freedom to conduct a business, economic development and cyber sovereignty. Neither personal information protection nor the right to privacy, whether taken separately or together, has ever been raised to the rank of a fundamental or constitutional right in China. China's approach results from a combination of domestic priorities, international models and strategic decisions. The outcome is a data protection framework that looks similar to the GDPR on the surface but is adapted to China's own political, cultural and legal context. Unlike the United States, China exports few digital services to the EU. It therefore has much less reason to bring its data protection law into line with EU standards in order to secure the free flow of personal data from Europe. (https://doi.org/10.1016/j.clsr.2024.105994)</p><p><br></p><br />
#''' '''Portability of Non-personal data<br />
#China has no direct equivalent to the EU Data Act’s internet of things data portability regime.<br />
#National security is at the forefront of considerations playing into information transfers abroad.<br />
<span ><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*Unlike the EU legislation’s motto of “free flow of data in the internal market”, China is guarding sovereignty concerns when thinking of the transfer of data.<br />
<p>While data transfers outside of China should not be confused with the general right to data portability, the interplay between the two could be considered. A limitation, or a lack in the adoption of the right to data portability results in less flow of data both within China, and outside of China. While data transfers abroad do not form part of this exercise, it should also be noted that the main driving factor of EU’s data protection regime is the free flow of information within the internal market, while China does not take part in such a union and is therefore not incentivized by such a market goal.</p><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">[[Data:India|India]]</span></span> ==<br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">United States</span></span> ==<br />
in progress</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Data:_Data_Portability&diff=124214Data: Data Portability2026-10-07T09:47:43Z<p>Isiklar Ceren: /* China Personal Information Protection Law (PIPL) Data Portability Summary */</p>
<hr />
<div>= <span dir="ltr" lang="en"><span class="mw-page-title-main">Data: Data Portability</span></span> =<br />
<br />
According to [https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng#art_20 Article 20] of the General Data Protection Regulation, "[the data subject shall have the right to receive the personal data concerning him or her, which he or she has provided to a controller, in a structured, commonly used and machine-readable format and have the right to transmit those data to another controller without hindrance from the controller to which the personal data have been provided" where processing is based on consent or contract and is carried out by automated means. Additionally, the [https://eur-lex.europa.eu/eli/reg/2023/2854/oj/eng Data Act ] foresees that data portability should support interoperability of data processing services, while data portability should also be ensured as part of the [https://eur-lex.europa.eu/eli/reg/2022/1925/oj/eng Digital Markets Act] gatekeeper obligations.<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">Brazil</span></span> ==<br />
<span dir="ltr" lang="en"><span class="mw-page-title-main">in progress</span></span><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">China</span></span> ==<br />
== Ceren, Sergey, Juliette ==<br />
<p><br></p><br />
<p><br></p><br />
<p><br></p><br />
<br />
== 1. Overview ==<br />
<p>The Personal Information Protection Law (PIPL) https://en.spp.gov.cn/2021-12/29/c_948419.htm came into effect on 1 November 2021, much later than the General Data Protection Regulation (GDPR) https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02016R0679-20160504 which came into force &nbsp;on 24 May 2016. PIPL is China’s primary legal framework for personal information protection and has notable parallels with the GDPR, while reflecting distinctly Chinese regulatory priorities.</p><br />
<br />
== 2. Key Terms and Definitions in the PIPL are as follows ==<br />
<p>PIPL Article 2: “The '''personal information of natural persons''' shall be protected by law. No organization or individual may infringe upon natural persons’ rights and interests on their personal information.”</p><br />
<p>'''Personal information processor''' (Article 73(1)): “any organization or individual that independently determines the purpose and method of processing personal information.” The term personal information processor is functionally equivalent to the GDPR concept of a data controller.</p><br />
<p>'''Personal information''' (Article 4): “information related to an identified or identifiable natural person, recorded electronically or by other means, excluding anonymized information.”</p><br />
<br />
== 3. The Scope of PIPL ==<br />
<p>PIPL applies to the processing of personal information of natural persons within China (Article 3), while also having explicit extraterritorial reach, applying to processing outside China where:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*the purpose is to provide products or services to persons within China;<br />
*the purpose is to analyze or assess the behavior of persons within China; or<br />
*other circumstances provided by law or administrative regulations apply.<br />
<p>https://www.dlapiperdataprotection.com/index.html?c=CN</p><br />
<br />
== 4. Data Portability under PIPL Article 45 ==<br />
<p>Article 45 of the PIPL sets out China’s primary data-portability terms:</p><br />
<p>“Individuals have the right to access and copy their personal information from personal information processors, except where laws or administrative regulations provide otherwise. Where an individual requests access to or copying of personal information, the personal information processor shall provide it in a timely manner.</p><br />
<p>Where an individual requests the transfer of personal information to a personal information processor designated by the individual, where the conditions set by the national cyberspace authority (hereon abbreviated as “CAC”) are met, the personal information processor shall provide a means for such transfer.”</p><br />
<p>When the scope of Article 45 of the PIPL is reviewed, it is seen that the data portability right:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*- applies to all personal information processors;<br />
*- has no size threshold or gatekeeper designation, whereby a small enterprises to large platforms are, in principle, equally subject to the provision;<br />
*- is limited to personal information;<br />
*- does not encompass non-personal data, including machine-generated, anonymized and IoT data.<br />
*- not confined to processing based on consent or contract (until the DSMR clarified, as elaborated below),<br />
*- not expressly limited to data “provided by” the individual (until the DSMR clarified, as elaborated below)<br />
<p>At first, the PIPL was construed to be vague in terms of this data portability clause, since the data portability conditions were awaited to be announced by CAC. The conditions referred to in PIPL Article 45 have since been elaborated in Article 25 of the Network Data Security Management Regulations (DSMR) https://www.gov.cn/zhengce/content/202409/content_6977766.htm, (Official English Ministry of Justice text: https://en.moj.gov.cn/pdf/RegulationsonNetworkDataSecurityManagement.pdf) promulgated by the State Council on 30 September 2024 and effective from 1 January 2025. The Regulations are a State Council administrative regulation, not an instrument issued solely by the CAC. They nonetheless respond to PIPL Art. 45’s reference to conditions set by the CAC and operate within China’s broader CAC-centred data-governance framework.</p><br />
<p>Article 25 is widely understood as implementing and further specifying the PIPL’s data-portability right. Nonetheless, the provision does not itself establish a fully mature interoperability regime comparable to the EU framework: further technical standards, procedural guidance, and enforcement practice remain relevant to the right’s practical exercise. (https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902)</p><br />
<p>DSMR Article 25 reads as follows:</p><br />
<p>“For requests for transferring personal information that meets the following conditions, a network data processor shall provide means for other network data processors designated by the individual to access and obtain relevant personal information:</p><br />
<p>(1) the true identity of the requester can be verified;</p><br />
<p>(2) the requested transfer involves personal information provided with the individual's consent or collected based on a contract;</p><br />
<p>(3) the transfer of personal information is technically feasible; and</p><br />
<p>(4) the transfer of personal information does not harm the legitimate rights and interests of others. Where the number of transfer requests significantly exceeds a reasonable limit, the network data processor may charge necessary fees based on the cost of transferring personal information.”</p><br />
<p>'''Lack of Direction in Implementation'''</p><br />
<p>Implementation is lacking, although lawyers’ commentary describes Article 25 as an “expansion and further specification” of the portability right under PIPL Art. 45. (https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902)</p><br />
<p>Article 25 of the DSMR does not by itself create a fully mature interoperability regime. Further CAC rules, technical standards, transfer formats, authentication procedures, and enforcement practice may still be needed for the right to operate consistently in practice. We distinguish between: (1) the existence of regulatory conditions, which Article 25 of the DSMR supplies; and (2) complete operational implementation, which remains dependent on technical and administrative development.</p><br />
<br />
== 5. Implementation and Case Law ==<br />
<p>We identified no published Chinese judgment directly applying the transfer right in PIPL Art. 45(3). Indeed, Courts have addressed portability indirectly, mainly through unfair competition law. On 28 August 2025 the Supreme People's Court (https://www.court.gov.cn/zixun/xiangqing/474431.html), released their first batch of guiding cases devoted to data rights. Two of these stand out in terms of data portability, and are discussed below, although the rulings are not based on data portability provisions under the PIPL:</p><br />
#Guiding Case No. 263: The case concerned a dispute between two recruitment platforms and was decided before the PIPL entered into force, on the basis of Art. 2 of the Anti-Unfair Competition Law. The court held that a platform which, with the user's authorization, transfers data that user obtained on another platform does not engage in unfair competition, provided it does not disrupt market order. The original platform holds protected interests in data it has invested in, but it may not prevent users from transferring data they lawfully hold.<br />
<p><br></p><br />
#Guiding Case No. 262 (https://www.court.gov.cn/zixun/xiangqing/474431.html), states that unauthorized scraping that substantially replaces the original platform's service is unfair competition (https://cms.law/en/chn/legal-updates/china-s-supreme-court-releases-six-guiding-cases-on-data-rights-providing-insights-for-corporate-counsels).<br />
<p>In a judgment of 8 September 2023, the Guangzhou Internet Court (https://www.hunton.com/privacy-and-information-security-law/the-first-case-in-china-on-personal-information-protection-in-cross-border-transfer-scenario) held that the rights to be informed and to decide are the core personal information rights, whereas the rights of access, copy, portability, correction, supplementation and explanation are instrumental rights. This case pertained to the necessity of the personal information processor’s (in GDPR terms, data controller’s) transfer of data abroad. Albeit not being directly related to data portability, this case classified data portability as a supplementary right.</p><br />
<p>Overall, there is no evidence yet that the individual transfer right works in practice. Data portability in China has so far been developed by the courts and framed by competition and data-circulation concerns rather than by data protection.</p><br />
<p>https://doi.org/10.1016/j.clsr.2024.105994 -&nbsp; In their article “''From brussels effect to gravity assists: Understanding the evolution of the GDPR-inspired personal information protection law in China''”, Wenlong Li and Jiahong Chen have stated that there is much space left for local courts to decide on the nature, scope and impact of data portability rights on a case-by-case basis. It should be noted, as a significant caveat, that there exists a scant corpus of case-law, and the few decisions that are publicly accessible are inadequate to form a coherent pattern.</p><br />
<p>Despite the interpretative powers granted by the PIPL to the CAC, the authority remains relatively passive in elucidating and detailing the provisions of the PIPL through official guidelines.</p><br />
<br />
== 6. Public and Private Sector ==<br />
<p>PIPL applies to both public and private sector processors.</p><br />
<p>State organs are specifically addressed in Articles 33 through 38 of the PIPL https://en.spp.gov.cn/2021-12/29/c_948419.htm and receive some exemptions, such as the absence of a consent requirement where processing is necessary to perform statutory duties or obligations. PIPL’s Article 45 on data portability does not expressly exclude state organs, but has a very broad general carve-out “except where laws or administrative regulations provide otherwise”. In terms of setting out a broad exception regime, this article may be construed as similar to the exceptions under GDPR Article 23 (this subject as a topic exceeds the scope of this research).</p><br />
<br />
== 7. Related Legislation: Data Security Law (DSL, 2021) ==<br />
<p>The DSL https://www.chinalawtranslate.com/en/anti-monopoly-law-2022/ classifies data into tiers: general, important, and core national data. It imposes corresponding security obligations. It contains no portability right. Restrictions on cross-border transfers of “important data” may limit the practical exercise of portability. We will not delve into this piece of legislation and its application, as it vastly remains outside the scope of this research.</p><br />
<p>A related legislative framework is also encountered in Article 9 of the 2022 Anti-Monopoly Law, providing that undertakings must not use data and algorithms, technology, capital advantages, platform rules, or similar means to engage in monopolistic conduct prohibited by the law.</p><br />
<br />
== 8. Comparison of the Chinese Data Portability Regime with the EU Data Portability Regime ==<br />
<br />
#''' ''''''The EU'''<br />
<p>The EU portability right originated in Article 18(1) of the draft GDPR as a way to facilitate switching between online services, although the final provision narrowed its scope. https://ejlt.org/index.php/ejlt/article/view/988. GDPR’s Article 20 gives individuals more control over personal data and can support data flows within the EU by enabling the provision of a copy of personal data or a direct transfer between controllers.</p><br />
<p>The scope of the GDPR based data portability right encompasses the following:</p><br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*personal data processed on the basis of consent or a contract: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:02016R0679-20160504<br />
*non-personal data falls outside the scope of the GDPR entirely,<br />
*the right applies to SMEs as well as large technology firms (similar to the Chinese scope).<br />
*the right is free of charge and may be exercised at any time (subject to limits such as deletion/anonymization of the data, interference with a public-interest task, and the rights and freedoms of others).<br />
<p><br></p><br />
<p>The EU’s Article 29 Working Party Guidelines on the right to "data portability" https://ec.europa.eu/newsroom/article29/items/611233 shed light on the application and intent of the data portability right, as quoted below:</p><br />
<p>“It allows for data subjects to receive the personal data that they have provided to a controller, in a structured, commonly used and machine-readable format, and to transmit those data to another data controller. The purpose of this new right is to empower the data subject and give him/her more control over the personal data concerning him or her. Since it allows the direct transmission of personal data from one data controller to another, the right to data portability is also an important tool that will support the free flow of personal data in the EU and foster competition between controllers. It will facilitate switching between different service providers, and will therefore foster the development of new services in the context of the digital single market strategy.”</p><br />
<p><br></p><br />
'''Comparative analysis of GDPR and PIPL:'''<p>Compared with the EU framework, China’s Article 25 is a significant move from a high-level statutory portability clause toward specified regulatory conditions. Yet the availability of concrete technical standards and consistent enforcement remains a central practical question.</p><br />
<p>https://doi.org/10.1016/j.clsr.2024.105994 - As identified by Wenlong Li and Jiahong Chen:</p><br />
<p>“unlike the EU's cherishment of data protection as a freestanding, fundamental right, China's placement of personal information protection as a legally protectable interest in its legal order is further down the legal hierarchy to such an extent that its legal position has significantly affected how personal information protection is balanced against other rights and interests. Particularly relevant rights include the right to conduct a business (not formulated explicitly in China), economic growth, as well as cyber sovereignty. Personal information protection, even combined with the right to privacy, has never been elevated to the highest level of hierarchy as a fundamental or constitutional right in China.”</p><br />
<p>&nbsp;“…China navigates through a patchwork of internal considerations, international standards, and strategic choices, ultimately sculpting a data protection regime that has a similar appearance to the GDPR but aligns with its distinct political, cultural and legal landscape.”</p><br />
<p>“Unlike the US, China is not a major exporter of digital services to the EU, which gives the country a much weaker incentive to align its data privacy law in an attempt to facilitate the free flow of personal data from the EU.”</p><br />
<p>In light of these valuable considerations, it is concluded that in the EU, data protection is recognized as an autonomous fundamental right. In China, by contrast, personal information protection is treated as a ''legally protected interest'', which places it much lower in the legal hierarchy. This weaker status shapes how it is weighed against competing considerations, such as the freedom to conduct a business, economic development and cyber sovereignty. Neither personal information protection nor the right to privacy, whether taken separately or together, has ever been raised to the rank of a fundamental or constitutional right in China. China's approach results from a combination of domestic priorities, international models and strategic decisions. The outcome is a data protection framework that looks similar to the GDPR on the surface but is adapted to China's own political, cultural and legal context. Unlike the United States, China exports few digital services to the EU. It therefore has much less reason to bring its data protection law into line with EU standards in order to secure the free flow of personal data from Europe. (https://doi.org/10.1016/j.clsr.2024.105994)</p><br />
<p><br></p><br />
#''' '''Portability of Non-personal data<br />
#China has no direct equivalent to the EU Data Act’s internet of things data portability regime.<br />
#National security is at the forefront of considerations playing into information transfers abroad.<br />
<br />
<span><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*Unlike the EU legislation’s motto of “free flow of data in the internal market”, China is guarding sovereignty concerns when thinking of the transfer of data.<br />
<p>While data transfers outside of China should not be confused with the general right to data portability, the interplay between the two could be considered. A limitation, or a lack in the adoption of the right to data portability results in less flow of data both within China, and outside of China. While data transfers abroad do not form part of this exercise, it should also be noted that the main driving factor of EU’s data protection regime is the free flow of information within the internal market, while China does not take part in such a union and is therefore not incentivized by such a market goal.</p><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">[[Data:India|India]]</span></span> ==<br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">United States</span></span> ==<br />
in progress</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Data:_Data_Portability&diff=124213Data: Data Portability2026-10-07T09:46:52Z<p>Isiklar Ceren: /* China */</p>
<hr />
<div>= <span dir="ltr" lang="en"><span class="mw-page-title-main">Data: Data Portability</span></span> =<br />
<br />
According to [https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng#art_20 Article 20] of the General Data Protection Regulation, "[the data subject shall have the right to receive the personal data concerning him or her, which he or she has provided to a controller, in a structured, commonly used and machine-readable format and have the right to transmit those data to another controller without hindrance from the controller to which the personal data have been provided" where processing is based on consent or contract and is carried out by automated means. Additionally, the [https://eur-lex.europa.eu/eli/reg/2023/2854/oj/eng Data Act ] foresees that data portability should support interoperability of data processing services, while data portability should also be ensured as part of the [https://eur-lex.europa.eu/eli/reg/2022/1925/oj/eng Digital Markets Act] gatekeeper obligations.<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">Brazil</span></span> ==<br />
<span dir="ltr" lang="en"><span class="mw-page-title-main">in progress</span></span><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">China</span></span> ==<br />
= China Personal Information Protection Law (PIPL) Data Portability Summary =<br />
<p>Ceren, Sergey, Juliette</p><p>Word count: 2364</p><p><br></p><br />
== 1. Overview ==<br />
<p>The Personal Information Protection Law (PIPL) https://en.spp.gov.cn/2021-12/29/c_948419.htm came into effect on 1 November 2021, much later than the General Data Protection Regulation (GDPR) https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A02016R0679-20160504 which came into force &nbsp;on 24 May 2016. PIPL is China’s primary legal framework for personal information protection and has notable parallels with the GDPR, while reflecting distinctly Chinese regulatory priorities.</p><br />
== 2. Key Terms and Definitions in the PIPL are as follows ==<br />
<p>PIPL Article 2: “The '''personal information of natural persons''' shall be protected by law. No organization or individual may infringe upon natural persons’ rights and interests on their personal information.”</p><p>'''Personal information processor''' (Article 73(1)): “any organization or individual that independently determines the purpose and method of processing personal information.” The term personal information processor is functionally equivalent to the GDPR concept of a data controller.</p><p>'''Personal information''' (Article 4): “information related to an identified or identifiable natural person, recorded electronically or by other means, excluding anonymized information.”</p><br />
== 3. The Scope of PIPL ==<br />
<p>PIPL applies to the processing of personal information of natural persons within China (Article 3), while also having explicit extraterritorial reach, applying to processing outside China where:</p><br />
<br />
<span ><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*the purpose is to provide products or services to persons within China;<br />
*the purpose is to analyze or assess the behavior of persons within China; or<br />
*other circumstances provided by law or administrative regulations apply.<br />
<p>https://www.dlapiperdataprotection.com/index.html?c=CN</p><br />
== 4. Data Portability under PIPL Article 45 ==<br />
<p>Article 45 of the PIPL sets out China’s primary data-portability terms:</p><p>“Individuals have the right to access and copy their personal information from personal information processors, except where laws or administrative regulations provide otherwise. Where an individual requests access to or copying of personal information, the personal information processor shall provide it in a timely manner.</p><p>Where an individual requests the transfer of personal information to a personal information processor designated by the individual, where the conditions set by the national cyberspace authority (hereon abbreviated as “CAC”) are met, the personal information processor shall provide a means for such transfer.”</p><p>When the scope of Article 45 of the PIPL is reviewed, it is seen that the data portability right:</p><br />
<br />
<span ><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*- applies to all personal information processors;<br />
*- has no size threshold or gatekeeper designation, whereby a small enterprises to large platforms are, in principle, equally subject to the provision;<br />
*- is limited to personal information;<br />
*- does not encompass non-personal data, including machine-generated, anonymized and IoT data.<br />
*- not confined to processing based on consent or contract (until the DSMR clarified, as elaborated below),<br />
*- not expressly limited to data “provided by” the individual (until the DSMR clarified, as elaborated below)<br />
<p>At first, the PIPL was construed to be vague in terms of this data portability clause, since the data portability conditions were awaited to be announced by CAC. The conditions referred to in PIPL Article 45 have since been elaborated in Article 25 of the Network Data Security Management Regulations (DSMR) https://www.gov.cn/zhengce/content/202409/content_6977766.htm, (Official English Ministry of Justice text: https://en.moj.gov.cn/pdf/RegulationsonNetworkDataSecurityManagement.pdf) promulgated by the State Council on 30 September 2024 and effective from 1 January 2025. The Regulations are a State Council administrative regulation, not an instrument issued solely by the CAC. They nonetheless respond to PIPL Art. 45’s reference to conditions set by the CAC and operate within China’s broader CAC-centred data-governance framework.</p><p>Article 25 is widely understood as implementing and further specifying the PIPL’s data-portability right. Nonetheless, the provision does not itself establish a fully mature interoperability regime comparable to the EU framework: further technical standards, procedural guidance, and enforcement practice remain relevant to the right’s practical exercise. (https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902)</p><p>DSMR Article 25 reads as follows:</p><p>“For requests for transferring personal information that meets the following conditions, a network data processor shall provide means for other network data processors designated by the individual to access and obtain relevant personal information:</p><p>(1) the true identity of the requester can be verified;</p><p>(2) the requested transfer involves personal information provided with the individual's consent or collected based on a contract;</p><p>(3) the transfer of personal information is technically feasible; and</p><p>(4) the transfer of personal information does not harm the legitimate rights and interests of others. Where the number of transfer requests significantly exceeds a reasonable limit, the network data processor may charge necessary fees based on the cost of transferring personal information.”</p><p>'''Lack of Direction in Implementation'''</p><p>Implementation is lacking, although lawyers’ commentary describes Article 25 as an “expansion and further specification” of the portability right under PIPL Art. 45. (https://www.dehenglaw.com/CN/tansuocontent/0008/032097/7.aspx?MID=0902)</p><p>Article 25 of the DSMR does not by itself create a fully mature interoperability regime. Further CAC rules, technical standards, transfer formats, authentication procedures, and enforcement practice may still be needed for the right to operate consistently in practice. We distinguish between: (1) the existence of regulatory conditions, which Article 25 of the DSMR supplies; and (2) complete operational implementation, which remains dependent on technical and administrative development.</p><br />
== 5. Implementation and Case Law ==<br />
<p>We identified no published Chinese judgment directly applying the transfer right in PIPL Art. 45(3). Indeed, Courts have addressed portability indirectly, mainly through unfair competition law. On 28 August 2025 the Supreme People's Court (https://www.court.gov.cn/zixun/xiangqing/474431.html), released their first batch of guiding cases devoted to data rights. Two of these stand out in terms of data portability, and are discussed below, although the rulings are not based on data portability provisions under the PIPL:</p><br />
#Guiding Case No. 263: The case concerned a dispute between two recruitment platforms and was decided before the PIPL entered into force, on the basis of Art. 2 of the Anti-Unfair Competition Law. The court held that a platform which, with the user's authorization, transfers data that user obtained on another platform does not engage in unfair competition, provided it does not disrupt market order. The original platform holds protected interests in data it has invested in, but it may not prevent users from transferring data they lawfully hold.<br />
<p><br></p><br />
#Guiding Case No. 262 (https://www.court.gov.cn/zixun/xiangqing/474431.html), states that unauthorized scraping that substantially replaces the original platform's service is unfair competition (https://cms.law/en/chn/legal-updates/china-s-supreme-court-releases-six-guiding-cases-on-data-rights-providing-insights-for-corporate-counsels).<br />
<p>In a judgment of 8 September 2023, the Guangzhou Internet Court (https://www.hunton.com/privacy-and-information-security-law/the-first-case-in-china-on-personal-information-protection-in-cross-border-transfer-scenario) held that the rights to be informed and to decide are the core personal information rights, whereas the rights of access, copy, portability, correction, supplementation and explanation are instrumental rights. This case pertained to the necessity of the personal information processor’s (in GDPR terms, data controller’s) transfer of data abroad. Albeit not being directly related to data portability, this case classified data portability as a supplementary right.</p><p>Overall, there is no evidence yet that the individual transfer right works in practice. Data portability in China has so far been developed by the courts and framed by competition and data-circulation concerns rather than by data protection.</p><p>https://doi.org/10.1016/j.clsr.2024.105994 -&nbsp; In their article “''From brussels effect to gravity assists: Understanding the evolution of the GDPR-inspired personal information protection law in China''”, Wenlong Li and Jiahong Chen have stated that there is much space left for local courts to decide on the nature, scope and impact of data portability rights on a case-by-case basis. It should be noted, as a significant caveat, that there exists a scant corpus of case-law, and the few decisions that are publicly accessible are inadequate to form a coherent pattern.</p><p>Despite the interpretative powers granted by the PIPL to the CAC, the authority remains relatively passive in elucidating and detailing the provisions of the PIPL through official guidelines.</p><br />
== 6. Public and Private Sector ==<br />
<p>PIPL applies to both public and private sector processors.</p><p>State organs are specifically addressed in Articles 33 through 38 of the PIPL https://en.spp.gov.cn/2021-12/29/c_948419.htm and receive some exemptions, such as the absence of a consent requirement where processing is necessary to perform statutory duties or obligations. PIPL’s Article 45 on data portability does not expressly exclude state organs, but has a very broad general carve-out “except where laws or administrative regulations provide otherwise”. In terms of setting out a broad exception regime, this article may be construed as similar to the exceptions under GDPR Article 23 (this subject as a topic exceeds the scope of this research).</p><br />
== 7. Related Legislation: Data Security Law (DSL, 2021) ==<br />
<p>The DSL https://www.chinalawtranslate.com/en/anti-monopoly-law-2022/ classifies data into tiers: general, important, and core national data. It imposes corresponding security obligations. It contains no portability right. Restrictions on cross-border transfers of “important data” may limit the practical exercise of portability. We will not delve into this piece of legislation and its application, as it vastly remains outside the scope of this research.</p><p>A related legislative framework is also encountered in Article 9 of the 2022 Anti-Monopoly Law, providing that undertakings must not use data and algorithms, technology, capital advantages, platform rules, or similar means to engage in monopolistic conduct prohibited by the law.</p><br />
== 8. Comparison of the Chinese Data Portability Regime with the EU Data Portability Regime ==<br />
<br />
#''' ''''''The EU'''<br />
<p>The EU portability right originated in Article 18(1) of the draft GDPR as a way to facilitate switching between online services, although the final provision narrowed its scope. https://ejlt.org/index.php/ejlt/article/view/988. GDPR’s Article 20 gives individuals more control over personal data and can support data flows within the EU by enabling the provision of a copy of personal data or a direct transfer between controllers.</p><p>The scope of the GDPR based data portability right encompasses the following:</p><br />
<br />
<span ><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*personal data processed on the basis of consent or a contract: https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:02016R0679-20160504<br />
*non-personal data falls outside the scope of the GDPR entirely,<br />
*the right applies to SMEs as well as large technology firms (similar to the Chinese scope).<br />
*the right is free of charge and may be exercised at any time (subject to limits such as deletion/anonymization of the data, interference with a public-interest task, and the rights and freedoms of others).<br />
<p><br></p><p>The EU’s Article 29 Working Party Guidelines on the right to "data portability" https://ec.europa.eu/newsroom/article29/items/611233 shed light on the application and intent of the data portability right, as quoted below:</p><p>“It allows for data subjects to receive the personal data that they have provided to a controller, in a structured, commonly used and machine-readable format, and to transmit those data to another data controller. The purpose of this new right is to empower the data subject and give him/her more control over the personal data concerning him or her. Since it allows the direct transmission of personal data from one data controller to another, the right to data portability is also an important tool that will support the free flow of personal data in the EU and foster competition between controllers. It will facilitate switching between different service providers, and will therefore foster the development of new services in the context of the digital single market strategy.”</p><p><br></p><br />
<br />
'''Comparative analysis of GDPR and PIPL:'''<p>Compared with the EU framework, China’s Article 25 is a significant move from a high-level statutory portability clause toward specified regulatory conditions. Yet the availability of concrete technical standards and consistent enforcement remains a central practical question.</p><p>https://doi.org/10.1016/j.clsr.2024.105994 - As identified by Wenlong Li and Jiahong Chen:</p><p>“unlike the EU's cherishment of data protection as a freestanding, fundamental right, China's placement of personal information protection as a legally protectable interest in its legal order is further down the legal hierarchy to such an extent that its legal position has significantly affected how personal information protection is balanced against other rights and interests. Particularly relevant rights include the right to conduct a business (not formulated explicitly in China), economic growth, as well as cyber sovereignty. Personal information protection, even combined with the right to privacy, has never been elevated to the highest level of hierarchy as a fundamental or constitutional right in China.”</p><p>&nbsp;“…China navigates through a patchwork of internal considerations, international standards, and strategic choices, ultimately sculpting a data protection regime that has a similar appearance to the GDPR but aligns with its distinct political, cultural and legal landscape.”</p><p>“Unlike the US, China is not a major exporter of digital services to the EU, which gives the country a much weaker incentive to align its data privacy law in an attempt to facilitate the free flow of personal data from the EU.”</p><p>In light of these valuable considerations, it is concluded that in the EU, data protection is recognized as an autonomous fundamental right. In China, by contrast, personal information protection is treated as a ''legally protected interest'', which places it much lower in the legal hierarchy. This weaker status shapes how it is weighed against competing considerations, such as the freedom to conduct a business, economic development and cyber sovereignty. Neither personal information protection nor the right to privacy, whether taken separately or together, has ever been raised to the rank of a fundamental or constitutional right in China. China's approach results from a combination of domestic priorities, international models and strategic decisions. The outcome is a data protection framework that looks similar to the GDPR on the surface but is adapted to China's own political, cultural and legal context. Unlike the United States, China exports few digital services to the EU. It therefore has much less reason to bring its data protection law into line with EU standards in order to secure the free flow of personal data from Europe. (https://doi.org/10.1016/j.clsr.2024.105994)</p><p><br></p><br />
#''' '''Portability of Non-personal data<br />
#China has no direct equivalent to the EU Data Act’s internet of things data portability regime.<br />
#National security is at the forefront of considerations playing into information transfers abroad.<br />
<span ><br />
<span dir="ltr" lang="en"><span class="mw-page-title-main"></span></span></span><br />
*Unlike the EU legislation’s motto of “free flow of data in the internal market”, China is guarding sovereignty concerns when thinking of the transfer of data.<br />
<p>While data transfers outside of China should not be confused with the general right to data portability, the interplay between the two could be considered. A limitation, or a lack in the adoption of the right to data portability results in less flow of data both within China, and outside of China. While data transfers abroad do not form part of this exercise, it should also be noted that the main driving factor of EU’s data protection regime is the free flow of information within the internal market, while China does not take part in such a union and is therefore not incentivized by such a market goal.</p><br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">[[Data:India|India]]</span></span> ==<br />
<br />
== <span dir="ltr" lang="en"><span class="mw-page-title-main">United States</span></span> ==<br />
in progress</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Governance_by_markets&diff=124110Governance by markets2026-10-04T18:00:03Z<p>Isiklar Ceren: /* Two Sided Markets (Ceren) */</p>
<hr />
<div>= Glossary =<br />
= Data as an input to market power (Sergey) =<br />
<p>In the present digital economy, data has emerged as a valuable economic commodity that entities leverage to gain a competitive edge over their rivals [[https://repository.nls.ac.in/cgi/viewcontent.cgi?article=1478&context=nlsblr 1]]. '''Data''' is an input into production, so businesses that control data can have market power and impede the entry of potential competitors. '''Market power''' refers to a firm's ability to influence the price, output, or other market conditions in its favour, without being constrained by competitive forces [[https://www.tutor2u.net/economics/reference/what-is-meant-by-market-power 2]].</p><br />
<p>'''Data as an input to market power''' means that access to information can help a business limit the competitive pressure it faces. Information about searches, clicks or purchases can improve services and advertising. If competitors cannot obtain comparable information at a reasonable cost, they may struggle to offer an attractive alternative. This can allow a platform to raise prices or worsen quality or privacy protections without losing enough business to make doing so unprofitable. This matters even when a service is free, because competition also concerns advertising charges, personal information and the choices available. Data can be used repeatedly and by several businesses without being used up. However, access can be restricted through contracts and technical controls. Nevertheless, holding a large dataset alone does not establish market power.</p><br />
<p>'''Google Search''' illustrates this mechanism. Google controls over 91% of global search engine traffic [[https://www.statista.com/statistics/1381664/worldwide-all-devices-market-share-of-search-engines/ 3]] and uses information about users’ searches and the results they click to improve the relevance of its rankings. A larger volume of searches gives it more opportunities to learn, including about unusual queries that smaller search engines encounter less often. Better results can attract further use, producing additional information and reinforcing the advantage. A new search engine may therefore struggle to attract users while lacking the information needed to improve its service. Data access can constitute a significant barrier to entry when this type of analytics is necessary to participate in a market, particularly when alternatives are limited.&nbsp;</p><br />
<p>A platform’s control over data access can shape who is able to compete with it. By determining whether, and on what terms, rivals can access that information, a platform can influence the competitive opportunities available to others. This suggests that regulation should examine access to strategically important data alongside prices and market shares. Article 6(11) of the EU Digital Markets Act [[https://eur-lex.europa.eu/eli/reg/2022/1925/oj/eng#:~:text=giving%20their%20consent.-,11.%C2%A0,-The%20gatekeeper%20shall 4]] reflects this approach: certain large search providers must, on request, share specified search data with rival search providers on fair and non-discriminatory terms, with relevant personal data anonymised. The aim is to help rivals compete while protecting users. A data advantage does not, by itself, establish unlawful conduct.</p><br />
<p>Would access to equivalent data enable a rival to compete effectively? The concept cannot answer this on its own. Additional data may eventually add little value, become outdated, or have substitutes. Firms also need the skills and computing resources to use it. Google’s default positions in browsers and devices can further restrict rivals’ access to users even if data become available. The unresolved issue is how much competitive advantage comes from data itself and how much comes from these other resources and arrangements.&nbsp;</p><br />
<br />
= Two Sided Markets (Ceren) =<br />
<p>In two-sided markets, two sides of a market interact through an intermediary. These markets typically have some externality,<code class="mwt-code" >Carl Shapiro and Hal R Varian, ''Information Rules: A Strategic Guide to the Network Economy'' (Harvard Business School Press 2010), 183.</code><sup></sup> where the decisions of the sides affect the other. The intermediary also has multitudes of effects on both sides, mainly identified in the related literature through its pricing.</p><br />
<p>An example of a two sided market is payment systems, whereby the credit card providing bank is the intermediary between the customers and merchants. In this example, banks provide credit cards to customers to be utilized in their payments, and merchants accept payment via multiple credit card systems to accommodate payments from customers holding credit cards from such providers[https://doi.org/10.1257/jep.23.3.125 .]</p><br />
<p>The main power of the intermediary materializes in their pricing toward the merchant (and the merchant’s bank in interchange fees in case of payment being transferred through different banks). Customers will be expected to be more loyal, holding a few credit cards, whereas merchants accept payment from many banks to accommodate all customers’ payment methods. Banks will provide more subsidies to customers to attract them and compete aggressively on the customer side, making their platform more desirable to work with by merchants, who will in turn be more accepting of the platform’s fees to gain the business of the larger volume of customers. However, dynamic pricing (increasing fees after gaining entry and loyalty) may be a way for these platforms to abuse their power.</p><br />
<p>The concept may be derailed from these logical / analytical systems of operation or expected outcomes when public policy interferes with the market. For example, net neutrality rules regulate what internet service providers (the intermediary) can charge content providers (one side) who aim to reach the consumers (the other side). In this case the above considerations and the concept are halted.</p><br />
<br />
= Switching costs and lock-in (Kate) =<br />
[[File:Untitled Diagram.drawio (1).png|300px|thumb|Goods Matrix]]<br />
<br />
= Excludability and rivalrousness (Paul)&nbsp; =<br />
=== Excludability and Rivalrousness ===<br />
<p>The terms excludability and rivalrousness both refer to consumption characteristics that can be assigned to- or identified in goods.&nbsp;</p><br />
<p>'''Excludability''': Goods to which economic actors can technically or legally restrict access are considered to have ‘high excludability’. Conversely, goods to which access cannot be restricted are of ‘low excludability’, or, in absolute terms, ‘non-excludable’.</p><br />
<p>'''Rivalrousness''': Rivalrousness on the other hand refers to the finitude of the good in question. The greater the depletion of the stock, quantity, or amount is on account of one party’s consumption, the more rivalrous a good is.&nbsp;</p><br />
<p>Tabulating the characteristics against one another allows for inference and definition of the type of good an object, service, or resource may constitute (see fig. 1). Excludability and Rivalrousness of goods can therethrough serve as a predictor for certain types of market failures: Goods which are non-excludable or of low excludability, but nonetheless costly to provide, are vulnerable to so-called free rider problem. Goods which are non-excludable, but highly rivalrous (common goods), may lead to the tragedy of the commons, that is over-exploitation.<br></p><br />
<br />
=== AI Training and the (non-)excludability of information. ===<br />
<p>The unusual nature of excludability and rivalrousness of data further compromises the applicability of the goods classification built thereon. In traditional economics, a non-excludable and non-rivalrous good would be seen as a public good. This does apply insofar as data is vulnerable to corporate exploitation without commensurate indemnification. Data usage may however actually be anti-rival in the sense that increasing aggregate usage increases the value of the data (better labeling, easier access, previously undrawn conclusions, etc.), rather than diminish the ‘stock’ of data. Conversely, data may be rivalrous not in its absolute depletion by consumption, but rather the benefit or competitive advantage usage of that data may confer: If all AI firms are able to train on the exact same data (all available data), the utility of that data may still increase, but the competitive advantage of possessing that data is exhausted.</p><br />
<br />
=== Free-Rider Problems & Public Data ===<br />
<p>As any party can benefit from publicly available data at no cost or low cost, the incentive for private market actors to fund its creation is comparatively weak. Consequently, public bodies (and less frequently open-source foundations and non-profits) often assume the responsibility for the provision of this type of data. A classical example is weather data and its creation by national weather agencies.</p><br />
<br />
= Interoperability (Sisi) =<br />
<br />
#What is interoperability?[[https://www.ibm.com/think/topics/interoperability 1]]<p>Interoperability is a “standards-based” approach that enables different IT systems to communicate with minimal end-user interaction to exchange data and “share functionality”. Each system also allows the other system to “read, update, modify, and analyze” data with minimal human interaction. [[https://www.oracle.com/nl/interoperability/ 2]]</p><br />
<p>Interoperability works by having different systems share data by employing the same standards for data formats (e.g., Extensible Markup Language or JavaScript Object Notation), exchange, and vocabulary to title data elements. These standards are agreed upon “in advance” by organizations, industry types, and user groups. Then, software developers build the system based on the model agreed upon.</p><br />
#Concrete example from a digital technology or platform<p>Interoperable systems are vital in healthcare, commerce, and public safety. A notable example includes the integration of Electronic Health Records (HER). This system allows different healthcare providers to securely access and share personal patient information regardless of the specific EHR system used.[[https://data.europa.eu/en/news-events/news/interoperability-solutions-bridging-systems-connected-future 3]] An example of such a system is the GNU Health Hospital Information System, which is a model employed by small private offices and large national public health systems.[[https://interoperable-europe.ec.europa.eu/collection/gnu-health/solution/gnu-health-hospital-information-system 4]]</p><br />
<p>For example, a health care professional may access lab results and patient history data from various platforms to enable them to make a diagnosis.</p><br />
#One governance implication: what does this concept explain about how platforms exercise power?<p>Interoperability is a powerful tool because it helps provide a “seamless user experience” and optimizes data sharing between separate systems. It helps companies and organizations access data from multiple sources and improve efficiency, such as accelerating workflows and reducing the possibility of errors by pooling data from its sources.</p><br />
<p>Interoperability standards are mandated by law on the technical side to ensure “critical systems” are compatible, especially in public safety and health. [[https://www.ibm.com/think/topics/interoperability 5]]</p><br />
<p>In Europe, interoperability is governed by the European Health Data Space regulation (EHDS); the “first common EU data space dedicated to a specific sector as part of the European strategy for data.”</p><br />
<p>This Regulation aims to benefit EU citizens such as patients, researchers, healthcare professionals, and industry players by establishing a common framework for the exchange of electronic health data within the EU. In addition, it enables certain data to be “reused” for public purpose and innovative scientific research. [[https://health.ec.europa.eu/ehealth-digital-health-and-care/european-health-data-space-regulation-ehds_en 6]]</p><br />
#Where does the concept break down or fail to explain something<p>While the EDHS harmonizes a legal and technical framework for sharing EU data, its shortcoming is its gradual implementation. The EDHS entered into force in 2025; however, most of its obligations will not apply until 2029. This leaves four years for health care companies to use interoperability in a deregulated manner. [[https://health.ec.europa.eu/ehealth-digital-health-and-care/european-health-data-space-regulation-ehds_en 7]]</p><br />
<p>Furthermore, there are actual barriers to achieving full interoperability in healthcare, including data silos (which isolate data collections and hinder data exchange), lack of standardization (where one system records blood pressure as free text, another system stores it as a structured numeric value), and deficient infrastructure, which requires significant technological upgrading.</p><br />
<p>The burden remains on health companies to decide which standards to adopt and how much to invest in stable technological infrastructure to strengthen their data governance and interoperability. [[https://www.tigahealth.com/how-to-overcome-healthcare-interoperability-challenges/ 8]]</p><br />
<br />
= "Economies of Scale (Jihae)" =<br />
= [[Network Effects (Indirect) - Sebastián]] =</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Governance_by_markets&diff=124109Governance by markets2026-10-04T17:52:41Z<p>Isiklar Ceren: /* Two Sided Markets (Ceren) */</p>
<hr />
<div>= Glossary =<br />
= Data as an input to market power (Sergey) =<br />
<p>In the present digital economy, data has emerged as a valuable economic commodity that entities leverage to gain a competitive edge over their rivals [[https://repository.nls.ac.in/cgi/viewcontent.cgi?article=1478&context=nlsblr 1]]. '''Data''' is an input into production, so businesses that control data can have market power and impede the entry of potential competitors. '''Market power''' refers to a firm's ability to influence the price, output, or other market conditions in its favour, without being constrained by competitive forces [[https://www.tutor2u.net/economics/reference/what-is-meant-by-market-power 2]].</p><br />
<p>'''Data as an input to market power''' means that access to information can help a business limit the competitive pressure it faces. Information about searches, clicks or purchases can improve services and advertising. If competitors cannot obtain comparable information at a reasonable cost, they may struggle to offer an attractive alternative. This can allow a platform to raise prices or worsen quality or privacy protections without losing enough business to make doing so unprofitable. This matters even when a service is free, because competition also concerns advertising charges, personal information and the choices available. Data can be used repeatedly and by several businesses without being used up. However, access can be restricted through contracts and technical controls. Nevertheless, holding a large dataset alone does not establish market power.</p><br />
<p>'''Google Search''' illustrates this mechanism. Google controls over 91% of global search engine traffic [[https://www.statista.com/statistics/1381664/worldwide-all-devices-market-share-of-search-engines/ 3]] and uses information about users’ searches and the results they click to improve the relevance of its rankings. A larger volume of searches gives it more opportunities to learn, including about unusual queries that smaller search engines encounter less often. Better results can attract further use, producing additional information and reinforcing the advantage. A new search engine may therefore struggle to attract users while lacking the information needed to improve its service. Data access can constitute a significant barrier to entry when this type of analytics is necessary to participate in a market, particularly when alternatives are limited.&nbsp;</p><br />
<p>A platform’s control over data access can shape who is able to compete with it. By determining whether, and on what terms, rivals can access that information, a platform can influence the competitive opportunities available to others. This suggests that regulation should examine access to strategically important data alongside prices and market shares. Article 6(11) of the EU Digital Markets Act [[https://eur-lex.europa.eu/eli/reg/2022/1925/oj/eng#:~:text=giving%20their%20consent.-,11.%C2%A0,-The%20gatekeeper%20shall 4]] reflects this approach: certain large search providers must, on request, share specified search data with rival search providers on fair and non-discriminatory terms, with relevant personal data anonymised. The aim is to help rivals compete while protecting users. A data advantage does not, by itself, establish unlawful conduct.</p><br />
<p>Would access to equivalent data enable a rival to compete effectively? The concept cannot answer this on its own. Additional data may eventually add little value, become outdated, or have substitutes. Firms also need the skills and computing resources to use it. Google’s default positions in browsers and devices can further restrict rivals’ access to users even if data become available. The unresolved issue is how much competitive advantage comes from data itself and how much comes from these other resources and arrangements.&nbsp;</p><br />
<br />
= Two Sided Markets (Ceren) =<br />
<p>In two-sided markets, two sides of a market interact through an intermediary. These markets typically have some externality, where the decisions of the sides affect the other. The intermediary also has multitudes of effects on both sides, mainly identified in the related literature through its pricing.</p><p>An example of a two sided market is payment systems, whereby the credit card providing bank is the intermediary between the customers and merchants. In this example, banks provide credit cards to customers to be utilized in their payments, and merchants accept payment via multiple credit card systems to accommodate payments from customers holding credit cards from such providers.</p><p>The main power of the intermediary materializes in their pricing toward the merchant (and the merchant’s bank in interchange fees in case of payment being transferred through different banks). Customers will be expected to be more loyal, holding a few credit cards, whereas merchants accept payment from many banks to accommodate all customers’ payment methods. Banks will provide more subsidies to customers to attract them and compete aggressively on the customer side, making their platform more desirable to work with by merchants, who will in turn be more accepting of the platform’s fees to gain the business of the larger volume of customers. However, dynamic pricing (increasing fees after gaining entry and loyalty) may be a way for these platforms to abuse their power.</p><p>The concept may be derailed from these logical / analytical systems of operation or expected outcomes when public policy interferes with the market. For example, net neutrality rules regulate what internet service providers (the intermediary) can charge content providers (one side) who aim to reach the consumers (the other side). In this case the above considerations and the concept are halted.</p><br />
<br />
= Switching costs and lock-in (Kate) =<br />
[[File:Untitled Diagram.drawio (1).png|300px|thumb|Goods Matrix]]<br />
<br />
= Excludability and rivalrousness (Paul)&nbsp; =<br />
=== Excludability and Rivalrousness ===<br />
<p>The terms excludability and rivalrousness both refer to consumption characteristics that can be assigned to- or identified in goods.&nbsp;</p><br />
<p>'''Excludability''': Goods to which economic actors can technically or legally restrict access are considered to have ‘high excludability’. Conversely, goods to which access cannot be restricted are of ‘low excludability’, or, in absolute terms, ‘non-excludable’.</p><br />
<p>'''Rivalrousness''': Rivalrousness on the other hand refers to the finitude of the good in question. The greater the depletion of the stock, quantity, or amount is on account of one party’s consumption, the more rivalrous a good is.&nbsp;</p><br />
<p>Tabulating the characteristics against one another allows for inference and definition of the type of good an object, service, or resource may constitute (see fig. 1). Excludability and Rivalrousness of goods can therethrough serve as a predictor for certain types of market failures: Goods which are non-excludable or of low excludability, but nonetheless costly to provide, are vulnerable to so-called free rider problem. Goods which are non-excludable, but highly rivalrous (common goods), may lead to the tragedy of the commons, that is over-exploitation.<br></p><br />
<br />
=== AI Training and the (non-)excludability of information. ===<br />
<p>The unusual nature of excludability and rivalrousness of data further compromises the applicability of the goods classification built thereon. In traditional economics, a non-excludable and non-rivalrous good would be seen as a public good. This does apply insofar as data is vulnerable to corporate exploitation without commensurate indemnification. Data usage may however actually be anti-rival in the sense that increasing aggregate usage increases the value of the data (better labeling, easier access, previously undrawn conclusions, etc.), rather than diminish the ‘stock’ of data. Conversely, data may be rivalrous not in its absolute depletion by consumption, but rather the benefit or competitive advantage usage of that data may confer: If all AI firms are able to train on the exact same data (all available data), the utility of that data may still increase, but the competitive advantage of possessing that data is exhausted.</p><br />
<br />
=== Free-Rider Problems & Public Data ===<br />
<p>As any party can benefit from publicly available data at no cost or low cost, the incentive for private market actors to fund its creation is comparatively weak. Consequently, public bodies (and less frequently open-source foundations and non-profits) often assume the responsibility for the provision of this type of data. A classical example is weather data and its creation by national weather agencies.</p><br />
<br />
= Interoperability (Sisi) =<br />
<br />
#What is interoperability?[[https://www.ibm.com/think/topics/interoperability 1]]<p>Interoperability is a “standards-based” approach that enables different IT systems to communicate with minimal end-user interaction to exchange data and “share functionality”. Each system also allows the other system to “read, update, modify, and analyze” data with minimal human interaction. [[https://www.oracle.com/nl/interoperability/ 2]]</p><br />
<p>Interoperability works by having different systems share data by employing the same standards for data formats (e.g., Extensible Markup Language or JavaScript Object Notation), exchange, and vocabulary to title data elements. These standards are agreed upon “in advance” by organizations, industry types, and user groups. Then, software developers build the system based on the model agreed upon.</p><br />
#Concrete example from a digital technology or platform<p>Interoperable systems are vital in healthcare, commerce, and public safety. A notable example includes the integration of Electronic Health Records (HER). This system allows different healthcare providers to securely access and share personal patient information regardless of the specific EHR system used.[[https://data.europa.eu/en/news-events/news/interoperability-solutions-bridging-systems-connected-future 3]] An example of such a system is the GNU Health Hospital Information System, which is a model employed by small private offices and large national public health systems.[[https://interoperable-europe.ec.europa.eu/collection/gnu-health/solution/gnu-health-hospital-information-system 4]]</p><br />
<p>For example, a health care professional may access lab results and patient history data from various platforms to enable them to make a diagnosis.</p><br />
#One governance implication: what does this concept explain about how platforms exercise power?<p>Interoperability is a powerful tool because it helps provide a “seamless user experience” and optimizes data sharing between separate systems. It helps companies and organizations access data from multiple sources and improve efficiency, such as accelerating workflows and reducing the possibility of errors by pooling data from its sources.</p><br />
<p>Interoperability standards are mandated by law on the technical side to ensure “critical systems” are compatible, especially in public safety and health. [[https://www.ibm.com/think/topics/interoperability 5]]</p><br />
<p>In Europe, interoperability is governed by the European Health Data Space regulation (EHDS); the “first common EU data space dedicated to a specific sector as part of the European strategy for data.”</p><br />
<p>This Regulation aims to benefit EU citizens such as patients, researchers, healthcare professionals, and industry players by establishing a common framework for the exchange of electronic health data within the EU. In addition, it enables certain data to be “reused” for public purpose and innovative scientific research. [[https://health.ec.europa.eu/ehealth-digital-health-and-care/european-health-data-space-regulation-ehds_en 6]]</p><br />
#Where does the concept break down or fail to explain something<p>While the EDHS harmonizes a legal and technical framework for sharing EU data, its shortcoming is its gradual implementation. The EDHS entered into force in 2025; however, most of its obligations will not apply until 2029. This leaves four years for health care companies to use interoperability in a deregulated manner. [[https://health.ec.europa.eu/ehealth-digital-health-and-care/european-health-data-space-regulation-ehds_en 7]]</p><br />
<p>Furthermore, there are actual barriers to achieving full interoperability in healthcare, including data silos (which isolate data collections and hinder data exchange), lack of standardization (where one system records blood pressure as free text, another system stores it as a structured numeric value), and deficient infrastructure, which requires significant technological upgrading.</p><br />
<p>The burden remains on health companies to decide which standards to adopt and how much to invest in stable technological infrastructure to strengthen their data governance and interoperability. [[https://www.tigahealth.com/how-to-overcome-healthcare-interoperability-challenges/ 8]]</p><br />
<br />
= "Economies of Scale (Jihae)" =<br />
= [[Network Effects (Indirect) - Sebastián]] =</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Governance_by_markets&diff=124089Governance by markets2026-10-02T11:40:09Z<p>Isiklar Ceren: /* Glossary */</p>
<hr />
<div>= Glossary =<br />
= Two Sided Markets (Ceren) =<br />
[[File:Untitled Diagram.drawio (1).png|300px|thumb|Goods Matrix]]<br />
<br />
= Excludability and rivalrousness (Paul) =<br />
<p>Excludability and Rivalrousness</p><br />
<br />
<br><p>The terms excludability and rivalrousness both refer to consumption characteristics that can be assigned to- or identified in goods.&nbsp;</p><br />
<br />
<br><p>Excludability: Goods to which economic actors can technically or legally restrict access are considered to have ‘high excludability’. Conversely, goods to which access cannot be restricted are of ‘low excludability’, or, in absolute terms, ‘non-excludable’.</p><br />
<p>Rivalrousness: Rivalrousness on the other hand refers to the finitude of the good in question. The greater the depletion of the stock, quantity, or amount is on account of one party’s consumption, the more rivalrous a good is.&nbsp;</p><br />
<br />
<br><p>Tabulating the characteristics against one another allows for inference and definition of the type of good an object, service, or resource may constitute (see fig. 1). Excludability and Rivalrousness of goods can therethrough serve as a predictor for certain types of market failures: Goods which are non-excludable or of low excludability, but nonetheless costly to provide, are vulnerable to so-called free rider problem. Goods which are non-excludable, but highly rivalrous (common goods), may lead to the tragedy of the commons, that is over-exploitation.<br></p><br />
<p>AI Training and the (non-)excludability of information.</p><br />
<p>The unusual nature of excludability and rivalrousness of data further compromises the applicability of the goods classification built thereon. In traditional economics, a non-excludable and non-rivalrous good would be seen as a public good. This does apply insofar as data is vulnerable to corporate exploitation without commensurate indemnification. Data usage may however actually be anti-rival in the sense that increasing aggregate usage increases the value of the data (better labeling, easier access, previously undrawn conclusions, etc.), rather than diminish the ‘stock’ of data.&nbsp;</p></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Governance_by_markets&diff=124088Governance by markets2026-10-02T11:39:25Z<p>Isiklar Ceren: /* Glossary */</p>
<hr />
<div>= Glossary =<br />
[[File:Untitled Diagram.drawio (1).png|300px|thumb|Goods Matrix]]<br />
= Excludability and rivalrousness (Paul) =<br />
<p>Excludability and Rivalrousness</p><br />
<br />
<br><p>The terms excludability and rivalrousness both refer to consumption characteristics that can be assigned to- or identified in goods.&nbsp;</p><br />
<br />
<br><p>Excludability: Goods to which economic actors can technically or legally restrict access are considered to have ‘high excludability’. Conversely, goods to which access cannot be restricted are of ‘low excludability’, or, in absolute terms, ‘non-excludable’.</p><br />
<p>Rivalrousness: Rivalrousness on the other hand refers to the finitude of the good in question. The greater the depletion of the stock, quantity, or amount is on account of one party’s consumption, the more rivalrous a good is.&nbsp;</p><br />
<br />
<br><p>Tabulating the characteristics against one another allows for inference and definition of the type of good an object, service, or resource may constitute (see fig. 1). Excludability and Rivalrousness of goods can therethrough serve as a predictor for certain types of market failures: Goods which are non-excludable or of low excludability, but nonetheless costly to provide, are vulnerable to so-called free rider problem. Goods which are non-excludable, but highly rivalrous (common goods), may lead to the tragedy of the commons, that is over-exploitation.<br></p><br />
<p>AI Training and the (non-)excludability of information.</p><br />
<p>The unusual nature of excludability and rivalrousness of data further compromises the applicability of the goods classification built thereon. In traditional economics, a non-excludable and non-rivalrous good would be seen as a public good. This does apply insofar as data is vulnerable to corporate exploitation without commensurate indemnification. Data usage may however actually be anti-rival in the sense that increasing aggregate usage increases the value of the data (better labeling, easier access, previously undrawn conclusions, etc.), rather than diminish the ‘stock’ of data.&nbsp;</p></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Cloud_service_(Ceren)&diff=123987Cloud service (Ceren)2026-09-23T10:00:52Z<p>Isiklar Ceren: </p>
<hr />
<div><p>A cloud service that is being utilized by EU customers, for example Microsoft, would be governed by the below institutions, this list not being exhaustive. The governance mechanisms touched upon in this entry were fueled by a concern over sovereignty/jurisdiction. The data stored and transported through cloud services could be monitored by non-EU actors (namely US hyper scalers and through these the US government (e.g. Snowden revelations)), thereby potentially giving rise to the compromise of EU data. The race to govern through the below mentioned legal instruments and institutions aim to address sovereignty concerns.</p><br />
'''1. The European Union Agency for Cybersecurity ''''''ENISA '''(public)<br />
*'''Source of authority and Governing instrument:''' Regulation (EU) 2019/881 on the European Union Agency for Cybersecurity and on information and communications technology cybersecurity certification (Cybersecurity Act) (CSA) [https://www.enisa.europa.eu/about-enisa/what-we-do empowers ENISA ]<br />
*'''Interest/value:''' in the [https://www.enisa.europa.eu/sites/default/files/2026-05/ENISA%20NIS360%202026.pdf NIS360 report ] published by ENISA, it is stated that ENISA is “the Union’s agency dedicated to achieving a high common level of cybersecurity across Europe” and that ENISA “contributes to EU cyber policy, enhances the trustworthiness of ICT products, services and processes with cybersecurity certification schemes, cooperates with Member States and EU bodies, and helps Europe prepare for the cyber challenges”.<br />
*'''Weakness:''' ENISA's capacity to resist geopolitical and commercial pressure is being questioned, as US hyperscalers continue to dominate global cloud service markets<br />
'''2. National Cybersecurity Certification Authority of the Netherlands'''''' ''''''(Dutch NCCA) '''(public)<br />
*'''Source of authority and Governing instrument:''' EU Cybersecurity Act (Article 58), &nbsp;and the Dutch Cybersecurity Regulation Implementation Act which implemented the Cybersecurity Act nationally. This entity is the national cybersecurity certification authority int he Netherlands.<br />
*'''Interest/value:''' as described on their [https://www.dutchncca.nl/about-the-ncca website], the NCAA has the following mandate:&nbsp;&nbsp;&nbsp;&nbsp;<br />
**“Oversee the issuing of EU cybersecurity certificates at the CSA’s assurance level High;<br />
**Authorise Conformity Assessment Bodies (CABs)&nbsp;for the CSA certification schemes;<br />
**Supervise certificates issued throughout the lifecycle of certified ICT products and services;<br />
**Contribute on European&nbsp;level to the&nbsp;development&nbsp;and maintenance of CSA certification schemes.<br />
**Market trust, consumer protection, and national security through verified cloud security standards”&nbsp;<br />
*'''Weakness:''' Heavily dependent on the EU-level EUCS framework, where if that scheme is weak or delayed, the NCCA's certification work lacks a solid foundation.<br />
'''3. European Data Protection Board (EDPB) '''(public, supranational)<br />
*'''Source of authority:''' GDPR (Regulation 2016/679)<br />
*'''Governing instrument:''' GDPR; EDPB Guidelines (e.g. Guidelines 01/2020 on processing personal data in cloud services)<br />
*'''Interest/value:''' Privacy and data protection; ensuring cloud providers processing EU personal data comply with fundamental rights obligations<br />
*'''Weakness:''' Enforcement of the GDPR is left to national DPAs, which vary in resources and willingness to act (Ireland's DPA has been widely criticised for slow enforcement)<br />
'''4. Gaia X '''(non-state, international)<br />
*'''Source of authority:''' Voluntary membership organisation<br />
*'''Governing instrument:''' Gaia-X Trust Framework defines the minimum baseline to be part of the&nbsp;'''Gaia-X Ecosystem'''. This framework “provides a common governance and the basic level of interoperability across individual ecosystems”<br />
*'''Interest/value:''' Gaia X [https://gaia-x.eu/about/ aims] to achieve digital sovereignty through innovation, and its [https://docs.gaia-x.eu/policy-rules-committee/compliance-document/3.1.0/Executive_Summary/ values] are “openness, transparency, data protection, security, and portability”&nbsp;<br />
*'''Weakness:''' Gaia-X was trying to build sovereign infrastructure in the EU market where non-European hyperscalers (Microsoft, Google, Amazon) already dominate (Plixavra Vogiatzoglou and Joris van Hoboken, 'The EU's Digital Sovereignty and Quantum Technologies: To What End?')</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Cloud_service_(Ceren)&diff=123986Cloud service (Ceren)2026-09-23T09:59:16Z<p>Isiklar Ceren: </p>
<hr />
<div><p>A cloud service that is being utilized by EU customers, for example Microsoft, would be governed by the below institutions, this list not being exhaustive. The governance mechanisms touched upon in this entry were fueled by a concern over sovereignty/jurisdiction. The data stored and transported through cloud services could be monitored by non-EU actors (namely US hyper scalers and through these the US government (e.g. Snowden revelations)), thereby potentially giving rise to the compromise of EU data. The race to govern through the below mentioned legal instruments and institutions aim to address sovereignty concerns.</p><br />
'''1. The European Union Agency for Cybersecurity ''''''ENISA '''(public)<br />
*'''Source of authority and Governing instrument:''' Regulation (EU) 2019/881 on the European Union Agency for Cybersecurity and on information and communications technology cybersecurity certification (Cybersecurity Act) (CSA) [https://www.enisa.europa.eu/about-enisa/what-we-do empowers ENISA ]<br />
*'''Interest/value:''' in the [https://www.enisa.europa.eu/sites/default/files/2026-05/ENISA%20NIS360%202026.pdf NIS360 report ] published by ENISA, it is stated that ENISA is “the Union’s agency dedicated to achieving a high common level of cybersecurity across Europe” and that ENISA “contributes to EU cyber policy, enhances the trustworthiness of ICT products, services and processes with cybersecurity certification schemes, cooperates with Member States and EU bodies, and helps Europe prepare for the cyber challenges”.<br />
*'''Weakness:''' ENISA's capacity to resist geopolitical and commercial pressure is being questioned, as US hyperscalers continue to dominate global cloud service markets<br />
'''2. National Cybersecurity Certification Authority of the Netherlands'''''' ''''''(Dutch NCCA) '''(public)<br />
*'''Source of authority and Governing instrument:''' EU Cybersecurity Act (Article 58), &nbsp;and the Dutch Cybersecurity Regulation Implementation Act which implemented the Cybersecurity Act nationally. This entity is the national cybersecurity certification authority int he Netherlands.<br />
*'''Interest/value:''' as described on their [https://www.dutchncca.nl/about-the-ncca website], the NCAA has the following mandate:&nbsp;&nbsp;&nbsp;&nbsp;<br />
**“Oversee the issuing of EU cybersecurity certificates at the CSA’s assurance level High;<br />
**Authorise Conformity Assessment Bodies (CABs)&nbsp;for the CSA certification schemes;<br />
**Supervise certificates issued throughout the lifecycle of certified ICT products and services;<br />
**Contribute on European&nbsp;level to the&nbsp;development&nbsp;and maintenance of CSA certification schemes.<br />
**Market trust, consumer protection, and national security through verified cloud security standards”&nbsp;<br />
*'''Weakness:''' Heavily dependent on the EU-level EUCS framework, where if that scheme is weak or delayed, the NCCA's certification work lacks a solid foundation.<br />
'''3. European Data Protection Board (EDPB) (EU — public, supranational)'''<br />
*'''Source of authority:''' GDPR (Regulation 2016/679)<br />
*'''Governing instrument:''' GDPR; EDPB Guidelines (e.g. Guidelines 01/2020 on processing personal data in cloud services)<br />
*'''Interest/value:''' Privacy and data protection; ensuring cloud providers processing EU personal data comply with fundamental rights obligations<br />
*'''Weakness:''' Enforcement of the GDPR is left to national DPAs, which vary in resources and willingness to act (Ireland's DPA has been widely criticised for slow enforcement)<br />
'''4. Gaia X '''(non-state, international)<br />
*'''Source of authority:''' Voluntary membership organisation<br />
*'''Governing instrument:''' Gaia-X Trust Framework defines the minimum baseline to be part of the&nbsp;'''Gaia-X Ecosystem'''. This framework “provides a common governance and the basic level of interoperability across individual ecosystems”<br />
*'''Interest/value:''' Gaia X [https://gaia-x.eu/about/ aims] to achieve digital sovereignty through innovation, and its [https://docs.gaia-x.eu/policy-rules-committee/compliance-document/3.1.0/Executive_Summary/ values] are “openness, transparency, data protection, security, and portability”&nbsp;<br />
*'''Weakness:''' Gaia-X was trying to build sovereign infrastructure in the EU market where non-European hyperscalers (Microsoft, Google, Amazon) already dominate (Plixavra Vogiatzoglou and Joris van Hoboken, 'The EU's Digital Sovereignty and Quantum Technologies: To What End?')</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Cloud_service_(Ceren)&diff=123985Cloud service (Ceren)2026-09-23T09:58:54Z<p>Isiklar Ceren: </p>
<hr />
<div><p>A cloud service that is being utilized by EU customers, for example Microsoft, would be governed by the below institutions, this list not being exhaustive. The governance mechanisms touched upon in this entry were fueled by a concern over sovereignty/jurisdiction. The data stored and transported through cloud services could be monitored by non-EU actors (namely US hyper scalers and through these the US government (e.g. Snowden revelations)), thereby potentially giving rise to the compromise of EU data. The race to govern through the below mentioned legal instruments and institutions aim to address sovereignty concerns.</p><br />
1. The European Union Agency for Cybersecurity''' ''''''ENISA '''(public)<br />
*'''Source of authority and Governing instrument:''' Regulation (EU) 2019/881 on the European Union Agency for Cybersecurity and on information and communications technology cybersecurity certification (Cybersecurity Act) (CSA) [https://www.enisa.europa.eu/about-enisa/what-we-do empowers ENISA ]<br />
*'''Interest/value:''' in the [https://www.enisa.europa.eu/sites/default/files/2026-05/ENISA%20NIS360%202026.pdf NIS360 report ] published by ENISA, it is stated that ENISA is “the Union’s agency dedicated to achieving a high common level of cybersecurity across Europe” and that ENISA “contributes to EU cyber policy, enhances the trustworthiness of ICT products, services and processes with cybersecurity certification schemes, cooperates with Member States and EU bodies, and helps Europe prepare for the cyber challenges”.<br />
*'''Weakness:''' ENISA's capacity to resist geopolitical and commercial pressure is being questioned, as US hyperscalers continue to dominate global cloud service markets<br />
'''2. National Cybersecurity Certification Authority of the Netherlands'''''' ''''''(Dutch NCCA) '''(public)<br />
*'''Source of authority and Governing instrument:''' EU Cybersecurity Act (Article 58), &nbsp;and the Dutch Cybersecurity Regulation Implementation Act which implemented the Cybersecurity Act nationally. This entity is the national cybersecurity certification authority int he Netherlands.<br />
*'''Interest/value:''' as described on their [https://www.dutchncca.nl/about-the-ncca website], the NCAA has the following mandate:&nbsp;&nbsp;&nbsp;&nbsp;<br />
**“Oversee the issuing of EU cybersecurity certificates at the CSA’s assurance level High;<br />
**Authorise Conformity Assessment Bodies (CABs)&nbsp;for the CSA certification schemes;<br />
**Supervise certificates issued throughout the lifecycle of certified ICT products and services;<br />
**Contribute on European&nbsp;level to the&nbsp;development&nbsp;and maintenance of CSA certification schemes.<br />
**Market trust, consumer protection, and national security through verified cloud security standards”&nbsp;<br />
*'''Weakness:''' Heavily dependent on the EU-level EUCS framework, where if that scheme is weak or delayed, the NCCA's certification work lacks a solid foundation.<br />
'''3. European Data Protection Board (EDPB) (EU — public, supranational)'''<br />
*'''Source of authority:''' GDPR (Regulation 2016/679)<br />
*'''Governing instrument:''' GDPR; EDPB Guidelines (e.g. Guidelines 01/2020 on processing personal data in cloud services)<br />
*'''Interest/value:''' Privacy and data protection; ensuring cloud providers processing EU personal data comply with fundamental rights obligations<br />
*'''Weakness:''' Enforcement of the GDPR is left to national DPAs, which vary in resources and willingness to act (Ireland's DPA has been widely criticised for slow enforcement)<br />
'''4. Gaia X '''(non-state, international)<br />
*'''Source of authority:''' Voluntary membership organisation<br />
*'''Governing instrument:''' Gaia-X Trust Framework defines the minimum baseline to be part of the&nbsp;'''Gaia-X Ecosystem'''. This framework “provides a common governance and the basic level of interoperability across individual ecosystems”<br />
*'''Interest/value:''' Gaia X [https://gaia-x.eu/about/ aims] to achieve digital sovereignty through innovation, and its [https://docs.gaia-x.eu/policy-rules-committee/compliance-document/3.1.0/Executive_Summary/ values] are “openness, transparency, data protection, security, and portability”&nbsp;<br />
*'''Weakness:''' Gaia-X was trying to build sovereign infrastructure in the EU market where non-European hyperscalers (Microsoft, Google, Amazon) already dominate (Plixavra Vogiatzoglou and Joris van Hoboken, 'The EU's Digital Sovereignty and Quantum Technologies: To What End?')</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Talk:Submarine_Internet_Cables_-_By_Pablo_Latorre&diff=123880Talk:Submarine Internet Cables - By Pablo Latorre2026-09-22T20:33:33Z<p>Isiklar Ceren: </p>
<hr />
<div>this way very enlightening! With the task of suggesting an improvement, I might question whether UNCLOS may be construed as an institution (although I agree it is a governance tool).&nbsp;- Ceren</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Talk:Decentralized_digital_currency:_BITCOIN_(Sisi)&diff=123879Talk:Decentralized digital currency: BITCOIN (Sisi)2026-09-22T20:32:31Z<p>Isiklar Ceren: Created page with "Very interesting to see this evaluation of a notoriously non-governed instrument! A suggestion could be to mention talks of regulating cryptocurrency in some countries? - Ceren"</p>
<hr />
<div>Very interesting to see this evaluation of a notoriously non-governed instrument! A suggestion could be to mention talks of regulating cryptocurrency in some countries? - Ceren</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Talk:Submarine_Internet_Cables_-_By_Pablo_Latorre&diff=123875Talk:Submarine Internet Cables - By Pablo Latorre2026-09-22T20:29:07Z<p>Isiklar Ceren: Created page with "this way very enlightening! With the task of suggesting an improvement, I might question whether UNCLOS may be construed as an institution (although I agree it is a governance tool).&nbsp;"</p>
<hr />
<div>this way very enlightening! With the task of suggesting an improvement, I might question whether UNCLOS may be construed as an institution (although I agree it is a governance tool).&nbsp;</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Cloud_service_(Ceren)&diff=123874Cloud service (Ceren)2026-09-22T20:18:40Z<p>Isiklar Ceren: Created page with "<p>A cloud service that is being utilized by EU customers, for example Microsoft, would be governed by the below institutions, this list not being exhaustive.</p> #''' '''The European Union Agency for Cybersecurity''' ''''''ENISA '''(public) *'''Source of authority and Governing instrument:''' Regulation (EU) 2019/881 on the European Union Agency for Cybersecurity and on information and communications technology cybersecurity certification (Cybersecurity Act) (CSA) [htt..."</p>
<hr />
<div><p>A cloud service that is being utilized by EU customers, for example Microsoft, would be governed by the below institutions, this list not being exhaustive.</p><br />
#''' '''The European Union Agency for Cybersecurity''' ''''''ENISA '''(public)<br />
<br />
*'''Source of authority and Governing instrument:''' Regulation (EU) 2019/881 on the European Union Agency for Cybersecurity and on information and communications technology cybersecurity certification (Cybersecurity Act) (CSA) [https://www.enisa.europa.eu/about-enisa/what-we-do empowers ENISA ]<br />
*'''Interest/value:''' in the [https://www.enisa.europa.eu/sites/default/files/2026-05/ENISA%20NIS360%202026.pdf NIS360 report ] published by ENISA, it is stated that ENISA is “the Union’s agency dedicated to achieving a high common level of cybersecurity across Europe” and that ENISA “contributes to EU cyber policy, enhances the trustworthiness of ICT products, services and processes with cybersecurity certification schemes, cooperates with Member States and EU bodies, and helps Europe prepare for the cyber challenges”.<br />
*'''Weakness:''' ENISA's capacity to resist geopolitical and commercial pressure is being questioned, as US hyperscalers continue to dominate global cloud service markets<br />
<br />
#''' National Cybersecurity Certification Authority of the Netherlands'''''' ''''''(Dutch NCCA) '''(public)<br />
<br />
*'''Source of authority and Governing instrument:''' EU Cybersecurity Act (Article 58), &nbsp;and the Dutch Cybersecurity Regulation Implementation Act which implemented the Cybersecurity Act nationally. This entity is the national cybersecurity certification authority int he Netherlands.<br />
*'''Interest/value:''' as described on their [https://www.dutchncca.nl/about-the-ncca website], the NCAA has the following mandate:&nbsp;&nbsp;&nbsp;&nbsp;<br />
<br />
**“Oversee the issuing of EU cybersecurity certificates at the CSA’s assurance level High;<br />
**Authorise Conformity Assessment Bodies (CABs)&nbsp;for the CSA certification schemes;<br />
**Supervise certificates issued throughout the lifecycle of certified ICT products and services;<br />
**Contribute on European&nbsp;level to the&nbsp;development&nbsp;and maintenance of CSA certification schemes.<br />
**Market trust, consumer protection, and national security through verified cloud security standards”&nbsp;<br />
*'''Weakness:''' Heavily dependent on the EU-level EUCS framework, where if that scheme is weak or delayed, the NCCA's certification work lacks a solid foundation.<br />
<br />
#''' European Data Protection Board (EDPB) (EU — public, supranational)'''<br />
<br />
*'''Source of authority:''' GDPR (Regulation 2016/679)<br />
*'''Governing instrument:''' GDPR; EDPB Guidelines (e.g. Guidelines 01/2020 on processing personal data in cloud services)<br />
*'''Interest/value:''' Privacy and data protection; ensuring cloud providers processing EU personal data comply with fundamental rights obligations<br />
*'''Weakness:''' Enforcement of the GDPR is left to national DPAs, which vary in resources and willingness to act (Ireland's DPA has been widely criticised for slow enforcement)<br />
<br />
#''' Gaia X '''(non-state, international)<br />
<br />
*'''Source of authority:''' Voluntary membership organisation<br />
*'''Governing instrument:''' Gaia-X Trust Framework defines the minimum baseline to be part of the&nbsp;'''Gaia-X Ecosystem'''. This framework “provides a common governance and the basic level of interoperability across individual ecosystems”<br />
*'''Interest/value:''' Gaia X [https://gaia-x.eu/about/ aims] to achieve digital sovereignty through innovation, and its [https://docs.gaia-x.eu/policy-rules-committee/compliance-document/3.1.0/Executive_Summary/ values] are “openness, transparency, data protection, security, and portability”&nbsp;<br />
*'''Weakness:''' Gaia-X was trying to build sovereign infrastructure in the EU market where non-European hyperscalers (Microsoft, Google, Amazon) already dominate (Plixavra Vogiatzoglou and Joris van Hoboken, 'The EU's Digital Sovereignty and Quantum Technologies: To What End?')</div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Governance_by_institutions&diff=123836Governance by institutions2026-09-20T09:23:32Z<p>Isiklar Ceren: </p>
<hr />
<div><br />
<br />
<br />
*<span style="font-weight: normal;">[[social-media platform]] (mariona)</span><br />
*<br />
= <span style="font-weight: normal;">[[cloud service (Ceren)]]</span> =<br />
*<span style="font-weight: normal;"> app store</span><br />
*<span style="font-weight: normal;">digital identity system</span><br />
*<span style="font-weight: normal;">online-payment system</span><br />
*<span style="font-weight: normal;">AI model</span><br />
*<span style="font-weight: normal;">public algorithmic system.</span></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Governance_by_history&diff=123786Governance by history2026-09-09T10:30:30Z<p>Isiklar Ceren: /* Platform Dependence in Public Communication (News) Ceren & Rodrigue */</p>
<hr />
<div>= [[Workplace surveillance]] =<br />
== [[Information Control and Workplace Surveillance - by Jihae Park and Mariona Fortuny Jané]] ==<br />
==== <span style="font-size: 12pt;">The Current Governance Issue</span> ====<br />
<span style="font-size: 10pt;">There are numerous current governance problems arising from technological innovations, yet here we will specifically focus on the information control and workplace surveillance. Whether intended or unintended, there were certain historical incidents which resulted in social and political consequences. As noticed from the Control Revolution, the dramatic evolution in mass media and telecommunications technologies has led to the reinforcement of the economic and political control during the Industrial Revolution. ([https://archive.org/details/beniger-james-the-control-revolution Beniger, 1986]) By applying this logic to a modern example, this is clearly how many corporations are getting in control of their employees through surveillance technologies. Along with the emergence of remote and hybrid work after Covid-19, employers are now relying on “bossware” to analyze the emails, chats, and messages of their employees on platforms such as Teams or Slack. ([https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/view/19100/13263 Ollier-Malaterre et al., 2026, p.237]) Some companies have strict restrictions on transferring data both internally and externally in protection of confidential information and consistently monitor their workers to the certain extent which could slow down their efficiency. This is problematic as it’s not only violating the privacy of their employees but also depriving employees of rights they should be naturally be able to exercise.</span><br />
<br />
<span style="font-size: 12pt;"></span><br />
<br />
==== <span style="font-size: 12pt;">Historical Lineage</span> ====<br />
<span style="font-size: 12pt;"><span style="font-size: 10pt;">In relation to the current issue of the information control and workplace surveillance, Max Weber’s argument of bureaucracy and rationalization in the middle and late nineteenth century are good historical examples which are still frequently visible nowadays. Weber stated how the range of control could extend not only by expanding the capability to process information but also by limiting the amount of information to be processed. Here, the former is directly related to the control implemented by bureaucratization (in the mid 19th century) and computerization (in the late 20th century), whereas the latter addresses rationalization. An example from bureaucracy is the expansion of paperwork in response to the growth in information. We can still note these traces of bureaucracy from numerous procedures that we have to go through for a decision-making to take place in corporations. He brings up the example of standardized time zones for rationalization which is simply an example for an omission or a breakdown of information to facilitate its processing. ([https://archive.org/details/beniger-james-the-control-revolution Beniger, 1986, p.15-16]) This is also commonly seen from nowadays as some companies may use internal terminologies for the sake of both confidentiality and efficiency.</span></span><br />
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==== <span style="font-size: 12pt;">Mechanism of Path Dependence</span> ====<br />
<p>Following along the line with the historical lineage, there are certain mechanisms at work of path dependence for information control and workplace surveillance. Bureaucracy is closely related with organizational routines. Many companies have already settled down with a fixed workflow and decision-making process, which makes it more costly for one to change from its conventional way of working. This means switching costs from an old system to a new one is clearly high considering its time and capital, not necessarily will guarantee increasing returns. Hence, many firms end up maintaining its old strategy, reluctant to make any modifications or changes.<br></p><br />
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==== <span style="font-size: 12pt;">Politics and Distribution</span> ====<br />
<br />
As businesses grew too large for managers to oversee everything directly, companies replaced human judgment with formal rule-systems, as we see explained by Beniger's 'intellectual technology' ([https://archive.org/details/beniger-james-the-control-revolution/page/65/mode/2up Beniger, 1986, pp. 17, 21]). Algorithmic management continues this: a call once made by a supervisor's judgment is now a rule built into software that runs without one, extending a logic Beniger traces as far back as to Taylorism and the so called 'assembly line'. Winner ([https://www.jstor.org/stable/20024652 1980]) asks whether such systems must concentrate power this way or were driven there, when other designs were equally possible; nothing required shutting workers out of the decision, so leaving them out was a political choice, and not necessarily a technical necessity. Barbrook and Cameron ([https://doi.org/10.1080/09505439609526455 1996]) explain the reasoning why some can defend this 'domination': they show how 1990s tech culture sold new technologies as freedom even as it tightened control, so the rhetoric could become one of closer oversight as flexibility and autonomy. Together, authority accrues to employers, who in some systems can set and revise these oversight rules unilaterally and face less resistance because the arrangement is framed as freedom; workers bear the cost, losing the informal give-and-take they had with a human supervisor for oversight that is harder to see, question, or contest, while being told it grants them more freedom, not less.<br />
<br />
==== <span style="font-size: 12pt;">Contingency and Alternatives</span> ====<br />
<br />
A plausible alternative happened on U.S. post WWII: in some workplaces, labor and its pacing was demanded to be set through collective bargaining and enforced jointly, by both management and union stewards monitoring compliance on the line ([https://doi.org/10.1093/icc/dtaf038 Breznitz et al., 2025, p. 211]). So, in this context, workplace surveillance could have developed as a bargained, dual-administered practice rather than a management monopoly. The 1950 [https://en.wikipedia.org/wiki/Reuther%27s_Treaty_of_Detroit Reuther's Treaty of Detroit ] cut that possibility off: unions won guaranteed wages and benefits in exchange for surrendering any general claim over how work was supervised ([https://doi.org/10.1093/icc/dtaf038 Breznitz et al., 2025, pp. 210–211]). Workers depended on wages to survive, and employers controlled the wage relationship. That asymmetry meant employers, given their position of power, were able to arrange things so that, at the very least, workers would have far less capacity to sustain a fight over control itself. Thus, the "trade" wasn't a fair exchange between equals. This reflects which side could afford to hold out on which issue. Hypothetically speaking, had that joint administration model prevailed instead, this could have greatly impacted norms internationally and good practices with worker-union agreed surveillance would have become a widely accepted standard practice.<br />
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==== <span style="font-size: 12pt;">Governance Implication</span> ====<br />
<br />
An interesting proposition for present-day governance that wants to fill a gap in workplace surveillance is what [https://doi.org/10.1016/j.digbus.2025.100120 Kayas, Ong and Belal (2025)] are proposing: They argue that EU law, through the [https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng GDPR] and its required [https://en.wikipedia.org/wiki/Data_protection_impact_assessment data protection impact assessments (DPIAs)], already offers meaningful protection for workers in terms of lawful high-risk data collection and data processing. Nevertheless, these DPIAs are built around data and privacy, so they leave out several dimensions of monitoring itself: its purpose, how intrusive it is, how visible it is to the people being watched, and its effects on workers' autonomy, trust, and standing relative to management. These authors propose a "surveillance impact assessment" scoring a system against these characteristics directly, before any surveillance system is put in place. Although this mechanism "is constrained by its reliance on existing literature and the lack of empirical validation," it feels like a genuine alternative for two reasons: 1. it targets the actual mechanism at issue, and 2. at the same time it builds upon a mechanism of active participatory approach where employees have a direct say in how surveillance is designed ([https://doi.org/10.1016/j.digbus.2025.100120 Kayas et al., 2025, p. 11]), which, combined with the actual assessment, would put workers' own judgment at the centre of the one decision that affects them. It's important to note that this alternative is proposed as worth piloting, not as a proven fix, and it is fair to ask whether another mandatory assessment stacked on top of DPIAs would function as intended or simply read to workers as more compliance paperwork.<br />
<br />
==== References ====<br />
<br>Barbrook, R., & Cameron, A. (1996). The Californian Ideology. ''Science as Culture'', 6(1), 44–72. [https://doi.org/10.1080/09505439609526455 https://doi.org/10.1080/09505439609526455]<br>Beniger, J. R. (1986). ''The Control Revolution: Technological and Economic Origins of the Information Society''. Harvard University Press. [https://archive.org/details/beniger-james-the-control-revolution https://archive.org/details/beniger-james-the-control-revolution]&nbsp;<br>Breznitz, D., Levy, K., Lipartito, K., & Zehavi, A. (2025). An equity-focused research agenda for workplace surveillance. ''Industrial and Corporate Change'', 35(1), 206–221. [https://doi.org/10.1093/icc/dtaf038 https://doi.org/10.1093/icc/dtaf038]<br>Kayas, O. G., Ong, C. E., & Belal, H. M. (2025). From humans to algorithms: A sociotechnical framework of workplace surveillance. ''Digital Business'', 5, 100120. [https://doi.org/10.1016/j.digbus.2025.100120 https://doi.org/10.1016/j.digbus.2025.100120]<br>Ollier-Malaterre, A., Parent-Rocheleau, X., Benkrid, K., & Provost Savard, Y. (2026). Making Sense of Workplace Surveillance: How Workers and Union Representatives Experience, Imagine, and Resist Surveillance Exposure. ''Surveillance & Society'', 24(3), 236–254. [https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/view/19100/13263 https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/view/19100/13263]<br>Winner, L. (1980). Do Artifacts Have Politics? ''Daedalus'', 109(1), 121–136. [https://www.jstor.org/stable/20024652 https://www.jstor.org/stable/20024652]<br />
<br />
<br><br />
<br />
== [[Algorithmic management and workplace surveillance - by Sebastián Muller and Kate Davey'''&nbsp;''']] ==<br />
<br />
<br />
<br />
<br />
<br />
=== 1. The current issue. ===<br />
<br><p>Algorithmic management and workplace surveillance can be defined as the use of computer-programmed procedures to coordinate labor input in an organization ([https://joint-research-centre.ec.europa.eu/scientific-activities/employment/algorithmic-management-and-digital-monitoring-work_en 1]). Simply put, it is a way to control workers, and workers generally have no say in how the system that tracks them is created. As Winner says "different people are differently situated and possess unequal degrees of power as well as unequal levels of awareness" ([https://www.jstor.org/stable/20024652?seq=7 2]).</p><br />
<p>The population affected is workers; both “white collar” and “blue collar” workers are impacted. Whether it’s Amazon tracking warehouse workers’ “Time Off Task” with handheld scanners ([https://www.wired.com/story/amazon-worker-tracking-details-revealed 3]) or Meta employees having their every click tracked ([https://www.techpolicy.press/metas-worker-surveillance-tests-eu-rules-on-ai-and-labor/ 4]) to train AI, employers have the power to watch and control their employees in an unprecedented way.</p><br />
<p>It matters legally because workers have very few rights to fight back against these surveillance programs; even the The Electronic Communications Privacy Act of 1986 allows exceptions to surveillance of employees ([https://bja.ojp.gov/program/it/privacy-civil-liberties/authorities/statutes/1285 5]).<br></p><br />
<br />
=== <br>2. Historical lineage. ===<br />
<p><br>2.1 Panopticon: it is an architectural apparatus developed by Jeremy Bentham in 1791. The design of this building effectively generated the sense of constant monitoring, which in turn motivated the prisoners to behave as if they were being watched at all times. As human labor became commodified, capitalists began implementing measures to ensure the maximization of productivity, including the replication of this design ([https://doi.org/10.14452/MR-070-09-2019-02_2 6]). While unused today, the panopticon is widely considered as both a theoretical and practical inspiration of other forms of surveillance in the workplace.</p><br />
<p><br></p><br />
<p>2.2 Scientific management: this theory attempts to analyze and standardize workflows to improve labor productivity. Frederick Winslow Taylor, its main pioneer, used early forms of data analysis during the XX century to decrease walking distances, eliminating unnecessary movements and preventing deliberate slow-walking among workers. ([https://doi.org/10.14452/MR-070-09-2019-02_2 7]). There are many modern forms of data-driven decision-making processes in the workforce. For instance, Amazon warehouses track individual workers' scan rates in real time through handheld scanners, generating data feeds to track and evaluate performance ([https://www.theverge.com/2019/4/25/18516004/amazon-warehouse-fulfillment-centers-productivity-firing-terminations 8]).</p><br />
<p><br></p><br />
<p>2.3 PC in the workplace: John Blankenbaker designed the first commercially available personal computer in 1971 ([https://www.computerhistory.org/revolution/personal-computers/17/297 9]), however, it wasn’t until the mid-1980s that the use of personal computers in the workplace became an industry standard. This achievement gave rise to the digital monitoring of work, which in turn allowed employers to monitor employees in real-time, effectively replacing the human eye with a more efficient surveillance mechanism. This represents one of the key aspects of modern-day workplace monitoring.<br><br></p><br />
<p><br></p><br />
<br />
=== 3. Mechanism of path dependence. ===<br />
'''<br>'''When analyzing the historic lineage of work surveillance, it is possible to point out two main path dependencies mechanisms in place.<p>Firstly, it is clear that many of the technological developments that arose through these events have one major goal, which is to increase wealth within a hierarchical ecosystem. Employers resort to several mechanisms to maximize profits and cut inefficiencies at the expense of workers.&nbsp;</p><br />
<p>In addition, standardization can also be singled out as a key mechanism at play. Once one corporation implements any of these developments (such as the digital monitoring of the workplace), the market incentives would force the rest to do the same in order to be profitable and remain competitive.</p><br />
<br />
=== 4. Politics and distribution. ===<br />
<br>One simple answer to this question would be that capitalists implement and leverage these mechanisms to increase their wealth while the working class remains powerless and unable to withdraw itself from the system in force.&nbsp;<p>However, if we resort to Winner's framework, we see that the technical elements of these technologies are not intrinsically capitalist, since workplace surveillance can also be observed in alternative regimes (including chattel slavery and the Soviet regime). It seems that, rather than being exclusively tied to capitalistic values, the methods in question respond to strong hierarchical structures.</p><br />
<p>In addition, even under a libertarian framework, structural inequalities are still present, allowing a privileged class to enjoy individual freedoms while segregated groups keep performing low-income jobs ([https://www.metamute.org/editorial/articles/californian-ideology 10]), arguably still subject to surveillance. Thus, not only are these technologies compatible with hierarchical top-down forms of government, but also with structures that allow such hierarchies to form without state intervention.</p><br />
<p>That said, this form of management seems less compatible with democratic societies, which tend not only to value individual liberties but to turn them into enforceable rights (including workers' privacy, health and integrity), thus establishing boundaries for workplace surveillance. This could explain why studies of American business leaders have found them unhappy with democratic scruples ([https://www.jstor.org/stable/20024652 11]).</p><br />
<p><br></p><br />
<br />
=== 5. Contingency and alternatives. ===<br />
<p><br></p><br />
<p>Bush writes about the memex, a machine that could extend a person’s memory and that the memory would belong to the person who owned it. As Bush expands, “For mature thought there is no mechanical substitute" ([https://dl.acm.org/doi/pdf/10.1145/227181.227186 12]). His idea was that a machine could take over the repetitive nature of someone’s job, while the person could record their own thoughts for their own use. Bush’s memex was never created, but the idea inspired products like Microsoft’s Productivity Score that were made for employers (the buyers) not for the person whose memory it used (the worker).</p><br />
<p>This immediately brings to mind Meta's Model Capability Initiative, which was done to train AI agents the company hopes to sell to other employers as well as watch their employees ([https://www.reuters.com/sustainability/boards-policy-regulation/meta-start-capturing-employee-mouse-movements-keystrokes-ai-training-data-2026-04-21/ 13]). If this was Bush’s memex, it would belong to the employee using it, not Meta.&nbsp;</p><br />
<br />
<br />
=== 6. Governance implication.<br> ===<br />
Democratic oversight of the use of algorithms as a form of surveillance is essential to ensure that workers’ rights are not overstepped in the name of efficiency. As such we propose: all workers should have a legal right to be consulted and approve a surveillance program before a company installs and uses it. A tracking system should be a group decision, not an inevitable, unilateral one. While the United States has very little protections for workers in terms of surveillance, the EU leads the way with the GDPR, specifically Article 22 ([http://data.europa.eu/eli/reg/2016/679/oj 14]), and the AI Act Article 5 ([http://data.europa.eu/eli/reg/2024/1689/oj 15]). It’s also worth noting that in December 2026, the Platform Work Directive ([https://eur-lex.europa.eu/eli/dir/2024/2831/oj/eng 16]) will come into effect which will ban automated termination.<br />
<br />
= [[Platform Dependence in Public Communication (News)]] Ceren & Rodrigue =<br />
<br />
Public communication is the conveyance of a message to a large group of people. This includes public announcements, advertisements in public spaces, social media broadcasts, news delivered in reporting, editorials, opinion pieces, and even political campaigns. Platform dependence is the reliance on a third party platform or digital infrastructure to reach the audience of the public communication, the public. Platform dependence in public communication therefore includes reliance on private companies like Meta (Facebook), state television channels, or telecommunications providers who provide and control access to, and develop the infrastructure of such platforms. For the purpose of this exercise, news will be utilized as the main example of public communication. It is very difficult to discuss news without highlighting the deep entanglement it shares with with information. For our purpose 'information' will have the the following characteristics; it can be learned, processed, archived, and it's worth correlates to its rarity.<sup>[[#fn1|[1]]]</sup> News is the end result of the process of taking this information from one form to another, and transmitting to a wider, typically public audience is what we will anchor our definition of 'news' to be. <br />
<br />
Those who are affected by platform dependence in public communication are the communicators and the public alike. News outlets are mainly for-profit organizations. These organizations’ reliance on third party digital platforms grows day-by-day to maintain their popularity and engagement ultimately deciding the revenue generated from advertisers. The public on the other hand are provided catchier and more diluted information, gaining just enough knowledge to grab their attention while not being provided substantial knowledge on matters. Additionally, members of the public who do not have the resources to access such platforms and digital services remain “information poor”.&nbsp;<sup>6</sup> Digital rich, the virtual class of tech-professional and entrepreneurs benefit from the dependence to their platforms.<br />
<br />
This is crucial as platform dependence may threaten democracy and free political expression. Platforms, run by private parties, can be run according to their political beliefs. Social media platforms aiming to keep users online utilize algorithms that provide their users with their confirmed preferences, not allowing the conveyance of a truly heterogeneous catalogue of news. The original ideal of the democratic electronic agora is undermined when private corporations control the flow of news and the infrastructure on which they are provided.<br />
<br />
=== Historical Lineage ===<br />
<br />
Modern form of this can be traced to Renaissance Europe,<sup>[[#fn2|[2]]]</sup> where a single innovation displaced established networks of collecting, processing and sharing news.The church, merchants, students, and diplomats were core participants in this ecosystem.<sup>[[#fn3|[3]]]</sup> The invention of printing in the 15th century was a seismic point in history as it offered new possibilities for the dissemination of information and therefore news. Initially, printing benefitted from the existing networks more than the networks benefitted from printing. This was the case until the networks were transformed in an unrecognisable manner (a trend we will see come to see throughout the history of the news. A clear instance of this is Johann Carolus's ''Relation aller Fürnemmen und gedenckwürdigen Historien'', a handwritten newspaper delivered weekly to the elite class of the time. The mode of production and the means of distribution were constrained by the available technology rather than strategy. The mode of production decreased the cost, time and later revolutionised the network as production could be localised and dependency on transporting was reduced.&nbsp;<br><br />
<br />
<br />
One of the first paying customers for press was the Church, selling indulgences. During this era the Church and the State were in a clear symbiotic relationship, and drawing a separation between the two was difficult. Both actors deeply understood Beniger's principle that control depends on information processing and communication working together.<sup>[[#fn4|[4]]]&nbsp;</sup><sup>&nbsp;</sup>By introducing hurdles (such as the requirement of licensing the type of content that could be printed) and benefiting from the industrial might of this innovation, the Church and the state had effectively consolidated power and control. Interestingly, this contrasts what would take place generations later in the computing revolutions, where proximity to the state purposely unmentioned in order to appeal to the masses.<sup>[[#fn5|[5]]]</sup> <sup></sup><br />
<br />
<br />
The next evolution of news took place when transmission was once again innovated with the radio. Radio’s reach could be decoupled from the cost, decreasing reliance on aging networks such as the now matured postal system. Control could be focused on content providers &nbsp;and who would be allowed broadcast rights. This changed the trajectory of news as a broadcaster could deliver news to anyone with a receiver dialed in to the relevant frequency. News outlets now had legitimate, diverse, alternative methods of production and distribution. The television followed not after, however it mostly followed the trajectory of the radio with the caveat that it dominated due to ability to generate commercial revenue through advertisement and optionality it provided.&nbsp;&nbsp;<br />
<br />
=== Mechanism of Path Dependence ===<br />
<br />
The public generally partakes in the consumption of content on social media. Hence, with its 3 billion monthly active users for example, Instagram has an installed base for news outlets to depend upon (Instagram Revenue and Usage Statistics (2026), n.d.). The audience of news outlets spends an increasing amount of their time on social media platforms, which results in a habitual entrenchment for these news outlets. In other words, the means of reaching the audience is dependent on the audience’s habits of content consumption. An indirect contractual entrenchment may also be speculated, as news outlets have obligations to their advertisers (who may request the upkeep of views/clicks on the news platforms they pay to advertise in). Cultural entrenchment should not be disregarded: the public expects to receive their news on social media platforms they readily frequent, and many news outlets meet this expectation. Hence, news outlets must partake in building a presence in social media platforms if they wish to compete.<br />
<br />
=== Politics and Distribution ===<br />
<br />
Barbook argues that although the California Ideology claims that state power will be decreased and individuals will be empowered through decentralized networks enabled by digital technologies, he demonstrates that public communication is in fact not immune to undemocratic powers. These include private corporations: these corporations may gatekeep in choosing when and how to provide access to their platforms, while finetuning how users navigate their platforms. By enabling access to content that users tend to agree with, those who manage these platforms enable public opinion to shift to extremes. Being “fed” the same narrative and not being challenged to see an opposing perspective ultimately provides fewer choices to the consumer of the information, the general public. Therefore, individual agency is constrained by platform architecture and control, not liberated by it.<br />
<br />
=== Point Of No Return ===<br />
In examining the lineage of news and its eventual platform dependency, the diminishing returns of technological advancement for the industry become evident. Revenue has not been a particular focus of this article. The broadcast era was the era in which news outlets earned some of their largest revenues and were at their most independent. It was during this time that news outlets initiated the unbundling of one of their main revenue generators, the classified advertisement. By initiating this [https://stratechery.com/2017/the-great-unbundling/ unbundling] without any afterthought on capitalising on its timely advantages, news outlets entered their relationships with social media platforms in a weakened position. Searching for a saviour and giving the platform the credentials and reputation they needed in the early days in return. Reminiscent of the trend identified earlier. An example of a new's outlet that has navigated this journey with more diligence is [https://business.columbia.edu/insights/ai-transformative-tech/how-new-york-times-company-reinventing-itself-digital-age The New York Times].<br />
<br />
=== Governance Implication & Proposition ===<br />
<br />
It's clear that complete avoidance of these platforms on the part of news outlet is a Herculean request! New's outlets have flocked to these platforms due to their substantial audience and lock on audience. It's virtually impossible for a single organisation to mount a significant rebellion without self harming. A proposal is to approach the problem more as a herd and invest and cultivate more alternative open platforms for example [https://en.wikipedia.org/wiki/Bluesky Bluesky]&nbsp; and [https://joinmastodon.org Mastadon]. The benefit that these platforms bring about begin with not only optionality from the current dependencies but governance via protocol.<br />
<br />
=== Footnotes ===<br />
<br />
# <span id="fn1"></span>Mark Greengrass, Thierry Rentet and Stéphane Gal, ‘The Hinterland of the Newsletter: Handling Information in Space and Time’ in Joad Raymond and Noah Moxham (eds), News Networks in Early Modern Europe (Brill 2016) http://www.jstor.org/stable/10.1163/j.ctt1w8h1ng.34 accessed 7 September 2026; ‘Michel Serres Prononce En Sorbonne La Conférence Inaugurale Du Programme Paris Nouveaux Mondes - La Chancellerie Des Universités de Paris’ (La Chancellerie des Universités de Paris, 1 January 2013) https://www.sorbonne.fr/michel-serres-prononce-en-sorbonne-la-conference-inaugurale-du-programme-paris-nouveaux-mondes/ accessed 7 September 2026. James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986).<br />
# <span id="fn2"></span>Brendan Dooley, Making News in Renaissance Europe (1st edn, Cambridge University Press 2026) https://doi.org/10.1017/9781009358835.<br />
# <span id="fn3"></span>Andrew Pettegree, The Invention of News: How the World Came to Know about Itself (Yale University Press 2014). Helmer Helmers, ‘Public Diplomacy in Early Modern Europe: Towards a New History of News’ (2016) 22 Media History 401 https://doi.org/10.1080/13688804.2016.1174570.<br />
# <span id="fn4"></span>James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986) P24-25<br />
# <span id="fn5"></span>Richard Barbrook and Andy Cameron, The Californian Ideology (1996)<br><br />
#Richard Barbrook and Andy Cameron, The Californian Ideology (1996)<br />
<br />
= Centralization of AI Compute and Data =<br />
<br />
== Centralization of AI Compute and Data - by Sisi Hammoudi & Juliette Chamot ==<br />
=== Governance issue ===<br />
<span class="s8">Today, several path-dependence phenomena are emerging across advanced computing technologies. This assignment addresses one of them: the </span><span class="s8">centralisation</span><span class="s8"> of AI compute and data. Training and running frontier AI systems now depends on a handful of hyperscale providers, namely Amazon, Microsoft, Google, and Nvidia, which dominates the GPU market. In other words, near monopolies exist throughout the supply chain. This concentration creates a governance problem affecting public and private actors alike, both legally and institutionally. On the institutional side, it prevents public administrations, and states other than the US or China, from reaching sovereign AI capacity. It also raises competition-law concerns, since dominant market positions can prevent the market from delivering the best products at the best prices to consumers. Finally, AI developers, like states, are often forced into contracts with hyperscale providers, creating a structural dependence on them.</span><br />
<br />
<span class="s8"></span><br />
=== <span class="s8">Historical lineage</span> ===<br />
==== <span class="s8"><span class="s8">1945</span></span> ====<br />
<span class="s8"><span class="s8">Wartime scientific instruments should have been redirected to extend human command over knowledge, helping establish the postwar model of sustained federal funding for computing research (Vannevar Bush's, "As We May Think », 1945).</span></span><br />
<br />
<span class="s8"><span class="s8"></span></span><br />
==== <span class="s8"><span class="s8">1990s</span></span> ====<br />
<span class="s8"><span class="s8">The privatisation of the NSFNET established the idea that critical digital infrastructure, even though publicly subsidised, could legitimately be privately owned. The EU Commission followed the US's lead, recommending privatisation and deregulation of telecommunications and media as the best way to build the "infobahn" though EU members could instead have chosen nationalisation of the infrastructure (Barbrook & Cameron, "The Californian Ideology," 1996).</span></span><br />
<br />
<span class="s8"><span class="s8"></span></span><br />
==== <span class="s8"><span class="s8">2006</span></span> ====<br />
<span class="s8"><span class="s8"></span></span><div class="s13">Hyperscale cloud computing turned massive fixed capital investment in data centresinto a rentable service, favouring firms able to invest at scale.</div><br />
<div class="s13">Same period: Nvidia's proprietary CUDA software, released alongside its GPUs, became the de facto standard for machine learning, locking in a decade of tooling and expertise around one firm's hardware.</div><br />
<div class="s13"><br />
<br />
==== <span class="s8"><span class="s8"><span class="s8"><span class="s8">From 2022</span></span></span></span> ====<br />
<span class="s8"><span class="s8"><span class="s8"><span class="s8"><span class="s8"><span class="s8">Semiconductor export controls and the CHIPS Act turned compute into an explicit instrument of geopolitical strategy.</span></span></span></span></span></span></div><br />
<br />
<span class="s8"></span><br />
<br />
=== <span class="s8">Mechanisms of path dependance</span><span class="s8"></span> ===<br />
<span class="s8"><span class="s8">Several mechanisms drive this </span><span class="s8">centralisation</span><span class="s8">, but path-dependence ones dominate. Because AI compute is a capital-intensive industry, new entrants struggle to compete with </span><span class="s8">hyperscalers</span><span class="s8"> that have already sunk huge sums into infrastructure, a barrier that produces monopoly-like situations. This dynamic, known as increasing returns, generates system-scale economies that harden into a near-irreversibility of investment (David, "Clio and the Economics of QWERTY," 1985). It overlaps with a second mechanism, </span><span class="s8">standardisation</span><span class="s8">, itself a form of technical interrelatedness: researchers' investment in Nvidia's CUDA-based tooling locks the field into that ecosystem regardless of whether better alternatives exist. A further mechanism is legal and contractual entrenchment. For example, Microsoft's stake in OpenAI binds developers to a specific provider by agreement rather than technical necessity.</span></span><br />
=== Politics and distribution ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">Technology does not have a history of distributing power equally. Rather, its development has strengthened the interests and authority of powerful groups that already possessed economic and political resource</span><span class="s8">s, and it is yet to be determined whether AI compute and data will follow suit</span><span class="s8">. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Author Langdon Winner illustrates </span><span class="s8">the historical con</span><span class="s8">s</span><span class="s8">traints of technological development</span><span class="s8"> with the case of New York from </span><span class="s8">the </span><span class="s8">1920s to the 1970s. He argued that the city’s roads, bridges, and parks’ physical arrangement contained “explicit and implicit political purpose</span><span class="s8">.</span><span class="s8">”</span><span class="s8"> </span><span class="s8">These infrastructures privileged wealthy and white communities while restricting poor and Black populations’ choice of mobility. Similarly, the development of industrial machinery increased productivity, simultaneously weakening union and non-union worker</span><span class="s8">s’</span><span class="s8"> bargaining power.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">In the twentieth century, f</span><span class="s8">ollowing the Industrial Revolution, a Control Revolution emerged from the increasing need to manage </span><span class="s8">expanding production, transportation, and information flows requiring strengthened organizational bureaucratic control.</span><span class="s8"> This was heavily shaped by the political context of post-World War II warfare.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Therefore, the bearer of the initial cost of technology is the person putting in the capital to erect it</span><span class="s8">,</span><span class="s8"> but ultimately, the person bearing the long-term cost of technology, whose choices diminish</span><span class="s8">,</span><span class="s8"> </span><span class="s8">is</span><span class="s8"> not the rich and privileged, but the everyday person subject to technologies. Forced to adapt, to reshape their professional skills to adapt to an environment trying to make them obsolete.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">AI compute and data </span><span class="s8">are</span><span class="s8"> at risk of creating the same effect. I</span><span class="s8">n their critique of dotcom neoliberalism</span><span class="s8">,</span><span class="s8"> authors Barbrook and Cameron exposed a similar socio-economic tension. The Californian Ideology claims digital technology empowers individuals</span><span class="s8">;</span><span class="s8"> however, perpetual unequal access to it creates </span><span class="s8">an apartheid between </span><span class="s8">“information-rich” and “information-poor” populations.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Finally, the development of AI compute and data depends on expensive and scar</span><span class="s8">c</span><span class="s8">e computing infrastructure and </span><span class="s8">a </span><span class="s8">highly concentrated semiconductor supply chain.</span><span class="s8"> Today, this is one of the most concentrated industries</span><span class="s8">,</span><span class="s8"> with single companies having near</span><span class="s8">-</span><span class="s8">total monopolies over the production of chips necessary </span><span class="s8">for</span><span class="s8"> the functioning of AI. This monopoly model threatens to reinforce the existing economic hierarchy.</span></p><br />
<br />
<span class="s8"></span><br />
=== <span class="s8">Contingency and alternatives</span> ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">If a different technological trajectory was plausible, the most apt time for it to have occurred would be during the transition from the Industrial Revolution to </span><span class="s8">the </span><span class="s8">“Control Revolution”. When industrial production accelerated, our society experienced a “crisis of control”, creating opportunities to organize information and communication differently.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Instead of allowing control technologies to </span><span class="s8">be monopolized within businesses and states, our societies could have pursued a more democratic and decentralized system. Barbrook and Cameron provide such an alternative path through their idea of the “electronic agora</span><span class="s8">,</span><span class="s8">” where digital networks could encourage community participation </span><span class="s8">and </span><span class="s8">direct democracy</span><span class="s8">,</span><span class="s8"> where government could actively engage with the people to shape digital infrastructure and expand access.</span><span class="s8"> These alternatives did not actually prevail because corporat</span><span class="s8">e</span><span class="s8"> and state market participants possessed greater resources and authority to shape technological development at the end of the twentieth century. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Inherently, technological development is not predetermined</span><span class="s8">;</span><span class="s8"> it can support either authoritarian or democratic arrangements.</span><span class="s8"> Today, monopolies control chip production needed for AI compute and data, but other technologies like blockchain permit democratic participation.</span></p><br />
<br />
<span class="s8"></span><br />
=== <span class="s8">Governance implication</span> ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">History always threatens to repeat itself. As Barbrook discussed, digital societies are shaped by the political context i</span><span class="s8">n</span><span class="s8"> </span><span class="s8">which</span><span class="s8"> </span><span class="s8">they develop</span><span class="s8">. It is a valid concern, then, that the development of information technology, through AI computing, would follow the same trajectory</span><span class="s8">-</span><span class="s8"> that is, be constrained to benefit the wealthy who funded its development, and ultimately harm the middle and lower classes enabling its functioning. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">However, AI’s place in our society has not yet crystallized. Technology governance does not have to adhere to this system. Such a seemingly sustainable approach to AI compute and data governance has already been broached. In 2022, the Notre Dame Journal on Emerging Technologies published an article in </span><span class="s8">its</span><span class="s8"> issue on Artificial Intelligence where the authors proposed an AI compute system based on a “dual investment strategy”</span><span class="s8">. Firstly, the model would be launched by “subsidizing and negotiating” cloud computing for </span><span class="s17">human </span><span class="s8">AI researchers through “existing” cloud vendors</span><span class="s8">,</span><span class="s8"> which would expand on existing AI compute initiatives. Secondly, the compute system would be specifically invested in as a public</span><span class="s8">ly</span><span class="s8"> owned infrastructure that would </span><span class="s8">b</span><span class="s8">e built</span><span class="s8"> and operate similarly to national libraries which own “academic supercomputing facilities”. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">The pilot program would have a “base level of compute access”</span><span class="s8"> which would keep costs of processing </span><span class="s8">down and</span><span class="s8"> enable it to meet the compute need</span><span class="s8">s</span><span class="s8"> of </span><span class="s8">a majority of</span><span class="s8"> academic researchers. Absent any strengthened legislation on the use of AI compute and data, the hardware would be accompanied by an AI ethics framework to enable sustainable technological governance. In addition to an ethical staff, the human resources needed to keep an AI compute model running would include data officers, scientists, data center and software engineers, research developers, </span><span class="s8">and </span><span class="s8">system administrators. These positions require specialized training, allowing new types of professional</span><span class="s8">s</span><span class="s8">, from any background</span><span class="s8">,</span><span class="s8"> to have access to professional prosperity in the field of AI. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">By implementing these frameworks, never neglecting the human element, and the economic and intellectual impact AI has on our society, we move from a historical determinist perspective to one acknowledging historical constraints and </span><span class="s8">learning</span><span class="s8"> from them.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8"></span></p><br />
<h3 class="s16 mwt-heading" style="text-align: justify;" ><span class="s8">Bibliography</span></h3><br />
<span class="s8"></span><div><div><p>[1] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 124, (1980)</p></div><div><p>[2] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 124, (1980)</p></div><div><p>[3] James R. Beniger, The Control Revolution: Technological and Economic Origins of the Information Society, Harvard University Press, p. 443, 450 (1986)</p></div><div><p>[4] Richard Barbrook, Andy Cameron, The Californian Ideology,&nbsp;''Science as Culture'',&nbsp;''6''(1), 44–72, 61 (1996)</p></div><div><p>[5] Anton Korinek, Jai Vipra, Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence, National Bureau of Economic Research, 10.3386/w33139, p. 11, 13-15 (2024)</p></div></div><div><div><p>[6] James R. Beniger, The Control Revolution: Technological and Economic Origins of the Information Society, Harvard University Press, p. 443, 442 (1986)</p></div><div><p>[7] Richard Barbrook, Andy Cameron, The Californian Ideology,&nbsp;''Science as Culture'',&nbsp;''6''(1), 44–72 (1996)</p></div><div><p>[8] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 130 (1980)</p></div><div><p>[9] Daniel E. Ho, Jennifer King, Russell C. Wald & Christopher Wan, The Centrality of Data and Compute for AI Innovation: A Blueprint for the National Research Cloud, 3 Notre Dame J. on Emerging Tech. 71, 81(2022)</p></div><div><p>[10] Daniel E. Ho, Jennifer King, Russell C. Wald & Christopher Wan, The Centrality of Data and Compute for AI Innovation: A Blueprint for the National Research Cloud, 3 Notre Dame J. on Emerging Tech. 71, 82 (2022)</p></div></div><br />
<br />
== Centralization of AI compute and Data - by Atmika Dechamma & Pablo Latorre ==<br />
=== Governance Issue ===<br />
AI computing capacity and data presents the governance problem of an extreme concentration of technological infrastructure and information in a restricted number of companies that privately and globally dominate the market. This affects public and private actors - such as small and medium enterprises, potential new competitors, and Global South countries - that increasingly depend on AI systems outside their control and/or are deterred from competing with established companies because of impenetrable entry barriers - most notably initial investments and operational costs (1). The institutional and legal relevance of this is that it consolidates, reproduces and amplifies asymmetries of power in favor of the “Big Tech”, reverting the technological trend from digital decentralization to physical infrastructure dependency and curbing innovation and market efficiency.<br />
<br />
=== Historical Lineage ===<br />
==== Limitation of Machine Learning ====<br />
<p style="text-align: justify;">The AI revolution was built on the limitation of human capabilities to process large information and derive efficient results - where before there existed only facilitative tools to allow for human-enabled processes, AI now offered derivations and cognitive reasoning in moments and at large scales.</p><br />
<br />
<br><br />
==== Revert to Physical Infrastructure Dependency in the rush to be the best ====<br />
<p style="text-align: justify;">The present AI model heavily relies on hardware in order to perform complex data processing for deep learning. The data centre models followed require larger model sizes (which require higher resource, information and capital investment) to be able to yield better results. Due to the limitation of resources and a rush to establish the best working model of an AI agent, data centres are built on a rudimentary model heavily dependent on massive amounts of electricity and fresh water (2).</p><br />
<br />
<br><br />
==== Regulation and Decentralization of Information ====<br />
<p style="text-align: justify;">Regulation and influence of sovereigns and institutions has resulted in data sharing and information exchange structurally through open source and cloud computing. But, while AI models claims their selling point to be accessibility for all, their information and derivations remain in a closed server, stored for the purpose of training their AI agents to be the best (3). Big AI contenders attract higher consumer and information flows overall resulting in a better developed AI model, proving disadvantageous in any market where early contenders have an advantage and accumulation of power.</p><br />
<br />
=== Mechanisms of Path Dependence ===<br />
<p style="text-align: justify;">Early on in the industry there is an expectation of human and capital investment from all stakeholders involved, this high cost for entry into the market and expected capital to sustain and develop a model by both consumer and enterprise makes for a high switching cost. For the AI model to run and scale there is a presumption that the rate of growth is dependent on the size of data fed, resulting in a better model and hence, more consumer usage. A closed centralised data loop is created but the requirement for storage and processing far surpasses current infrastructures capabilities - heavily relying on early market entry advantage and sustained capital investments taking away from smaller aspirants and hoarding of power within closed circles. Despite its physical dependency, AI data processing has unique requirements beyond legacy infrastructures (4) - larger demand and production of GPUs and designed to handle immense thermal heat generated while consuming electricity beyond current capabilities.&nbsp;</p><br />
<br />
<br><p style="text-align: justify;">The AI space largely remains unregulated due to its undefined form and fluid nature, however, this has given way for unethical and morality issues regarding data privacy, exploitation of labour and environmental harms.</p><br />
<br />
=== Politics and Distribution ===<br />
Concentration strengthens the values, interests, capacities, and authority of the “Big Tech” over other actors of public and private nature. In this context, Barbrook and Cameron (5) illuminate the ethos behind AI technology development while Winner (6) makes observable the power relations surrounding it: concentration is the consequence of an AI development anchored in the belief that it must be free from all institutional and normative restriction since it is inherently liberating and non-political which, in turn, provides a political/moral justification for the concentration (if technology is inherently liberating and non-political then there is no power relations to observe or question) that translates itself into power dynamics where the AI developer not only owns the AI technology but also decides how it is trained and deployed and which models the user can or cannot access.<br />
<br />
=== Contingency and Alternatives ===<br />
Concentration is due, first and foremost, to the fact that AI computing capacity requires massive and cutting-edge physical infrastructure - such as data centers and microprocessors - which, in turn, requires upfront investments that are unaffordable to most companies. In David’s (7) language, companies that could finance the infrastructure and position themselves first obtained self-reinforcing advantages and a “lock-in” effect in the market. In other words, concentration is the consequence of the development of AI physical infrastructure privately with no mixed or public alternatives as a public service. Therefore, there was a space for an alternative future at the end of the 1980s or the beginning of the 1990s when the privatization model of the technological infrastructure was consolidated in line with the “Californian Ideology”. In that moment governments had the chance to treat technological infrastructure as a mixed or public good rendering it universally accessible as it was the case of the Internet; this would have permitted companies of all sizes to profit from economies of scale, reducing entry barriers and fostering competition. However, this alternative path did not prevail since the Californian Ideology provided the moral/political justification to exclude governments from the development of technological infrastructure in the exact moment in which such a decision would produce structural consequences. If that path had been followed it could have contributed to collective access to economies of scale, lower entry barriers, and a more competitive AI market.<br />
<br />
=== Governance Implication ===<br />
Considering the above, public or mixed investment on AI physical infrastructure is a necessary governance measure for market decentralization and collective access to AI computing capacity and data. From an historical perspective, the proposed measure is not merely a corrective action for a market failure but for a contingent and ideological decision made between the late 1980s and early 1990s that produced a structural “path dependence” that now is necessary to change.<br />
==== References ====<br />
(1) The Quiet Re-Centralization of Tech: Why AI Is Reversing 20 Years of Platform Decentralization. (2026, January 10). Retrieved on 8 September 2026, from Medium website : [https://medium.com/@sumitbhardwaj1357/the-quiet-re-centralization-of-tech-why-ai-is-reversing-20-years-of-platform-decentralization-ce15962b6a13 https://medium.com/@sumitbhardwaj1357/the-quiet-re-centralization-of-tech-why-ai-is-reversing-20-years-of-platform-decentralization-ce15962b6a13]<br />
<br />
(2) [https://www.mdpi.com/1996-1073/19/1/137 Ginzburg-Ganz, E., Lifshits, P., Machlev, R., Belikov, J., Krieger, Z., & Levron, Y. (2025). Technical challenges of AI data center integration into power grids—A survey. <em>Energies</em>, <em>19</em>(1), 137.]<br />
<br />
(3) [https://decai-resources.s3.us-east-1.amazonaws.com/decentralized_ML_perspective-16.pdf Singh, A., Lu, C., Gupta, G., Chopra, A., Blanc, J., Klinghoffer, T., ... & Raskar, R. (2024). A perspective on decentralizing AI.]<br />
<br />
(4) The Rise of AI Data Center Models and the Decline of the General-Purpose Data Center. (Circa 2026). Retrieved on 8 September 2026, from SubZero Engineering website : [https://www.subzeroeng.com/the-decline-of-the-general-purpose-data-center/ https://www.subzeroeng.com/the-decline-of-the-general-purpose-data-center/]<br />
<br />
(5) [https://git.xpub.nl/onebigear/SI_09_reference_library/raw/commit/22bf61e1dcfed35d58fba23808212bd00584be47/Richard_Barbrook_Andy_Cameron_Californian_ideology.pdf Barbrook, R., & Cameron, A. (1996). The Californian Ideology. <em>Science as Culture</em>, <em>6</em>(1), 44-72].<br />
<br />
(6) [https://d1wqtxts1xzle7.cloudfront.net/87708502/langdon_winner_do_artifacts_have_politics-libre.pdf?1655588533=&response-content-disposition=inline%3B+filename%3DDo_Artifacts_Have_Politics.pdf&Expires=1788890463&Signature=UBBiMqkip5MfYZbkbLNAN6aE2hyZdKkER-HFcmyxXkwIZuTnMKdOGoao8ddFr-rQ5T55A8NWUOlnZkGYmi66e7XR9h99DgTELMCrh48sXjOb8KYgA48r~SUUymt1IW~R~aOKJzitMIUHcrc6yEGKK1OuaA~mrEIVOXpUjQMYjqOd26Xmk9YJEglTkqaxeR47VCCth5FvozNQIowdfjzeu8aNHnI8V7Yur1IiXY~PGvYRcN6wBtcgpVMHZUtNaI8NjmYbp2p5TBYrPMF9MCLtvpGhPlsCfsvA8Bdm6XulGwRlksZBKWvVUQ8D~M8oLu12V39YaiETIObyJqbE7ctIcQ__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA Winner, L. (2017). Do artifacts have politics?. In <em>Computer ethics</em>(pp. 177-192). Routledge].<br />
<br />
(7) [https://sjbae.pbworks.com/f/David+1985.pdf David, P. A. (1985). Clio and the Economics of QWERTY. <em>The American economic review</em>, <em>75</em>(2), 332-337].<br />
<br />
== Centralization of AI compute and Data - by Sergey Abramov and Paul Stein ==<br />
<div><br />
=== The current governance issue ===<br />
<p>Advanced AI currently depends on a narrow group of tech giants<sup>1</sup> and semiconductor oligopolies controlling microchips and software, hyperscale cloud infrastructure, large datasets, frontier models, and distribution platforms. This presents a governance problem where this narrow group exercises control over foundational digital infrastructure. This directly affects consumers, businesses, and academia out of AI. Legally and institutionally, this matters because it creates a profound democratic deficit: this neutralizes antitrust frameworks designed for traditional markets, often bypassing conventional copyright and data privacy protections through unchecked data harvesting thereby complicating enforcement.This ultimately might affect national sovereignty as the countries that host the buildout will shape the future of AI: who controls it, what values it contains, how it is used<sup>2</sup>.</p><br />
<br><br />
=== Historical lineage ===<br />
<p>In 1987, Taiwan Semiconductor Manufacturing Company (TSMC) was founded, establishing the world’s first semiconductor fab. Instead of designing and making its own chips, TSMC only manufactured chips designed by other companies. Today, nearly 100% of the world's most advanced AI processors are manufactured by TSMC, leaving the entire global AI compute supply chain centralized under one company.</p><br />
<br><p>In 2006, Nvidia launched CUDA (Compute Unified Device Architecture), a free software layer that allowed developers to use Nvidia's graphics chips (GPUs) which later became perfect for training deep neural networks. Today, this creates a near-monopoly on AI compute hardware.</p><br />
<br><p>Soon after Amazon launched AWS, Microsoft and Google launched their own cloud platforms marking the structural pivot to the cloud service provider model, shifting computing from a distributed architecture (where companies bought and managed their own physical servers) to a centralized infrastructure. As training modern AI models requires tens of thousands of GPUs, today’s frontier AI companies are entirely dependent on the extremely expensive physical infrastructure of a handful of cloud hyper-scalers (Microsoft, Google, AWS, and Meta).</p><br />
<br><p>In 2009, Fei-Fei Li launched ImageNet, a massive database of over 14 million images, which proved that AI model performance scales directly with data volume. This created an immediate institutional advantage for consumer internet platforms (like Google and Meta), because they were already architected to collect, centralize, and store masses of user data through search engines and social networks, they possessed the unique data stack required to train high-performing AI.</p><br />
<br><br />
=== Mechanism of path dependence ===<br />
<p>The centralization of AI compute and data is a classic case of technological lock-in. When structural choices were made decades ago, they triggered powerful, self-reinforcing loops. One such loop is the switching costs and software standardisation. As developers have spent more than a decade working with CUDA, moving to a rival hardware provider (or a decentralized compute network) requires an enterprise to completely rewrite its foundational software stack. The cost of code migration, developer retraining, and potential hardware downtime force companies to stay tied to dominant hardware monopolies such as Nvidia. Commitments, licensing conditions, and exclusivity provisions add contractual costs. Fewer than 1% of cloud customers switch provider annually, identifying technical differentiation and data-transfer charges as important barriers<sup>4</sup>.</p><br />
<br><p>Network effects also matter for computing power. More customers generate more revenue, usage information, and opportunities to improve infrastructure and models. Better services attract additional users and developers, whose applications make the platform more valuable. In cloud–AI partnerships, providers may additionally obtain information about model performance and future infrastructure demand. These feedback loops strengthen firms already operating across cloud, models, software, and distribution.</p><br />
<br><br />
=== Politics and distribution ===<br />
<p>According to Langdon Winner's definition, modern AI computing infrastructure may qualify as an "inherently political technology" because its large scale and significant financial requirements not only lend themselves to, but necessitate,<sup>5</sup> centralized, hierarchical control. The physical siting of this infrastructure shows evidence of Winner’s second category of politicization of technologies, the ‘political arrangement’:<sup>6</sup> Of the five largest U.S. AI firms, four are headquartered in California,<sup>7</sup> while just one is (partially) domiciled in Texas. Texas, however, hosts twice the GPU clusters.<sup>8</sup> This placement geographically insulates beneficiaries of the data infrastructure boom from its negative externalities. The specific choice of location may itself be a deliberate preference on account of Texas’ unique approach to water usage rights.<sup>9</sup> Juxtaposition of this unequal and even exploitative balance of interests with the pontificating rhetoric of the urban, information rich, beneficiaries is evocative of the internal contradictions of the Californian Ideology - the virtual artisans existence and privileged position is still based on the exploitation of a vulnerable out-group, the "information-rich" consuming the output, the "information-poor" hosting the extraction.<sup>10</sup></p><br />
<br><br />
=== Contingency and Alternatives ===<br />
<p>Profit motive and economies of scale now concentrate investment among a few hyperscalers,<sup>11</sup> but this reflects policy choice, not government incapacity: Compute infrastructure may be inherently political, but the technology is agnostic as to where the organizing authority originates, and states have historically funded infrastructure of comparable or greater scale, while facing less pressure to show short-term returns. The clearest turning point was 1995, when the National Science Foundation retired NSFNET, the publicly funded backbone that had connected U.S. research and supercomputing centers since the mid-1980s,<sup>12</sup> handing internet infrastructure to commercial providers with no conditions attached. This was a deliberate policy decision made amid the deregulatory push of the Clinton era. The privatization that followed ushered in the private industrial dominance that persists today in the form of hyperscalers. Had a publicly governed backbone instead been scaled up, today's compute infrastructure might rest on a different foundation entirely.</p><br />
<br><br />
=== Governance implication ===<br />
<p>Despite private hyperscaler dominance, the U.S. does have a nominal public alternative: the National AI Research Resource (NAIRR), established following the National AI Initiative Act of 2020 and piloted from January 2024, which explicitly aims to democratize access to the computational resources essential to AI research.<sup>13</sup>In Europe, a comparable program is the EuroHPCJU,<sup>14</sup> an initiative intended to pool resources to build supercomputing capacity. The undertaking’s legislative basis has since been extended to include networked ‘AI factories', as well as the so-called “Gigafactories”.<sup>15</sup> The framing in language of sovereignty indicates intent to at least compete with private infrastructure initiatives. Though government-led measures cannot reverse the centralization of compute, they can democratize access - provided they are intensified. The European Commission has “set a goal of investing more than €1 billion per year in AI research and innovation”.<sup>16</sup> While laudable in its own right, it pales in comparison to the investments of industry leaders, which are approaching, if not exceeding, trillions of Dollars.</p><br />
<br />
=== References & Notes ===<br />
1.Amazon, Google, Meta, Microsoft, and Oracle collectively hold an estimated 71% of the world’s cumulative AI compute as of Q4 2025, measured in H100-equivalents of computing power.&nbsp;<p>Luke Emberson, Josh You and Venkat Somala (2026), "Five hyperscalers now own over two-thirds of global AI compute". Published online at epoch.ai. Retrieved from 'https://epoch.ai/data-insights/hyperscalers-control-most-compute' [online resource]. Accessed 7 Sept 2026.</p>2. Alasdair Phillips-Robins, Teddy Tawil and Sam Winter-Levy, ‘The Compute Coalition: How to Build the Future of AI in the Free World’ (Carnegie Endowment for International Peace, 8 June 2026) https://carnegieendowment.org/research/2026/06/the-compute-coalition-how-to-build-the-future-of-ai-in-the-free-world accessed 7 September 2026.<br />
<br />
3. Amazon Web Services (AWS), a cloud computing platform<br />
<br />
4.&nbsp;Competition and Markets Authority, Cloud Infrastructure Services: Final Decision Report (31 July 2025) https://assets.publishing.service.gov.uk/media/688b8891fdde2b8f73469544/final_decision_report.pdf accessed 7 September 2026.<br />
<br />
5. Langdon Winner, 'Do Artifacts Have Politics?' (1980) 109(1) ''Daedalus'' 121, 128.<br />
<br />
6. Ibid. 123.<br />
<br />
7. OpenAI, Anthropic, Google DeepMind, Meta AI. xAI is an exception to the rule, domiciled between Palo Alto, CA and San Antonio, TX.<br />
<br />
8. Texas’ 17 to California’s 8, cf. Texas Royalty Brokers, 'AI Clusters by State' (''Texas Royalty Brokers'', 2025) https://texasroyaltybrokers.com/ai-clusters-by-state/ accessed 7 September 2026.<br />
<br />
9. The ‘rule of capture’, established in Houston & TC Railway Co v East (Tex 1904), permits landowners to extract groundwater beneath their land without liability for depleting adjacent wells or aquifers, a doctrine now exploited by hyperscale AI data centres to draw large cooling-water volumes with minimal regulatory constraint.<br />
<br />
10. Richard Barbrook and Andy Cameron, 'The Californian Ideology' (1996) 6(1) ''Science as Culture'' 44.<br />
<br />
11. Goldman Sachs, 'Global AI Investment Is Forecast to Exceed $1 Trillion in 2026' (''Goldman Sachs Insights'', 7 August 2026) https://www.goldmansachs.com/insights/articles/global-investment-is-forecast-to-exceed-1-trillion-in-2026 accessed 7 September 2026.<br />
<br />
12. &nbsp;National Science Foundation, 'Birth of the Commercial Internet' (''NSF Impacts'') https://www.nsf.gov/impacts/internet accessed 7 September 2026.<br />
<br />
13. CASRAI, 'NAIRR: National AI Research Resource, Explained' (''CASRAI'') https://casrai.org/dictionary/term/national-ai-research-resource-nairr accessed 7 September 2026.<br />
<br />
14. Council Regulation (EU) 2021/1173 of 13 July 2021 on establishing the European High Performance Computing Joint Undertaking and repealing Regulation (EU) 2018/1488 [2021] OJ L256/1.<br />
<br />
15. Council Regulation (EU) 2026/150 of 16 January 2026 amending Regulation (EU) 2021/1173 on establishing the European High Performance Computing Joint Undertaking [2026] OJ L 2026/150.<br />
<br />
16.&nbsp;European Commission, 'Realising Europe's Digital Decade' (''European Commission'', 11 October 2024) https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/story-von-der-leyen-commission/realising-europes-digital-decade_en accessed 7 September 2026.</div></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Governance_by_history&diff=123777Governance by history2026-09-09T07:18:38Z<p>Isiklar Ceren: /* Platform Dependence in Public Communication (News) Ceren & Rodrigue */</p>
<hr />
<div>= [[Workplace surveillance]] =<br />
== [[Information Control and Workplace Surveillance - by Jihae Park and Mariona Fortuny Jané]] ==<br />
==== <span style="font-size: 12pt;">The Current Governance Issue</span> ====<br />
<span style="font-size: 10pt;">There are numerous current governance problems arising from technological innovations, yet here we will specifically focus on the information control and workplace surveillance. Whether intended or unintended, there were certain historical incidents which resulted in social and political consequences. As noticed from the Control Revolution, the dramatic evolution in mass media and telecommunications technologies has led to the reinforcement of the economic and political control during the Industrial Revolution. ([https://archive.org/details/beniger-james-the-control-revolution Beniger, 1986]) By applying this logic to a modern example, this is clearly how many corporations are getting in control of their employees through surveillance technologies. Along with the emergence of remote and hybrid work after Covid-19, employers are now relying on “bossware” to analyze the emails, chats, and messages of their employees on platforms such as Teams or Slack. ([https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/view/19100/13263 Ollier-Malaterre et al., 2026, p.237]) Some companies have strict restrictions on transferring data both internally and externally in protection of confidential information and consistently monitor their workers to the certain extent which could slow down their efficiency. This is problematic as it’s not only violating the privacy of their employees but also depriving employees of rights they should be naturally be able to exercise.</span><br />
<br />
<span style="font-size: 12pt;"></span><br />
<br />
==== <span style="font-size: 12pt;">Historical Lineage</span> ====<br />
<span style="font-size: 12pt;"><span style="font-size: 10pt;">In relation to the current issue of the information control and workplace surveillance, Max Weber’s argument of bureaucracy and rationalization in the middle and late nineteenth century are good historical examples which are still frequently visible nowadays. Weber stated how the range of control could extend not only by expanding the capability to process information but also by limiting the amount of information to be processed. Here, the former is directly related to the control implemented by bureaucratization (in the mid 19th century) and computerization (in the late 20th century), whereas the latter addresses rationalization. An example from bureaucracy is the expansion of paperwork in response to the growth in information. We can still note these traces of bureaucracy from numerous procedures that we have to go through for a decision-making to take place in corporations. He brings up the example of standardized time zones for rationalization which is simply an example for an omission or a breakdown of information to facilitate its processing. ([https://archive.org/details/beniger-james-the-control-revolution Beniger, 1986, p.15-16]) This is also commonly seen from nowadays as some companies may use internal terminologies for the sake of both confidentiality and efficiency.</span></span><br />
<br />
==== <span style="font-size: 12pt;">Mechanism of Path Dependence</span> ====<br />
<p>Following along the line with the historical lineage, there are certain mechanisms at work of path dependence for information control and workplace surveillance. Bureaucracy is closely related with organizational routines. Many companies have already settled down with a fixed workflow and decision-making process, which makes it more costly for one to change from its conventional way of working. This means switching costs from an old system to a new one is clearly high considering its time and capital, not necessarily will guarantee increasing returns. Hence, many firms end up maintaining its old strategy, reluctant to make any modifications or changes.<br></p><br />
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==== <span style="font-size: 12pt;">Politics and Distribution</span> ====<br />
<br />
As businesses grew too large for managers to oversee everything directly, companies replaced human judgment with formal rule-systems, as we see explained by Beniger's 'intellectual technology' ([https://archive.org/details/beniger-james-the-control-revolution/page/65/mode/2up Beniger, 1986, pp. 17, 21]). Algorithmic management continues this: a call once made by a supervisor's judgment is now a rule built into software that runs without one, extending a logic Beniger traces as far back as to Taylorism and the so called 'assembly line'. Winner ([https://www.jstor.org/stable/20024652 1980]) asks whether such systems must concentrate power this way or were driven there, when other designs were equally possible; nothing required shutting workers out of the decision, so leaving them out was a political choice, and not necessarily a technical necessity. Barbrook and Cameron ([https://doi.org/10.1080/09505439609526455 1996]) explain the reasoning why some can defend this 'domination': they show how 1990s tech culture sold new technologies as freedom even as it tightened control, so the rhetoric could become one of closer oversight as flexibility and autonomy. Together, authority accrues to employers, who in some systems can set and revise these oversight rules unilaterally and face less resistance because the arrangement is framed as freedom; workers bear the cost, losing the informal give-and-take they had with a human supervisor for oversight that is harder to see, question, or contest, while being told it grants them more freedom, not less.<br />
<br />
==== <span style="font-size: 12pt;">Contingency and Alternatives</span> ====<br />
<br />
A plausible alternative happened on U.S. post WWII: in some workplaces, labor and its pacing was demanded to be set through collective bargaining and enforced jointly, by both management and union stewards monitoring compliance on the line ([https://doi.org/10.1093/icc/dtaf038 Breznitz et al., 2025, p. 211]). So, in this context, workplace surveillance could have developed as a bargained, dual-administered practice rather than a management monopoly. The 1950 [https://en.wikipedia.org/wiki/Reuther%27s_Treaty_of_Detroit Reuther's Treaty of Detroit ] cut that possibility off: unions won guaranteed wages and benefits in exchange for surrendering any general claim over how work was supervised ([https://doi.org/10.1093/icc/dtaf038 Breznitz et al., 2025, pp. 210–211]). Workers depended on wages to survive, and employers controlled the wage relationship. That asymmetry meant employers, given their position of power, were able to arrange things so that, at the very least, workers would have far less capacity to sustain a fight over control itself. Thus, the "trade" wasn't a fair exchange between equals. This reflects which side could afford to hold out on which issue. Hypothetically speaking, had that joint administration model prevailed instead, this could have greatly impacted norms internationally and good practices with worker-union agreed surveillance would have become a widely accepted standard practice.<br />
<br />
==== <span style="font-size: 12pt;">Governance Implication</span> ====<br />
<br />
An interesting proposition for present-day governance that wants to fill a gap in workplace surveillance is what [https://doi.org/10.1016/j.digbus.2025.100120 Kayas, Ong and Belal (2025)] are proposing: They argue that EU law, through the [https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng GDPR] and its required [https://en.wikipedia.org/wiki/Data_protection_impact_assessment data protection impact assessments (DPIAs)], already offers meaningful protection for workers in terms of lawful high-risk data collection and data processing. Nevertheless, these DPIAs are built around data and privacy, so they leave out several dimensions of monitoring itself: its purpose, how intrusive it is, how visible it is to the people being watched, and its effects on workers' autonomy, trust, and standing relative to management. These authors propose a "surveillance impact assessment" scoring a system against these characteristics directly, before any surveillance system is put in place. Although this mechanism "is constrained by its reliance on existing literature and the lack of empirical validation," it feels like a genuine alternative for two reasons: 1. it targets the actual mechanism at issue, and 2. at the same time it builds upon a mechanism of active participatory approach where employees have a direct say in how surveillance is designed ([https://doi.org/10.1016/j.digbus.2025.100120 Kayas et al., 2025, p. 11]), which, combined with the actual assessment, would put workers' own judgment at the centre of the one decision that affects them. It's important to note that this alternative is proposed as worth piloting, not as a proven fix, and it is fair to ask whether another mandatory assessment stacked on top of DPIAs would function as intended or simply read to workers as more compliance paperwork.<br />
<br />
==== References ====<br />
<br>Barbrook, R., & Cameron, A. (1996). The Californian Ideology. ''Science as Culture'', 6(1), 44–72. [https://doi.org/10.1080/09505439609526455 https://doi.org/10.1080/09505439609526455]<br>Beniger, J. R. (1986). ''The Control Revolution: Technological and Economic Origins of the Information Society''. Harvard University Press. [https://archive.org/details/beniger-james-the-control-revolution https://archive.org/details/beniger-james-the-control-revolution]&nbsp;<br>Breznitz, D., Levy, K., Lipartito, K., & Zehavi, A. (2025). An equity-focused research agenda for workplace surveillance. ''Industrial and Corporate Change'', 35(1), 206–221. [https://doi.org/10.1093/icc/dtaf038 https://doi.org/10.1093/icc/dtaf038]<br>Kayas, O. G., Ong, C. E., & Belal, H. M. (2025). From humans to algorithms: A sociotechnical framework of workplace surveillance. ''Digital Business'', 5, 100120. [https://doi.org/10.1016/j.digbus.2025.100120 https://doi.org/10.1016/j.digbus.2025.100120]<br>Ollier-Malaterre, A., Parent-Rocheleau, X., Benkrid, K., & Provost Savard, Y. (2026). Making Sense of Workplace Surveillance: How Workers and Union Representatives Experience, Imagine, and Resist Surveillance Exposure. ''Surveillance & Society'', 24(3), 236–254. [https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/view/19100/13263 https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/view/19100/13263]<br>Winner, L. (1980). Do Artifacts Have Politics? ''Daedalus'', 109(1), 121–136. [https://www.jstor.org/stable/20024652 https://www.jstor.org/stable/20024652]<br />
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<br><br />
<br />
== [[Algorithmic management and workplace surveillance - by Sebastián Muller and Kate Davey'''&nbsp;''']] ==<br />
<br />
<br />
<br />
<br />
<br />
=== 1. The current issue. ===<br />
<br><p>Algorithmic management and workplace surveillance can be defined as the use of computer-programmed procedures to coordinate labor input in an organization ([https://joint-research-centre.ec.europa.eu/scientific-activities/employment/algorithmic-management-and-digital-monitoring-work_en 1]). Simply put, it is a way to control workers, and workers generally have no say in how the system that tracks them is created. As Winner says "different people are differently situated and possess unequal degrees of power as well as unequal levels of awareness" ([https://www.jstor.org/stable/20024652?seq=7 2]).</p><br />
<p>The population affected is workers; both “white collar” and “blue collar” workers are impacted. Whether it’s Amazon tracking warehouse workers’ “Time Off Task” with handheld scanners ([https://www.wired.com/story/amazon-worker-tracking-details-revealed 3]) or Meta employees having their every click tracked ([https://www.techpolicy.press/metas-worker-surveillance-tests-eu-rules-on-ai-and-labor/ 4]) to train AI, employers have the power to watch and control their employees in an unprecedented way.</p><br />
<p>It matters legally because workers have very few rights to fight back against these surveillance programs; even the The Electronic Communications Privacy Act of 1986 allows exceptions to surveillance of employees ([https://bja.ojp.gov/program/it/privacy-civil-liberties/authorities/statutes/1285 5]).<br></p><br />
<br />
=== <br>2. Historical lineage. ===<br />
<p><br>2.1 Panopticon: it is an architectural apparatus developed by Jeremy Bentham in 1791. The design of this building effectively generated the sense of constant monitoring, which in turn motivated the prisoners to behave as if they were being watched at all times. As human labor became commodified, capitalists began implementing measures to ensure the maximization of productivity, including the replication of this design ([https://doi.org/10.14452/MR-070-09-2019-02_2 6]). While unused today, the panopticon is widely considered as both a theoretical and practical inspiration of other forms of surveillance in the workplace.</p><br />
<p><br></p><br />
<p>2.2 Scientific management: this theory attempts to analyze and standardize workflows to improve labor productivity. Frederick Winslow Taylor, its main pioneer, used early forms of data analysis during the XX century to decrease walking distances, eliminating unnecessary movements and preventing deliberate slow-walking among workers. ([https://doi.org/10.14452/MR-070-09-2019-02_2 7]). There are many modern forms of data-driven decision-making processes in the workforce. For instance, Amazon warehouses track individual workers' scan rates in real time through handheld scanners, generating data feeds to track and evaluate performance ([https://www.theverge.com/2019/4/25/18516004/amazon-warehouse-fulfillment-centers-productivity-firing-terminations 8]).</p><br />
<p><br></p><br />
<p>2.3 PC in the workplace: John Blankenbaker designed the first commercially available personal computer in 1971 ([https://www.computerhistory.org/revolution/personal-computers/17/297 9]), however, it wasn’t until the mid-1980s that the use of personal computers in the workplace became an industry standard. This achievement gave rise to the digital monitoring of work, which in turn allowed employers to monitor employees in real-time, effectively replacing the human eye with a more efficient surveillance mechanism. This represents one of the key aspects of modern-day workplace monitoring.<br><br></p><br />
<p><br></p><br />
<br />
=== 3. Mechanism of path dependence. ===<br />
'''<br>'''When analyzing the historic lineage of work surveillance, it is possible to point out two main path dependencies mechanisms in place.<p>Firstly, it is clear that many of the technological developments that arose through these events have one major goal, which is to increase wealth within a hierarchical ecosystem. Employers resort to several mechanisms to maximize profits and cut inefficiencies at the expense of workers.&nbsp;</p><br />
<p>In addition, standardization can also be singled out as a key mechanism at play. Once one corporation implements any of these developments (such as the digital monitoring of the workplace), the market incentives would force the rest to do the same in order to be profitable and remain competitive.</p><br />
<br />
=== 4. Politics and distribution. ===<br />
<br>One simple answer to this question would be that capitalists implement and leverage these mechanisms to increase their wealth while the working class remains powerless and unable to withdraw itself from the system in force.&nbsp;<p>However, if we resort to Winner's framework, we see that the technical elements of these technologies are not intrinsically capitalist, since workplace surveillance can also be observed in alternative regimes (including chattel slavery and the Soviet regime). It seems that, rather than being exclusively tied to capitalistic values, the methods in question respond to strong hierarchical structures.</p><br />
<p>In addition, even under a libertarian framework, structural inequalities are still present, allowing a privileged class to enjoy individual freedoms while segregated groups keep performing low-income jobs ([https://www.metamute.org/editorial/articles/californian-ideology 10]), arguably still subject to surveillance. Thus, not only are these technologies compatible with hierarchical top-down forms of government, but also with structures that allow such hierarchies to form without state intervention.</p><br />
<p>That said, this form of management seems less compatible with democratic societies, which tend not only to value individual liberties but to turn them into enforceable rights (including workers' privacy, health and integrity), thus establishing boundaries for workplace surveillance. This could explain why studies of American business leaders have found them unhappy with democratic scruples ([https://www.jstor.org/stable/20024652 11]).</p><br />
<p><br></p><br />
<br />
=== 5. Contingency and alternatives. ===<br />
<p><br></p><br />
<p>Bush writes about the memex, a machine that could extend a person’s memory and that the memory would belong to the person who owned it. As Bush expands, “For mature thought there is no mechanical substitute" ([https://dl.acm.org/doi/pdf/10.1145/227181.227186 12]). His idea was that a machine could take over the repetitive nature of someone’s job, while the person could record their own thoughts for their own use. Bush’s memex was never created, but the idea inspired products like Microsoft’s Productivity Score that were made for employers (the buyers) not for the person whose memory it used (the worker).</p><br />
<p>This immediately brings to mind Meta's Model Capability Initiative, which was done to train AI agents the company hopes to sell to other employers as well as watch their employees ([https://www.reuters.com/sustainability/boards-policy-regulation/meta-start-capturing-employee-mouse-movements-keystrokes-ai-training-data-2026-04-21/ 13]). If this was Bush’s memex, it would belong to the employee using it, not Meta.&nbsp;</p><br />
<br />
<br />
=== 6. Governance implication.<br> ===<br />
Democratic oversight of the use of algorithms as a form of surveillance is essential to ensure that workers’ rights are not overstepped in the name of efficiency. As such we propose: all workers should have a legal right to be consulted and approve a surveillance program before a company installs and uses it. A tracking system should be a group decision, not an inevitable, unilateral one. While the United States has very little protections for workers in terms of surveillance, the EU leads the way with the GDPR, specifically Article 22 ([http://data.europa.eu/eli/reg/2016/679/oj 14]), and the AI Act Article 5 ([http://data.europa.eu/eli/reg/2024/1689/oj 15]). It’s also worth noting that in December 2026, the Platform Work Directive ([https://eur-lex.europa.eu/eli/dir/2024/2831/oj/eng 16]) will come into effect which will ban automated termination.<br />
<br />
== [[Platform Dependence in Public Communication (News)]] Ceren & Rodrigue ==<br />
<br />
Public communication is the conveyance of a message to a large group of people. This includes public announcements, advertisements in public spaces, social media broadcasts, news delivered in reporting, editorials, opinion pieces, and even political campaigns. Platform dependence is the reliance on a third party platform or digital infrastructure to reach the audience of the public communication, the public. Platform dependence in public communication therefore includes reliance on private companies like Meta (Facebook), state television channels, or telecommunications providers who provide and control access to, and develop the infrastructure of such platforms. For the purpose of this exercise, news will be utilized as the main example of public communication. It is very difficult to discuss news without highlighting the deep entanglement it shares with with information. For our purpose 'information' will have the the following characteristics; it can be learned, processed, archived, and it's worth correlates to its rarity.<sup>[[#fn1|[1]]]</sup> News is the end result of the process of taking this information from one form to another, and transmitting to a wider, typically public audience is what we will anchor our definition of 'news' to be. <br />
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Those who are affected by platform dependence in public communication are the communicators and the public alike. News outlets are mainly for-profit organizations. These organizations’ reliance on third party digital platforms grows day-by-day to maintain their popularity and engagement ultimately deciding the revenue generated from advertisers. The public on the other hand are provided catchier and more diluted information, gaining just enough knowledge to grab their attention while not being provided substantial knowledge on matters. Additionally, members of the public who do not have the resources to access such platforms and digital services remain “information poor”.&nbsp;<sup>6</sup> Digital rich, the virtual class of tech-professional and entrepreneurs benefit from the dependence to their platforms.<br />
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This is crucial as platform dependence may threaten democracy and free political expression. Platforms, run by private parties, can be run according to their political beliefs. Social media platforms aiming to keep users online utilize algorithms that provide their users with their confirmed preferences, not allowing the conveyance of a truly heterogeneous catalogue of news. The original ideal of the democratic electronic agora is undermined when private corporations control the flow of news and the infrastructure on which they are provided.<br />
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=== Historical Lineage ===<br />
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Modern form of this can be traced to Renaissance Europe,<sup>[[#fn2|[2]]]</sup> where a single innovation displaced established networks of collecting, processing and sharing news.The church, merchants, students, and diplomats were core participants in this ecosystem.<sup>[[#fn3|[3]]]</sup> The invention of printing in the 15th century was a seismic point in history as it offered new possibilities for the dissemination of information and therefore news. Initially, printing benefitted from the existing networks more than the networks benefitted from printing. This was the case until the networks were transformed in an unrecognisable manner (a trend we will see come to see throughout the history of the news. A clear instance of this is Johann Carolus's ''Relation aller Fürnemmen und gedenckwürdigen Historien'', a handwritten newspaper delivered weekly to the elite class of the time. The mode of production and the means of distribution were constrained by the available technology rather than strategy. The mode of production decreased the cost, time and later revolutionised the network as production could be localised and dependency on transporting was reduced.&nbsp;<br><br />
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One of the first paying customers for press was the Church, selling indulgences. During this era the Church and the State were in a clear symbiotic relationship, and drawing a separation between the two was difficult. Both actors deeply understood Beniger's principle that control depends on information processing and communication working together.<sup>[[#fn4|[4]]]&nbsp;</sup><sup>&nbsp;</sup>By introducing hurdles (such as the requirement of licensing the type of content that could be printed) and benefiting from the industrial might of this innovation, the Church and the state had effectively consolidated power and control. Interestingly, this contrasts what would take place generations later in the computing revolutions, where proximity to the state purposely unmentioned in order to appeal to the masses.<sup>[[#fn5|[5]]]</sup> <sup></sup><br />
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The next evolution of news took place when transmission was once again innovated with the radio. Radio’s reach could be decoupled from the cost, decreasing reliance on aging networks such as the now matured postal system. Control could be focused on content providers &nbsp;and who would be allowed broadcast rights. This changed the trajectory of news as a broadcaster could deliver news to anyone with a receiver dialed in to the relevant frequency. News outlets now had legitimate, diverse, alternative methods of production and distribution. The television followed not after, however it mostly followed the trajectory of the radio with the caveat that it dominated due to ability to generate commercial revenue through advertisement and optionality it provided.&nbsp;&nbsp;<br />
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=== Mechanism of Path Dependence ===<br />
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The public generally partakes in the consumption of content on social media. Hence, with its 3 billion monthly active users for example, Instagram has an installed base for news outlets to depend upon (Instagram Revenue and Usage Statistics (2026), n.d.). The audience of news outlets spends an increasing amount of their time on social media platforms, which results in a habitual entrenchment for these news outlets. In other words, the means of reaching the audience is dependent on the audience’s habits of content consumption. An indirect contractual entrenchment may also be speculated, as news outlets have obligations to their advertisers (who may request the upkeep of views/clicks on the news platforms they pay to advertise in). Cultural entrenchment should not be disregarded: the public expects to receive their news on social media platforms they readily frequent, and many news outlets meet this expectation. Hence, news outlets must partake in building a presence in social media platforms if they wish to compete.<br />
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=== Politics and Distribution ===<br />
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Barbook argues that although the California Ideology claims that state power will be decreased and individuals will be empowered through decentralized networks enabled by digital technologies, he demonstrates that public communication is in fact not immune to undemocratic powers. These include private corporations: these corporations may gatekeep in choosing when and how to provide access to their platforms, while finetuning how users navigate their platforms. By enabling access to content that users tend to agree with, those who manage these platforms enable public opinion to shift to extremes. Being “fed” the same narrative and not being challenged to see an opposing perspective ultimately provides fewer choices to the consumer of the information, the general public. Therefore, individual agency is constrained by platform architecture and control, not liberated by it.<br />
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=== Point Of No Return ===<br />
In examining the lineage of news and its eventual platform dependency, the diminishing returns of technological advancement for the industry become evident. Revenue has not been a particular focus of this article. The broadcast era was the era in which news outlets earned some of their largest revenues and were at their most independent. It was during this time that news outlets initiated the unbundling of one of their main revenue generators, the classified advertisement. By initiating this [https://stratechery.com/2017/the-great-unbundling/ unbundling] without any afterthought on capitalising on its timely advantages, news outlets entered their relationships with social media platforms in a weakened position. Searching for a saviour and giving the platform the credentials and reputation they needed in the early days in return. Reminiscent of the trend identified earlier. An example of a new's outlet that has navigated this journey with more diligence is [https://business.columbia.edu/insights/ai-transformative-tech/how-new-york-times-company-reinventing-itself-digital-age The New York Times].<br />
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=== Governance Implication & Proposition ===<br />
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It's clear that complete avoidance of these platforms on the part of news outlet is a Herculean request! New's outlets have flocked to these platforms due to their substantial audience and lock on audience. It's virtually impossible for a single organisation to mount a significant rebellion without self harming. A proposal is to approach the problem more as a herd and invest and cultivate more alternative open platforms for example [https://en.wikipedia.org/wiki/Bluesky Bluesky]&nbsp; and [https://joinmastodon.org Mastadon]. The benefit that these platforms bring about begin with not only optionality from the current dependencies but governance via protocol.<br />
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=== Footnotes ===<br />
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# <span id="fn1"></span>Mark Greengrass, Thierry Rentet and Stéphane Gal, ‘The Hinterland of the Newsletter: Handling Information in Space and Time’ in Joad Raymond and Noah Moxham (eds), News Networks in Early Modern Europe (Brill 2016) http://www.jstor.org/stable/10.1163/j.ctt1w8h1ng.34 accessed 7 September 2026; ‘Michel Serres Prononce En Sorbonne La Conférence Inaugurale Du Programme Paris Nouveaux Mondes - La Chancellerie Des Universités de Paris’ (La Chancellerie des Universités de Paris, 1 January 2013) https://www.sorbonne.fr/michel-serres-prononce-en-sorbonne-la-conference-inaugurale-du-programme-paris-nouveaux-mondes/ accessed 7 September 2026. James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986).<br />
# <span id="fn2"></span>Brendan Dooley, Making News in Renaissance Europe (1st edn, Cambridge University Press 2026) https://doi.org/10.1017/9781009358835.<br />
# <span id="fn3"></span>Andrew Pettegree, The Invention of News: How the World Came to Know about Itself (Yale University Press 2014). Helmer Helmers, ‘Public Diplomacy in Early Modern Europe: Towards a New History of News’ (2016) 22 Media History 401 https://doi.org/10.1080/13688804.2016.1174570.<br />
# <span id="fn4"></span>James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986) P24-25<br />
# <span id="fn5"></span>Richard Barbrook and Andy Cameron, The Californian Ideology (1996)<br><br />
#Richard Barbrook and Andy Cameron, The Californian Ideology (1996)<br />
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= Centralization of AI Compute and Data =<br />
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== Centralization of AI Compute and Data - by Sisi Hammoudi & Juliette Chamot ==<br />
=== Governance issue ===<br />
<span class="s8">Today, several path-dependence phenomena are emerging across advanced computing technologies. This assignment addresses one of them: the </span><span class="s8">centralisation</span><span class="s8"> of AI compute and data. Training and running frontier AI systems now depends on a handful of hyperscale providers, namely Amazon, Microsoft, Google, and Nvidia, which dominates the GPU market. In other words, near monopolies exist throughout the supply chain. This concentration creates a governance problem affecting public and private actors alike, both legally and institutionally. On the institutional side, it prevents public administrations, and states other than the US or China, from reaching sovereign AI capacity. It also raises competition-law concerns, since dominant market positions can prevent the market from delivering the best products at the best prices to consumers. Finally, AI developers, like states, are often forced into contracts with hyperscale providers, creating a structural dependence on them.</span><br />
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=== <span class="s8">Historical lineage</span> ===<br />
==== <span class="s8"><span class="s8">1945</span></span> ====<br />
<span class="s8"><span class="s8">Wartime scientific instruments should have been redirected to extend human command over knowledge, helping establish the postwar model of sustained federal funding for computing research (Vannevar Bush's, "As We May Think », 1945).</span></span><br />
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<span class="s8"><span class="s8"></span></span><br />
==== <span class="s8"><span class="s8">1990s</span></span> ====<br />
<span class="s8"><span class="s8">The privatisation of the NSFNET established the idea that critical digital infrastructure, even though publicly subsidised, could legitimately be privately owned. The EU Commission followed the US's lead, recommending privatisation and deregulation of telecommunications and media as the best way to build the "infobahn" though EU members could instead have chosen nationalisation of the infrastructure (Barbrook & Cameron, "The Californian Ideology," 1996).</span></span><br />
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<span class="s8"><span class="s8"></span></span><br />
==== <span class="s8"><span class="s8">2006</span></span> ====<br />
<span class="s8"><span class="s8"></span></span><div class="s13">Hyperscale cloud computing turned massive fixed capital investment in data centresinto a rentable service, favouring firms able to invest at scale.</div><br />
<div class="s13">Same period: Nvidia's proprietary CUDA software, released alongside its GPUs, became the de facto standard for machine learning, locking in a decade of tooling and expertise around one firm's hardware.</div><br />
<div class="s13"><br />
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==== <span class="s8"><span class="s8"><span class="s8"><span class="s8">From 2022</span></span></span></span> ====<br />
<span class="s8"><span class="s8"><span class="s8"><span class="s8"><span class="s8"><span class="s8">Semiconductor export controls and the CHIPS Act turned compute into an explicit instrument of geopolitical strategy.</span></span></span></span></span></span></div><br />
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<span class="s8"></span><br />
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=== <span class="s8">Mechanisms of path dependance</span><span class="s8"></span> ===<br />
<span class="s8"><span class="s8">Several mechanisms drive this </span><span class="s8">centralisation</span><span class="s8">, but path-dependence ones dominate. Because AI compute is a capital-intensive industry, new entrants struggle to compete with </span><span class="s8">hyperscalers</span><span class="s8"> that have already sunk huge sums into infrastructure, a barrier that produces monopoly-like situations. This dynamic, known as increasing returns, generates system-scale economies that harden into a near-irreversibility of investment (David, "Clio and the Economics of QWERTY," 1985). It overlaps with a second mechanism, </span><span class="s8">standardisation</span><span class="s8">, itself a form of technical interrelatedness: researchers' investment in Nvidia's CUDA-based tooling locks the field into that ecosystem regardless of whether better alternatives exist. A further mechanism is legal and contractual entrenchment. For example, Microsoft's stake in OpenAI binds developers to a specific provider by agreement rather than technical necessity.</span></span><br />
=== Politics and distribution ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">Technology does not have a history of distributing power equally. Rather, its development has strengthened the interests and authority of powerful groups that already possessed economic and political resource</span><span class="s8">s, and it is yet to be determined whether AI compute and data will follow suit</span><span class="s8">. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Author Langdon Winner illustrates </span><span class="s8">the historical con</span><span class="s8">s</span><span class="s8">traints of technological development</span><span class="s8"> with the case of New York from </span><span class="s8">the </span><span class="s8">1920s to the 1970s. He argued that the city’s roads, bridges, and parks’ physical arrangement contained “explicit and implicit political purpose</span><span class="s8">.</span><span class="s8">”</span><span class="s8"> </span><span class="s8">These infrastructures privileged wealthy and white communities while restricting poor and Black populations’ choice of mobility. Similarly, the development of industrial machinery increased productivity, simultaneously weakening union and non-union worker</span><span class="s8">s’</span><span class="s8"> bargaining power.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">In the twentieth century, f</span><span class="s8">ollowing the Industrial Revolution, a Control Revolution emerged from the increasing need to manage </span><span class="s8">expanding production, transportation, and information flows requiring strengthened organizational bureaucratic control.</span><span class="s8"> This was heavily shaped by the political context of post-World War II warfare.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Therefore, the bearer of the initial cost of technology is the person putting in the capital to erect it</span><span class="s8">,</span><span class="s8"> but ultimately, the person bearing the long-term cost of technology, whose choices diminish</span><span class="s8">,</span><span class="s8"> </span><span class="s8">is</span><span class="s8"> not the rich and privileged, but the everyday person subject to technologies. Forced to adapt, to reshape their professional skills to adapt to an environment trying to make them obsolete.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">AI compute and data </span><span class="s8">are</span><span class="s8"> at risk of creating the same effect. I</span><span class="s8">n their critique of dotcom neoliberalism</span><span class="s8">,</span><span class="s8"> authors Barbrook and Cameron exposed a similar socio-economic tension. The Californian Ideology claims digital technology empowers individuals</span><span class="s8">;</span><span class="s8"> however, perpetual unequal access to it creates </span><span class="s8">an apartheid between </span><span class="s8">“information-rich” and “information-poor” populations.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Finally, the development of AI compute and data depends on expensive and scar</span><span class="s8">c</span><span class="s8">e computing infrastructure and </span><span class="s8">a </span><span class="s8">highly concentrated semiconductor supply chain.</span><span class="s8"> Today, this is one of the most concentrated industries</span><span class="s8">,</span><span class="s8"> with single companies having near</span><span class="s8">-</span><span class="s8">total monopolies over the production of chips necessary </span><span class="s8">for</span><span class="s8"> the functioning of AI. This monopoly model threatens to reinforce the existing economic hierarchy.</span></p><br />
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<span class="s8"></span><br />
=== <span class="s8">Contingency and alternatives</span> ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">If a different technological trajectory was plausible, the most apt time for it to have occurred would be during the transition from the Industrial Revolution to </span><span class="s8">the </span><span class="s8">“Control Revolution”. When industrial production accelerated, our society experienced a “crisis of control”, creating opportunities to organize information and communication differently.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Instead of allowing control technologies to </span><span class="s8">be monopolized within businesses and states, our societies could have pursued a more democratic and decentralized system. Barbrook and Cameron provide such an alternative path through their idea of the “electronic agora</span><span class="s8">,</span><span class="s8">” where digital networks could encourage community participation </span><span class="s8">and </span><span class="s8">direct democracy</span><span class="s8">,</span><span class="s8"> where government could actively engage with the people to shape digital infrastructure and expand access.</span><span class="s8"> These alternatives did not actually prevail because corporat</span><span class="s8">e</span><span class="s8"> and state market participants possessed greater resources and authority to shape technological development at the end of the twentieth century. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Inherently, technological development is not predetermined</span><span class="s8">;</span><span class="s8"> it can support either authoritarian or democratic arrangements.</span><span class="s8"> Today, monopolies control chip production needed for AI compute and data, but other technologies like blockchain permit democratic participation.</span></p><br />
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<span class="s8"></span><br />
=== <span class="s8">Governance implication</span> ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">History always threatens to repeat itself. As Barbrook discussed, digital societies are shaped by the political context i</span><span class="s8">n</span><span class="s8"> </span><span class="s8">which</span><span class="s8"> </span><span class="s8">they develop</span><span class="s8">. It is a valid concern, then, that the development of information technology, through AI computing, would follow the same trajectory</span><span class="s8">-</span><span class="s8"> that is, be constrained to benefit the wealthy who funded its development, and ultimately harm the middle and lower classes enabling its functioning. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">However, AI’s place in our society has not yet crystallized. Technology governance does not have to adhere to this system. Such a seemingly sustainable approach to AI compute and data governance has already been broached. In 2022, the Notre Dame Journal on Emerging Technologies published an article in </span><span class="s8">its</span><span class="s8"> issue on Artificial Intelligence where the authors proposed an AI compute system based on a “dual investment strategy”</span><span class="s8">. Firstly, the model would be launched by “subsidizing and negotiating” cloud computing for </span><span class="s17">human </span><span class="s8">AI researchers through “existing” cloud vendors</span><span class="s8">,</span><span class="s8"> which would expand on existing AI compute initiatives. Secondly, the compute system would be specifically invested in as a public</span><span class="s8">ly</span><span class="s8"> owned infrastructure that would </span><span class="s8">b</span><span class="s8">e built</span><span class="s8"> and operate similarly to national libraries which own “academic supercomputing facilities”. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">The pilot program would have a “base level of compute access”</span><span class="s8"> which would keep costs of processing </span><span class="s8">down and</span><span class="s8"> enable it to meet the compute need</span><span class="s8">s</span><span class="s8"> of </span><span class="s8">a majority of</span><span class="s8"> academic researchers. Absent any strengthened legislation on the use of AI compute and data, the hardware would be accompanied by an AI ethics framework to enable sustainable technological governance. In addition to an ethical staff, the human resources needed to keep an AI compute model running would include data officers, scientists, data center and software engineers, research developers, </span><span class="s8">and </span><span class="s8">system administrators. These positions require specialized training, allowing new types of professional</span><span class="s8">s</span><span class="s8">, from any background</span><span class="s8">,</span><span class="s8"> to have access to professional prosperity in the field of AI. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">By implementing these frameworks, never neglecting the human element, and the economic and intellectual impact AI has on our society, we move from a historical determinist perspective to one acknowledging historical constraints and </span><span class="s8">learning</span><span class="s8"> from them.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8"></span></p><br />
<h3 class="s16 mwt-heading" style="text-align: justify;" ><span class="s8">Bibliography</span></h3><br />
<span class="s8"></span><div><div><p>[1] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 124, (1980)</p></div><div><p>[2] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 124, (1980)</p></div><div><p>[3] James R. Beniger, The Control Revolution: Technological and Economic Origins of the Information Society, Harvard University Press, p. 443, 450 (1986)</p></div><div><p>[4] Richard Barbrook, Andy Cameron, The Californian Ideology,&nbsp;''Science as Culture'',&nbsp;''6''(1), 44–72, 61 (1996)</p></div><div><p>[5] Anton Korinek, Jai Vipra, Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence, National Bureau of Economic Research, 10.3386/w33139, p. 11, 13-15 (2024)</p></div></div><div><div><p>[6] James R. Beniger, The Control Revolution: Technological and Economic Origins of the Information Society, Harvard University Press, p. 443, 442 (1986)</p></div><div><p>[7] Richard Barbrook, Andy Cameron, The Californian Ideology,&nbsp;''Science as Culture'',&nbsp;''6''(1), 44–72 (1996)</p></div><div><p>[8] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 130 (1980)</p></div><div><p>[9] Daniel E. Ho, Jennifer King, Russell C. Wald & Christopher Wan, The Centrality of Data and Compute for AI Innovation: A Blueprint for the National Research Cloud, 3 Notre Dame J. on Emerging Tech. 71, 81(2022)</p></div><div><p>[10] Daniel E. Ho, Jennifer King, Russell C. Wald & Christopher Wan, The Centrality of Data and Compute for AI Innovation: A Blueprint for the National Research Cloud, 3 Notre Dame J. on Emerging Tech. 71, 82 (2022)</p></div></div><br />
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== Centralization of AI compute and Data - by Atmika Dechamma & Pablo Latorre ==<br />
=== Governance Issue ===<br />
AI computing capacity and data presents the governance problem of an extreme concentration of technological infrastructure and information in a restricted number of companies that privately and globally dominate the market. This affects public and private actors - such as small and medium enterprises, potential new competitors, and Global South countries - that increasingly depend on AI systems outside their control and/or are deterred from competing with established companies because of impenetrable entry barriers - most notably initial investments and operational costs (1). The institutional and legal relevance of this is that it consolidates, reproduces and amplifies asymmetries of power in favor of the “Big Tech”, reverting the technological trend from digital decentralization to physical infrastructure dependency and curbing innovation and market efficiency.<br />
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=== Historical Lineage ===<br />
==== Limitation of Machine Learning ====<br />
<p style="text-align: justify;">The AI revolution was built on the limitation of human capabilities to process large information and derive efficient results - where before there existed only facilitative tools to allow for human-enabled processes, AI now offered derivations and cognitive reasoning in moments and at large scales.</p><br />
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==== Revert to Physical Infrastructure Dependency in the rush to be the best ====<br />
<p style="text-align: justify;">The present AI model heavily relies on hardware in order to perform complex data processing for deep learning. The data centre models followed require larger model sizes (which require higher resource, information and capital investment) to be able to yield better results. Due to the limitation of resources and a rush to establish the best working model of an AI agent, data centres are built on a rudimentary model heavily dependent on massive amounts of electricity and fresh water (2).</p><br />
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==== Regulation and Decentralization of Information ====<br />
<p style="text-align: justify;">Regulation and influence of sovereigns and institutions has resulted in data sharing and information exchange structurally through open source and cloud computing. But, while AI models claims their selling point to be accessibility for all, their information and derivations remain in a closed server, stored for the purpose of training their AI agents to be the best (3). Big AI contenders attract higher consumer and information flows overall resulting in a better developed AI model, proving disadvantageous in any market where early contenders have an advantage and accumulation of power.</p><br />
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=== Mechanisms of Path Dependence ===<br />
<p style="text-align: justify;">Early on in the industry there is an expectation of human and capital investment from all stakeholders involved, this high cost for entry into the market and expected capital to sustain and develop a model by both consumer and enterprise makes for a high switching cost. For the AI model to run and scale there is a presumption that the rate of growth is dependent on the size of data fed, resulting in a better model and hence, more consumer usage. A closed centralised data loop is created but the requirement for storage and processing far surpasses current infrastructures capabilities - heavily relying on early market entry advantage and sustained capital investments taking away from smaller aspirants and hoarding of power within closed circles. Despite its physical dependency, AI data processing has unique requirements beyond legacy infrastructures (4) - larger demand and production of GPUs and designed to handle immense thermal heat generated while consuming electricity beyond current capabilities.&nbsp;</p><br />
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<br><p style="text-align: justify;">The AI space largely remains unregulated due to its undefined form and fluid nature, however, this has given way for unethical and morality issues regarding data privacy, exploitation of labour and environmental harms.</p><br />
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=== Politics and Distribution ===<br />
Concentration strengthens the values, interests, capacities, and authority of the “Big Tech” over other actors of public and private nature. In this context, Barbrook and Cameron (5) illuminate the ethos behind AI technology development while Winner (6) makes observable the power relations surrounding it: concentration is the consequence of an AI development anchored in the belief that it must be free from all institutional and normative restriction since it is inherently liberating and non-political which, in turn, provides a political/moral justification for the concentration (if technology is inherently liberating and non-political then there is no power relations to observe or question) that translates itself into power dynamics where the AI developer not only owns the AI technology but also decides how it is trained and deployed and which models the user can or cannot access.<br />
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=== Contingency and Alternatives ===<br />
Concentration is due, first and foremost, to the fact that AI computing capacity requires massive and cutting-edge physical infrastructure - such as data centers and microprocessors - which, in turn, requires upfront investments that are unaffordable to most companies. In David’s (7) language, companies that could finance the infrastructure and position themselves first obtained self-reinforcing advantages and a “lock-in” effect in the market. In other words, concentration is the consequence of the development of AI physical infrastructure privately with no mixed or public alternatives as a public service. Therefore, there was a space for an alternative future at the end of the 1980s or the beginning of the 1990s when the privatization model of the technological infrastructure was consolidated in line with the “Californian Ideology”. In that moment governments had the chance to treat technological infrastructure as a mixed or public good rendering it universally accessible as it was the case of the Internet; this would have permitted companies of all sizes to profit from economies of scale, reducing entry barriers and fostering competition. However, this alternative path did not prevail since the Californian Ideology provided the moral/political justification to exclude governments from the development of technological infrastructure in the exact moment in which such a decision would produce structural consequences. If that path had been followed it could have contributed to collective access to economies of scale, lower entry barriers, and a more competitive AI market.<br />
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=== Governance Implication ===<br />
Considering the above, public or mixed investment on AI physical infrastructure is a necessary governance measure for market decentralization and collective access to AI computing capacity and data. From an historical perspective, the proposed measure is not merely a corrective action for a market failure but for a contingent and ideological decision made between the late 1980s and early 1990s that produced a structural “path dependence” that now is necessary to change.<br />
==== References ====<br />
(1) The Quiet Re-Centralization of Tech: Why AI Is Reversing 20 Years of Platform Decentralization. (2026, January 10). Retrieved on 8 September 2026, from Medium website : [https://medium.com/@sumitbhardwaj1357/the-quiet-re-centralization-of-tech-why-ai-is-reversing-20-years-of-platform-decentralization-ce15962b6a13 https://medium.com/@sumitbhardwaj1357/the-quiet-re-centralization-of-tech-why-ai-is-reversing-20-years-of-platform-decentralization-ce15962b6a13]<br />
<br />
(2) [https://www.mdpi.com/1996-1073/19/1/137 Ginzburg-Ganz, E., Lifshits, P., Machlev, R., Belikov, J., Krieger, Z., & Levron, Y. (2025). Technical challenges of AI data center integration into power grids—A survey. <em>Energies</em>, <em>19</em>(1), 137.]<br />
<br />
(3) [https://decai-resources.s3.us-east-1.amazonaws.com/decentralized_ML_perspective-16.pdf Singh, A., Lu, C., Gupta, G., Chopra, A., Blanc, J., Klinghoffer, T., ... & Raskar, R. (2024). A perspective on decentralizing AI.]<br />
<br />
(4) The Rise of AI Data Center Models and the Decline of the General-Purpose Data Center. (Circa 2026). Retrieved on 8 September 2026, from SubZero Engineering website : [https://www.subzeroeng.com/the-decline-of-the-general-purpose-data-center/ https://www.subzeroeng.com/the-decline-of-the-general-purpose-data-center/]<br />
<br />
(5) [https://git.xpub.nl/onebigear/SI_09_reference_library/raw/commit/22bf61e1dcfed35d58fba23808212bd00584be47/Richard_Barbrook_Andy_Cameron_Californian_ideology.pdf Barbrook, R., & Cameron, A. (1996). The Californian Ideology. <em>Science as Culture</em>, <em>6</em>(1), 44-72].<br />
<br />
(6) [https://d1wqtxts1xzle7.cloudfront.net/87708502/langdon_winner_do_artifacts_have_politics-libre.pdf?1655588533=&response-content-disposition=inline%3B+filename%3DDo_Artifacts_Have_Politics.pdf&Expires=1788890463&Signature=UBBiMqkip5MfYZbkbLNAN6aE2hyZdKkER-HFcmyxXkwIZuTnMKdOGoao8ddFr-rQ5T55A8NWUOlnZkGYmi66e7XR9h99DgTELMCrh48sXjOb8KYgA48r~SUUymt1IW~R~aOKJzitMIUHcrc6yEGKK1OuaA~mrEIVOXpUjQMYjqOd26Xmk9YJEglTkqaxeR47VCCth5FvozNQIowdfjzeu8aNHnI8V7Yur1IiXY~PGvYRcN6wBtcgpVMHZUtNaI8NjmYbp2p5TBYrPMF9MCLtvpGhPlsCfsvA8Bdm6XulGwRlksZBKWvVUQ8D~M8oLu12V39YaiETIObyJqbE7ctIcQ__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA Winner, L. (2017). Do artifacts have politics?. In <em>Computer ethics</em>(pp. 177-192). Routledge].<br />
<br />
(7) [https://sjbae.pbworks.com/f/David+1985.pdf David, P. A. (1985). Clio and the Economics of QWERTY. <em>The American economic review</em>, <em>75</em>(2), 332-337].<br />
<br />
== Centralization of AI compute and Data - by Sergey Abramov and Paul Stein ==<br />
<div><br />
=== The current governance issue ===<br />
<p>Advanced AI currently depends on a narrow group of tech giants<sup>1</sup> and semiconductor oligopolies controlling microchips and software, hyperscale cloud infrastructure, large datasets, frontier models, and distribution platforms. This presents a governance problem where this narrow group exercises control over foundational digital infrastructure. This directly affects consumers, businesses, and academia out of AI. Legally and institutionally, this matters because it creates a profound democratic deficit: this neutralizes antitrust frameworks designed for traditional markets, often bypassing conventional copyright and data privacy protections through unchecked data harvesting thereby complicating enforcement.This ultimately might affect national sovereignty as the countries that host the buildout will shape the future of AI: who controls it, what values it contains, how it is used<sup>2</sup>.</p><br />
<br><br />
=== Historical lineage ===<br />
<p>In 1987, Taiwan Semiconductor Manufacturing Company (TSMC) was founded, establishing the world’s first semiconductor fab. Instead of designing and making its own chips, TSMC only manufactured chips designed by other companies. Today, nearly 100% of the world's most advanced AI processors are manufactured by TSMC, leaving the entire global AI compute supply chain centralized under one company.</p><br />
<br><p>In 2006, Nvidia launched CUDA (Compute Unified Device Architecture), a free software layer that allowed developers to use Nvidia's graphics chips (GPUs) which later became perfect for training deep neural networks. Today, this creates a near-monopoly on AI compute hardware.</p><br />
<br><p>Soon after Amazon launched AWS, Microsoft and Google launched their own cloud platforms marking the structural pivot to the cloud service provider model, shifting computing from a distributed architecture (where companies bought and managed their own physical servers) to a centralized infrastructure. As training modern AI models requires tens of thousands of GPUs, today’s frontier AI companies are entirely dependent on the extremely expensive physical infrastructure of a handful of cloud hyper-scalers (Microsoft, Google, AWS, and Meta).</p><br />
<br><p>In 2009, Fei-Fei Li launched ImageNet, a massive database of over 14 million images, which proved that AI model performance scales directly with data volume. This created an immediate institutional advantage for consumer internet platforms (like Google and Meta), because they were already architected to collect, centralize, and store masses of user data through search engines and social networks, they possessed the unique data stack required to train high-performing AI.</p><br />
<br><br />
=== Mechanism of path dependence ===<br />
<p>The centralization of AI compute and data is a classic case of technological lock-in. When structural choices were made decades ago, they triggered powerful, self-reinforcing loops. One such loop is the switching costs and software standardisation. As developers have spent more than a decade working with CUDA, moving to a rival hardware provider (or a decentralized compute network) requires an enterprise to completely rewrite its foundational software stack. The cost of code migration, developer retraining, and potential hardware downtime force companies to stay tied to dominant hardware monopolies such as Nvidia. Commitments, licensing conditions, and exclusivity provisions add contractual costs. Fewer than 1% of cloud customers switch provider annually, identifying technical differentiation and data-transfer charges as important barriers<sup>4</sup>.</p><br />
<br><p>Network effects also matter for computing power. More customers generate more revenue, usage information, and opportunities to improve infrastructure and models. Better services attract additional users and developers, whose applications make the platform more valuable. In cloud–AI partnerships, providers may additionally obtain information about model performance and future infrastructure demand. These feedback loops strengthen firms already operating across cloud, models, software, and distribution.</p><br />
<br><br />
=== Politics and distribution ===<br />
<p>According to Langdon Winner's definition, modern AI computing infrastructure may qualify as an "inherently political technology" because its large scale and significant financial requirements not only lend themselves to, but necessitate,<sup>5</sup> centralized, hierarchical control. The physical siting of this infrastructure shows evidence of Winner’s second category of politicization of technologies, the ‘political arrangement’:<sup>6</sup> Of the five largest U.S. AI firms, four are headquartered in California,<sup>7</sup> while just one is (partially) domiciled in Texas. Texas, however, hosts twice the GPU clusters.<sup>8</sup> This placement geographically insulates beneficiaries of the data infrastructure boom from its negative externalities. The specific choice of location may itself be a deliberate preference on account of Texas’ unique approach to water usage rights.<sup>9</sup> Juxtaposition of this unequal and even exploitative balance of interests with the pontificating rhetoric of the urban, information rich, beneficiaries is evocative of the internal contradictions of the Californian Ideology - the virtual artisans existence and privileged position is still based on the exploitation of a vulnerable out-group, the "information-rich" consuming the output, the "information-poor" hosting the extraction.<sup>10</sup></p><br />
<br><br />
=== Contingency and Alternatives ===<br />
<p>Profit motive and economies of scale now concentrate investment among a few hyperscalers,<sup>11</sup> but this reflects policy choice, not government incapacity: Compute infrastructure may be inherently political, but the technology is agnostic as to where the organizing authority originates, and states have historically funded infrastructure of comparable or greater scale, while facing less pressure to show short-term returns. The clearest turning point was 1995, when the National Science Foundation retired NSFNET, the publicly funded backbone that had connected U.S. research and supercomputing centers since the mid-1980s,<sup>12</sup> handing internet infrastructure to commercial providers with no conditions attached. This was a deliberate policy decision made amid the deregulatory push of the Clinton era. The privatization that followed ushered in the private industrial dominance that persists today in the form of hyperscalers. Had a publicly governed backbone instead been scaled up, today's compute infrastructure might rest on a different foundation entirely.</p><br />
<br><br />
=== Governance implication ===<br />
<p>Despite private hyperscaler dominance, the U.S. does have a nominal public alternative: the National AI Research Resource (NAIRR), established following the National AI Initiative Act of 2020 and piloted from January 2024, which explicitly aims to democratize access to the computational resources essential to AI research.<sup>13</sup>In Europe, a comparable program is the EuroHPCJU,<sup>14</sup> an initiative intended to pool resources to build supercomputing capacity. The undertaking’s legislative basis has since been extended to include networked ‘AI factories', as well as the so-called “Gigafactories”.<sup>15</sup> The framing in language of sovereignty indicates intent to at least compete with private infrastructure initiatives. Though government-led measures cannot reverse the centralization of compute, they can democratize access - provided they are intensified. The European Commission has “set a goal of investing more than €1 billion per year in AI research and innovation”.<sup>16</sup> While laudable in its own right, it pales in comparison to the investments of industry leaders, which are approaching, if not exceeding, trillions of Dollars.</p><br />
<br />
=== References & Notes ===<br />
1.Amazon, Google, Meta, Microsoft, and Oracle collectively hold an estimated 71% of the world’s cumulative AI compute as of Q4 2025, measured in H100-equivalents of computing power.&nbsp;<p>Luke Emberson, Josh You and Venkat Somala (2026), "Five hyperscalers now own over two-thirds of global AI compute". Published online at epoch.ai. Retrieved from 'https://epoch.ai/data-insights/hyperscalers-control-most-compute' [online resource]. Accessed 7 Sept 2026.</p>2. Alasdair Phillips-Robins, Teddy Tawil and Sam Winter-Levy, ‘The Compute Coalition: How to Build the Future of AI in the Free World’ (Carnegie Endowment for International Peace, 8 June 2026) https://carnegieendowment.org/research/2026/06/the-compute-coalition-how-to-build-the-future-of-ai-in-the-free-world accessed 7 September 2026.<br />
<br />
3. Amazon Web Services (AWS), a cloud computing platform<br />
<br />
4.&nbsp;Competition and Markets Authority, Cloud Infrastructure Services: Final Decision Report (31 July 2025) https://assets.publishing.service.gov.uk/media/688b8891fdde2b8f73469544/final_decision_report.pdf accessed 7 September 2026.<br />
<br />
5. Langdon Winner, 'Do Artifacts Have Politics?' (1980) 109(1) ''Daedalus'' 121, 128.<br />
<br />
6. Ibid. 123.<br />
<br />
7. OpenAI, Anthropic, Google DeepMind, Meta AI. xAI is an exception to the rule, domiciled between Palo Alto, CA and San Antonio, TX.<br />
<br />
8. Texas’ 17 to California’s 8, cf. Texas Royalty Brokers, 'AI Clusters by State' (''Texas Royalty Brokers'', 2025) https://texasroyaltybrokers.com/ai-clusters-by-state/ accessed 7 September 2026.<br />
<br />
9. The ‘rule of capture’, established in Houston & TC Railway Co v East (Tex 1904), permits landowners to extract groundwater beneath their land without liability for depleting adjacent wells or aquifers, a doctrine now exploited by hyperscale AI data centres to draw large cooling-water volumes with minimal regulatory constraint.<br />
<br />
10. Richard Barbrook and Andy Cameron, 'The Californian Ideology' (1996) 6(1) ''Science as Culture'' 44.<br />
<br />
11. Goldman Sachs, 'Global AI Investment Is Forecast to Exceed $1 Trillion in 2026' (''Goldman Sachs Insights'', 7 August 2026) https://www.goldmansachs.com/insights/articles/global-investment-is-forecast-to-exceed-1-trillion-in-2026 accessed 7 September 2026.<br />
<br />
12. &nbsp;National Science Foundation, 'Birth of the Commercial Internet' (''NSF Impacts'') https://www.nsf.gov/impacts/internet accessed 7 September 2026.<br />
<br />
13. CASRAI, 'NAIRR: National AI Research Resource, Explained' (''CASRAI'') https://casrai.org/dictionary/term/national-ai-research-resource-nairr accessed 7 September 2026.<br />
<br />
14. Council Regulation (EU) 2021/1173 of 13 July 2021 on establishing the European High Performance Computing Joint Undertaking and repealing Regulation (EU) 2018/1488 [2021] OJ L256/1.<br />
<br />
15. Council Regulation (EU) 2026/150 of 16 January 2026 amending Regulation (EU) 2021/1173 on establishing the European High Performance Computing Joint Undertaking [2026] OJ L 2026/150.<br />
<br />
16.&nbsp;European Commission, 'Realising Europe's Digital Decade' (''European Commission'', 11 October 2024) https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/story-von-der-leyen-commission/realising-europes-digital-decade_en accessed 7 September 2026.</div></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Governance_by_history&diff=123776Governance by history2026-09-09T07:16:11Z<p>Isiklar Ceren: /* Platform Dependence in Public Communication (News) Ceren & Rodrigue */</p>
<hr />
<div>= [[Workplace surveillance]] =<br />
== [[Information Control and Workplace Surveillance - by Jihae Park and Mariona Fortuny Jané]] ==<br />
==== <span style="font-size: 12pt;">The Current Governance Issue</span> ====<br />
<span style="font-size: 10pt;">There are numerous current governance problems arising from technological innovations, yet here we will specifically focus on the information control and workplace surveillance. Whether intended or unintended, there were certain historical incidents which resulted in social and political consequences. As noticed from the Control Revolution, the dramatic evolution in mass media and telecommunications technologies has led to the reinforcement of the economic and political control during the Industrial Revolution. ([https://archive.org/details/beniger-james-the-control-revolution Beniger, 1986]) By applying this logic to a modern example, this is clearly how many corporations are getting in control of their employees through surveillance technologies. Along with the emergence of remote and hybrid work after Covid-19, employers are now relying on “bossware” to analyze the emails, chats, and messages of their employees on platforms such as Teams or Slack. ([https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/view/19100/13263 Ollier-Malaterre et al., 2026, p.237]) Some companies have strict restrictions on transferring data both internally and externally in protection of confidential information and consistently monitor their workers to the certain extent which could slow down their efficiency. This is problematic as it’s not only violating the privacy of their employees but also depriving employees of rights they should be naturally be able to exercise.</span><br />
<br />
<span style="font-size: 12pt;"></span><br />
<br />
==== <span style="font-size: 12pt;">Historical Lineage</span> ====<br />
<span style="font-size: 12pt;"><span style="font-size: 10pt;">In relation to the current issue of the information control and workplace surveillance, Max Weber’s argument of bureaucracy and rationalization in the middle and late nineteenth century are good historical examples which are still frequently visible nowadays. Weber stated how the range of control could extend not only by expanding the capability to process information but also by limiting the amount of information to be processed. Here, the former is directly related to the control implemented by bureaucratization (in the mid 19th century) and computerization (in the late 20th century), whereas the latter addresses rationalization. An example from bureaucracy is the expansion of paperwork in response to the growth in information. We can still note these traces of bureaucracy from numerous procedures that we have to go through for a decision-making to take place in corporations. He brings up the example of standardized time zones for rationalization which is simply an example for an omission or a breakdown of information to facilitate its processing. ([https://archive.org/details/beniger-james-the-control-revolution Beniger, 1986, p.15-16]) This is also commonly seen from nowadays as some companies may use internal terminologies for the sake of both confidentiality and efficiency.</span></span><br />
<br />
==== <span style="font-size: 12pt;">Mechanism of Path Dependence</span> ====<br />
<p>Following along the line with the historical lineage, there are certain mechanisms at work of path dependence for information control and workplace surveillance. Bureaucracy is closely related with organizational routines. Many companies have already settled down with a fixed workflow and decision-making process, which makes it more costly for one to change from its conventional way of working. This means switching costs from an old system to a new one is clearly high considering its time and capital, not necessarily will guarantee increasing returns. Hence, many firms end up maintaining its old strategy, reluctant to make any modifications or changes.<br></p><br />
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==== <span style="font-size: 12pt;">Politics and Distribution</span> ====<br />
<br />
As businesses grew too large for managers to oversee everything directly, companies replaced human judgment with formal rule-systems, as we see explained by Beniger's 'intellectual technology' ([https://archive.org/details/beniger-james-the-control-revolution/page/65/mode/2up Beniger, 1986, pp. 17, 21]). Algorithmic management continues this: a call once made by a supervisor's judgment is now a rule built into software that runs without one, extending a logic Beniger traces as far back as to Taylorism and the so called 'assembly line'. Winner ([https://www.jstor.org/stable/20024652 1980]) asks whether such systems must concentrate power this way or were driven there, when other designs were equally possible; nothing required shutting workers out of the decision, so leaving them out was a political choice, and not necessarily a technical necessity. Barbrook and Cameron ([https://doi.org/10.1080/09505439609526455 1996]) explain the reasoning why some can defend this 'domination': they show how 1990s tech culture sold new technologies as freedom even as it tightened control, so the rhetoric could become one of closer oversight as flexibility and autonomy. Together, authority accrues to employers, who in some systems can set and revise these oversight rules unilaterally and face less resistance because the arrangement is framed as freedom; workers bear the cost, losing the informal give-and-take they had with a human supervisor for oversight that is harder to see, question, or contest, while being told it grants them more freedom, not less.<br />
<br />
==== <span style="font-size: 12pt;">Contingency and Alternatives</span> ====<br />
<br />
A plausible alternative happened on U.S. post WWII: in some workplaces, labor and its pacing was demanded to be set through collective bargaining and enforced jointly, by both management and union stewards monitoring compliance on the line ([https://doi.org/10.1093/icc/dtaf038 Breznitz et al., 2025, p. 211]). So, in this context, workplace surveillance could have developed as a bargained, dual-administered practice rather than a management monopoly. The 1950 [https://en.wikipedia.org/wiki/Reuther%27s_Treaty_of_Detroit Reuther's Treaty of Detroit ] cut that possibility off: unions won guaranteed wages and benefits in exchange for surrendering any general claim over how work was supervised ([https://doi.org/10.1093/icc/dtaf038 Breznitz et al., 2025, pp. 210–211]). Workers depended on wages to survive, and employers controlled the wage relationship. That asymmetry meant employers, given their position of power, were able to arrange things so that, at the very least, workers would have far less capacity to sustain a fight over control itself. Thus, the "trade" wasn't a fair exchange between equals. This reflects which side could afford to hold out on which issue. Hypothetically speaking, had that joint administration model prevailed instead, this could have greatly impacted norms internationally and good practices with worker-union agreed surveillance would have become a widely accepted standard practice.<br />
<br />
==== <span style="font-size: 12pt;">Governance Implication</span> ====<br />
<br />
An interesting proposition for present-day governance that wants to fill a gap in workplace surveillance is what [https://doi.org/10.1016/j.digbus.2025.100120 Kayas, Ong and Belal (2025)] are proposing: They argue that EU law, through the [https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng GDPR] and its required [https://en.wikipedia.org/wiki/Data_protection_impact_assessment data protection impact assessments (DPIAs)], already offers meaningful protection for workers in terms of lawful high-risk data collection and data processing. Nevertheless, these DPIAs are built around data and privacy, so they leave out several dimensions of monitoring itself: its purpose, how intrusive it is, how visible it is to the people being watched, and its effects on workers' autonomy, trust, and standing relative to management. These authors propose a "surveillance impact assessment" scoring a system against these characteristics directly, before any surveillance system is put in place. Although this mechanism "is constrained by its reliance on existing literature and the lack of empirical validation," it feels like a genuine alternative for two reasons: 1. it targets the actual mechanism at issue, and 2. at the same time it builds upon a mechanism of active participatory approach where employees have a direct say in how surveillance is designed ([https://doi.org/10.1016/j.digbus.2025.100120 Kayas et al., 2025, p. 11]), which, combined with the actual assessment, would put workers' own judgment at the centre of the one decision that affects them. It's important to note that this alternative is proposed as worth piloting, not as a proven fix, and it is fair to ask whether another mandatory assessment stacked on top of DPIAs would function as intended or simply read to workers as more compliance paperwork.<br />
<br />
==== References ====<br />
<br>Barbrook, R., & Cameron, A. (1996). The Californian Ideology. ''Science as Culture'', 6(1), 44–72. [https://doi.org/10.1080/09505439609526455 https://doi.org/10.1080/09505439609526455]<br>Beniger, J. R. (1986). ''The Control Revolution: Technological and Economic Origins of the Information Society''. Harvard University Press. [https://archive.org/details/beniger-james-the-control-revolution https://archive.org/details/beniger-james-the-control-revolution]&nbsp;<br>Breznitz, D., Levy, K., Lipartito, K., & Zehavi, A. (2025). An equity-focused research agenda for workplace surveillance. ''Industrial and Corporate Change'', 35(1), 206–221. [https://doi.org/10.1093/icc/dtaf038 https://doi.org/10.1093/icc/dtaf038]<br>Kayas, O. G., Ong, C. E., & Belal, H. M. (2025). From humans to algorithms: A sociotechnical framework of workplace surveillance. ''Digital Business'', 5, 100120. [https://doi.org/10.1016/j.digbus.2025.100120 https://doi.org/10.1016/j.digbus.2025.100120]<br>Ollier-Malaterre, A., Parent-Rocheleau, X., Benkrid, K., & Provost Savard, Y. (2026). Making Sense of Workplace Surveillance: How Workers and Union Representatives Experience, Imagine, and Resist Surveillance Exposure. ''Surveillance & Society'', 24(3), 236–254. [https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/view/19100/13263 https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/view/19100/13263]<br>Winner, L. (1980). Do Artifacts Have Politics? ''Daedalus'', 109(1), 121–136. [https://www.jstor.org/stable/20024652 https://www.jstor.org/stable/20024652]<br />
<br />
<br><br />
<br />
== [[Algorithmic management and workplace surveillance - by Sebastián Muller and Kate Davey'''&nbsp;''']] ==<br />
<br />
<br />
<br />
<br />
<br />
=== 1. The current issue. ===<br />
<br><p>Algorithmic management and workplace surveillance can be defined as the use of computer-programmed procedures to coordinate labor input in an organization ([https://joint-research-centre.ec.europa.eu/scientific-activities/employment/algorithmic-management-and-digital-monitoring-work_en 1]). Simply put, it is a way to control workers, and workers generally have no say in how the system that tracks them is created. As Winner says "different people are differently situated and possess unequal degrees of power as well as unequal levels of awareness" ([https://www.jstor.org/stable/20024652?seq=7 2]).</p><br />
<p>The population affected is workers; both “white collar” and “blue collar” workers are impacted. Whether it’s Amazon tracking warehouse workers’ “Time Off Task” with handheld scanners ([https://www.wired.com/story/amazon-worker-tracking-details-revealed 3]) or Meta employees having their every click tracked ([https://www.techpolicy.press/metas-worker-surveillance-tests-eu-rules-on-ai-and-labor/ 4]) to train AI, employers have the power to watch and control their employees in an unprecedented way.</p><br />
<p>It matters legally because workers have very few rights to fight back against these surveillance programs; even the The Electronic Communications Privacy Act of 1986 allows exceptions to surveillance of employees ([https://bja.ojp.gov/program/it/privacy-civil-liberties/authorities/statutes/1285 5]).<br></p><br />
<br />
=== <br>2. Historical lineage. ===<br />
<p><br>2.1 Panopticon: it is an architectural apparatus developed by Jeremy Bentham in 1791. The design of this building effectively generated the sense of constant monitoring, which in turn motivated the prisoners to behave as if they were being watched at all times. As human labor became commodified, capitalists began implementing measures to ensure the maximization of productivity, including the replication of this design ([https://doi.org/10.14452/MR-070-09-2019-02_2 6]). While unused today, the panopticon is widely considered as both a theoretical and practical inspiration of other forms of surveillance in the workplace.</p><br />
<p><br></p><br />
<p>2.2 Scientific management: this theory attempts to analyze and standardize workflows to improve labor productivity. Frederick Winslow Taylor, its main pioneer, used early forms of data analysis during the XX century to decrease walking distances, eliminating unnecessary movements and preventing deliberate slow-walking among workers. ([https://doi.org/10.14452/MR-070-09-2019-02_2 7]). There are many modern forms of data-driven decision-making processes in the workforce. For instance, Amazon warehouses track individual workers' scan rates in real time through handheld scanners, generating data feeds to track and evaluate performance ([https://www.theverge.com/2019/4/25/18516004/amazon-warehouse-fulfillment-centers-productivity-firing-terminations 8]).</p><br />
<p><br></p><br />
<p>2.3 PC in the workplace: John Blankenbaker designed the first commercially available personal computer in 1971 ([https://www.computerhistory.org/revolution/personal-computers/17/297 9]), however, it wasn’t until the mid-1980s that the use of personal computers in the workplace became an industry standard. This achievement gave rise to the digital monitoring of work, which in turn allowed employers to monitor employees in real-time, effectively replacing the human eye with a more efficient surveillance mechanism. This represents one of the key aspects of modern-day workplace monitoring.<br><br></p><br />
<p><br></p><br />
<br />
=== 3. Mechanism of path dependence. ===<br />
'''<br>'''When analyzing the historic lineage of work surveillance, it is possible to point out two main path dependencies mechanisms in place.<p>Firstly, it is clear that many of the technological developments that arose through these events have one major goal, which is to increase wealth within a hierarchical ecosystem. Employers resort to several mechanisms to maximize profits and cut inefficiencies at the expense of workers.&nbsp;</p><br />
<p>In addition, standardization can also be singled out as a key mechanism at play. Once one corporation implements any of these developments (such as the digital monitoring of the workplace), the market incentives would force the rest to do the same in order to be profitable and remain competitive.</p><br />
<br />
=== 4. Politics and distribution. ===<br />
<br>One simple answer to this question would be that capitalists implement and leverage these mechanisms to increase their wealth while the working class remains powerless and unable to withdraw itself from the system in force.&nbsp;<p>However, if we resort to Winner's framework, we see that the technical elements of these technologies are not intrinsically capitalist, since workplace surveillance can also be observed in alternative regimes (including chattel slavery and the Soviet regime). It seems that, rather than being exclusively tied to capitalistic values, the methods in question respond to strong hierarchical structures.</p><br />
<p>In addition, even under a libertarian framework, structural inequalities are still present, allowing a privileged class to enjoy individual freedoms while segregated groups keep performing low-income jobs ([https://www.metamute.org/editorial/articles/californian-ideology 10]), arguably still subject to surveillance. Thus, not only are these technologies compatible with hierarchical top-down forms of government, but also with structures that allow such hierarchies to form without state intervention.</p><br />
<p>That said, this form of management seems less compatible with democratic societies, which tend not only to value individual liberties but to turn them into enforceable rights (including workers' privacy, health and integrity), thus establishing boundaries for workplace surveillance. This could explain why studies of American business leaders have found them unhappy with democratic scruples ([https://www.jstor.org/stable/20024652 11]).</p><br />
<p><br></p><br />
<br />
=== 5. Contingency and alternatives. ===<br />
<p><br></p><br />
<p>Bush writes about the memex, a machine that could extend a person’s memory and that the memory would belong to the person who owned it. As Bush expands, “For mature thought there is no mechanical substitute" ([https://dl.acm.org/doi/pdf/10.1145/227181.227186 12]). His idea was that a machine could take over the repetitive nature of someone’s job, while the person could record their own thoughts for their own use. Bush’s memex was never created, but the idea inspired products like Microsoft’s Productivity Score that were made for employers (the buyers) not for the person whose memory it used (the worker).</p><br />
<p>This immediately brings to mind Meta's Model Capability Initiative, which was done to train AI agents the company hopes to sell to other employers as well as watch their employees ([https://www.reuters.com/sustainability/boards-policy-regulation/meta-start-capturing-employee-mouse-movements-keystrokes-ai-training-data-2026-04-21/ 13]). If this was Bush’s memex, it would belong to the employee using it, not Meta.&nbsp;</p><br />
<br />
<br />
=== 6. Governance implication.<br> ===<br />
Democratic oversight of the use of algorithms as a form of surveillance is essential to ensure that workers’ rights are not overstepped in the name of efficiency. As such we propose: all workers should have a legal right to be consulted and approve a surveillance program before a company installs and uses it. A tracking system should be a group decision, not an inevitable, unilateral one. While the United States has very little protections for workers in terms of surveillance, the EU leads the way with the GDPR, specifically Article 22 ([http://data.europa.eu/eli/reg/2016/679/oj 14]), and the AI Act Article 5 ([http://data.europa.eu/eli/reg/2024/1689/oj 15]). It’s also worth noting that in December 2026, the Platform Work Directive ([https://eur-lex.europa.eu/eli/dir/2024/2831/oj/eng 16]) will come into effect which will ban automated termination.<br />
<br />
== [[Platform Dependence in Public Communication (News)]] Ceren & Rodrigue ==<br />
<br />
Public communication is the conveyance of a message to a large group of people. This includes public announcements, advertisements in public spaces, social media broadcasts, news delivered in reporting, editorials, opinion pieces, and even political campaigns. Platform dependence is the reliance on a third party platform or digital infrastructure to reach the audience of the public communication, the public. Platform dependence in public communication therefore includes reliance on private companies like Meta (Facebook), state television channels, or telecommunications providers who provide and control access to, and develop the infrastructure of such platforms. For the purpose of this exercise, news will be utilized as the main example of public communication. It is very difficult to discuss news without highlighting the deep entanglement it shares with with information. For our purpose 'information' will have the the following characteristics; it can be learned, processed, archived, and it's worth correlates to its rarity.<sup>[[#fn1|[1]]]</sup> News is the end result of the process of taking this information from one form to another, and transmitting to a wider, typically public audience is what we will anchor our definition of 'news' to be. <br />
<br />
Those who are affected by platform dependence in public communication are the communicators and the public alike. News outlets are mainly for-profit organizations. These organizations’ reliance on third party digital platforms grows day-by-day to maintain their popularity and engagement ultimately deciding the revenue generated from advertisers. The public on the other hand are provided catchier and more diluted information, gaining just enough knowledge to grab their attention while not being provided substantial knowledge on matters. Additionally, members of the public who do not have the resources to access such platforms and digital services remain “information poor”.&nbsp;<sup>6</sup> Digital rich, the virtual class of tech-professional and entrepreneurs benefit from the dependence to their platforms.<br />
<br />
This is crucial as platform dependence may threaten democracy and free political expression. Platforms, run by private parties, can be run according to their political beliefs. Social media platforms aiming to keep users online utilize algorithms that provide their users with their confirmed preferences, not allowing the conveyance of a truly heterogeneous catalogue of news. The original ideal of the democratic electronic agora is undermined when private corporations control the flow of news and the infrastructure on which they are provided.<br />
<br />
=== Historical Lineage ===<br />
<br />
Modern form of this can be traced to Renaissance Europe,<sup>[[#fn2|[2]]]</sup> where a single innovation displaced established networks of collecting, processing and sharing news.The church, merchants, students, and diplomats were core participants in this ecosystem.<sup>[[#fn3|[3]]]</sup> The invention of printing in the 15th century was a seismic point in history as it offered new possibilities for the dissemination of information and therefore news. Initially, printing benefitted from the existing networks more than the networks benefitted from printing. This was the case until the networks were transformed in an unrecognisable manner (a trend we will see come to see throughout the history of the news. A clear instance of this is Johann Carolus's ''Relation aller Fürnemmen und gedenckwürdigen Historien'', a handwritten newspaper delivered weekly to the elite class of the time. The mode of production and the means of distribution were constrained by the available technology rather than strategy. The mode of production decreased the cost, time and later revolutionised the network as production could be localised and dependency on transporting was reduced.&nbsp;<br><br />
<br />
<br />
One of the first paying customers for press was the Church, selling indulgences. During this era the Church and the State were in a clear symbiotic relationship, and drawing a separation between the two was difficult. Both actors deeply understood Beniger's principle that control depends on information processing and communication working together.<sup>[[#fn4|[4]]]&nbsp;</sup><sup>&nbsp;</sup>By introducing hurdles (such as the requirement of licensing the type of content that could be printed) and benefiting from the industrial might of this innovation, the Church and the state had effectively consolidated power and control. Interestingly, this contrasts what would take place generations later in the computing revolutions, where proximity to the state purposely unmentioned in order to appeal to the masses.<sup>[[#fn5|[5]]]</sup> <sup></sup><br />
<br />
<br />
The next evolution of news takes place when transmission is once again innovated with the radio. With radio reach could reach could be decoupled from cost, reliance on aging networks such as the now matured postal system. Control was could now be on content and move closer to physics on licensing who could be broadcast rights. This changed the trajectory of new's as it birth the state broadcaster, responsible for broadcasting news to anyone with a receiver on the appropriate frequency. News outlet now had legitimate diverse alternative methods of production and distribution. The television followed not after, however it mostly followed the trajectory of the radio with the caveat that it dominated due to ability to generate commercial revenue through advertisement and optionality it provided.&nbsp;&nbsp;<br />
<br />
=== Mechanism of Path Dependence ===<br />
<br />
The public is generally partakes in the consumption of content on social media. Hence, with its 3 billion monthly active users for example, Instagram has an installed base for news outlets to depend upon (Instagram Revenue and Usage Statistics (2026), n.d.). The audiences of news outlets spend an increasing amount of their time on social media platforms, which gives results in a habitual entrenchment for these news outlets: the means of reaching the audience is dependent on their habits of content consumption. An indirect contractual entrenchment may also be discussed, as news outlets have obligations to their advertisers (who may request the upkeep of views/clicks on the news platforms they pay to advertise in). Cultural entrenchment should not be disregarded: the public expects to receive their news on social media platforms they readily frequent, and many news outlets meet this expectation. Hence, news outlets must partake in building a presence in social media platforms if they wish to compete.<br />
<br />
=== Politics and Distribution ===<br />
<br />
Barbook argues that although the California Ideology claims that state power will be decreased and individuals will be empowered through decentralized networks enabled by digital technologies, he demonstrates that public communication is in fact not immune to undemocratic powers. These include private corporations: these corporations may gatekeep in choosing when and how to provide access to their platforms, while finetuning how users navigate their platforms. By enabling access to content that users tend to agree with, those who manage these platforms enable public opinion to shift to extremes. Being “fed” the same narrative and not being challenged to see an opposing perspective ultimately provides fewer choices to the consumer of the information, the general public. Therefore, individual agency is constrained by platform architecture and control, not liberated by it.<br />
<br />
=== Point Of No Return ===<br />
In examining the lineage of news and its eventual platform dependency, the diminishing returns of technological advancement for the industry become evident. Revenue has not been a particular focus of this article. The broadcast era was the era in which news outlets earned some of their largest revenues and were at their most independent. It was during this time that news outlets initiated the unbundling of one of their main revenue generators, the classified advertisement. By initiating this [https://stratechery.com/2017/the-great-unbundling/ unbundling] without any afterthought on capitalising on its timely advantages, news outlets entered their relationships with social media platforms in a weakened position. Searching for a saviour and giving the platform the credentials and reputation they needed in the early days in return. Reminiscent of the trend identified earlier. An example of a new's outlet that has navigated this journey with more diligence is [https://business.columbia.edu/insights/ai-transformative-tech/how-new-york-times-company-reinventing-itself-digital-age The New York Times].<br />
<br />
=== Governance Implication & Proposition ===<br />
<br />
It's clear that complete avoidance of these platforms on the part of news outlet is a Heculean request! New's outlets have flocked to these platforms due to their substantial audience and lock on audience. It's virtually impossible for a single organisation to mount a significant rebellion without self harming. A proposal is to approach the problem more as a herd and invest and cultivate more alternative open platforms for example [https://en.wikipedia.org/wiki/Bluesky Bluesky]&nbsp; and [https://joinmastodon.org Mastadon]. The benefit that these platforms bring about begin with not only optionality from the current dependencies but governance via protocol.<br />
<br />
=== Footnotes ===<br />
<br />
# <span id="fn1"></span>Mark Greengrass, Thierry Rentet and Stéphane Gal, ‘The Hinterland of the Newsletter: Handling Information in Space and Time’ in Joad Raymond and Noah Moxham (eds), News Networks in Early Modern Europe (Brill 2016) http://www.jstor.org/stable/10.1163/j.ctt1w8h1ng.34 accessed 7 September 2026; ‘Michel Serres Prononce En Sorbonne La Conférence Inaugurale Du Programme Paris Nouveaux Mondes - La Chancellerie Des Universités de Paris’ (La Chancellerie des Universités de Paris, 1 January 2013) https://www.sorbonne.fr/michel-serres-prononce-en-sorbonne-la-conference-inaugurale-du-programme-paris-nouveaux-mondes/ accessed 7 September 2026. James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986).<br />
# <span id="fn2"></span>Brendan Dooley, Making News in Renaissance Europe (1st edn, Cambridge University Press 2026) https://doi.org/10.1017/9781009358835.<br />
# <span id="fn3"></span>Andrew Pettegree, The Invention of News: How the World Came to Know about Itself (Yale University Press 2014). Helmer Helmers, ‘Public Diplomacy in Early Modern Europe: Towards a New History of News’ (2016) 22 Media History 401 https://doi.org/10.1080/13688804.2016.1174570.<br />
# <span id="fn4"></span>James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986) P24-25<br />
# <span id="fn5"></span>Richard Barbrook and Andy Cameron, The Californian Ideology (1996)<br><br />
#Richard Barbrook and Andy Cameron, The Californian Ideology (1996)<br />
<br />
= Centralization of AI Compute and Data =<br />
<br />
== Centralization of AI Compute and Data - by Sisi Hammoudi & Juliette Chamot ==<br />
=== Governance issue ===<br />
<span class="s8">Today, several path-dependence phenomena are emerging across advanced computing technologies. This assignment addresses one of them: the </span><span class="s8">centralisation</span><span class="s8"> of AI compute and data. Training and running frontier AI systems now depends on a handful of hyperscale providers, namely Amazon, Microsoft, Google, and Nvidia, which dominates the GPU market. In other words, near monopolies exist throughout the supply chain. This concentration creates a governance problem affecting public and private actors alike, both legally and institutionally. On the institutional side, it prevents public administrations, and states other than the US or China, from reaching sovereign AI capacity. It also raises competition-law concerns, since dominant market positions can prevent the market from delivering the best products at the best prices to consumers. Finally, AI developers, like states, are often forced into contracts with hyperscale providers, creating a structural dependence on them.</span><br />
<br />
<span class="s8"></span><br />
=== <span class="s8">Historical lineage</span> ===<br />
==== <span class="s8"><span class="s8">1945</span></span> ====<br />
<span class="s8"><span class="s8">Wartime scientific instruments should have been redirected to extend human command over knowledge, helping establish the postwar model of sustained federal funding for computing research (Vannevar Bush's, "As We May Think », 1945).</span></span><br />
<br />
<span class="s8"><span class="s8"></span></span><br />
==== <span class="s8"><span class="s8">1990s</span></span> ====<br />
<span class="s8"><span class="s8">The privatisation of the NSFNET established the idea that critical digital infrastructure, even though publicly subsidised, could legitimately be privately owned. The EU Commission followed the US's lead, recommending privatisation and deregulation of telecommunications and media as the best way to build the "infobahn" though EU members could instead have chosen nationalisation of the infrastructure (Barbrook & Cameron, "The Californian Ideology," 1996).</span></span><br />
<br />
<span class="s8"><span class="s8"></span></span><br />
==== <span class="s8"><span class="s8">2006</span></span> ====<br />
<span class="s8"><span class="s8"></span></span><div class="s13">Hyperscale cloud computing turned massive fixed capital investment in data centresinto a rentable service, favouring firms able to invest at scale.</div><br />
<div class="s13">Same period: Nvidia's proprietary CUDA software, released alongside its GPUs, became the de facto standard for machine learning, locking in a decade of tooling and expertise around one firm's hardware.</div><br />
<div class="s13"><br />
<br />
==== <span class="s8"><span class="s8"><span class="s8"><span class="s8">From 2022</span></span></span></span> ====<br />
<span class="s8"><span class="s8"><span class="s8"><span class="s8"><span class="s8"><span class="s8">Semiconductor export controls and the CHIPS Act turned compute into an explicit instrument of geopolitical strategy.</span></span></span></span></span></span></div><br />
<br />
<span class="s8"></span><br />
<br />
=== <span class="s8">Mechanisms of path dependance</span><span class="s8"></span> ===<br />
<span class="s8"><span class="s8">Several mechanisms drive this </span><span class="s8">centralisation</span><span class="s8">, but path-dependence ones dominate. Because AI compute is a capital-intensive industry, new entrants struggle to compete with </span><span class="s8">hyperscalers</span><span class="s8"> that have already sunk huge sums into infrastructure, a barrier that produces monopoly-like situations. This dynamic, known as increasing returns, generates system-scale economies that harden into a near-irreversibility of investment (David, "Clio and the Economics of QWERTY," 1985). It overlaps with a second mechanism, </span><span class="s8">standardisation</span><span class="s8">, itself a form of technical interrelatedness: researchers' investment in Nvidia's CUDA-based tooling locks the field into that ecosystem regardless of whether better alternatives exist. A further mechanism is legal and contractual entrenchment. For example, Microsoft's stake in OpenAI binds developers to a specific provider by agreement rather than technical necessity.</span></span><br />
=== Politics and distribution ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">Technology does not have a history of distributing power equally. Rather, its development has strengthened the interests and authority of powerful groups that already possessed economic and political resource</span><span class="s8">s, and it is yet to be determined whether AI compute and data will follow suit</span><span class="s8">. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Author Langdon Winner illustrates </span><span class="s8">the historical con</span><span class="s8">s</span><span class="s8">traints of technological development</span><span class="s8"> with the case of New York from </span><span class="s8">the </span><span class="s8">1920s to the 1970s. He argued that the city’s roads, bridges, and parks’ physical arrangement contained “explicit and implicit political purpose</span><span class="s8">.</span><span class="s8">”</span><span class="s8"> </span><span class="s8">These infrastructures privileged wealthy and white communities while restricting poor and Black populations’ choice of mobility. Similarly, the development of industrial machinery increased productivity, simultaneously weakening union and non-union worker</span><span class="s8">s’</span><span class="s8"> bargaining power.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">In the twentieth century, f</span><span class="s8">ollowing the Industrial Revolution, a Control Revolution emerged from the increasing need to manage </span><span class="s8">expanding production, transportation, and information flows requiring strengthened organizational bureaucratic control.</span><span class="s8"> This was heavily shaped by the political context of post-World War II warfare.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Therefore, the bearer of the initial cost of technology is the person putting in the capital to erect it</span><span class="s8">,</span><span class="s8"> but ultimately, the person bearing the long-term cost of technology, whose choices diminish</span><span class="s8">,</span><span class="s8"> </span><span class="s8">is</span><span class="s8"> not the rich and privileged, but the everyday person subject to technologies. Forced to adapt, to reshape their professional skills to adapt to an environment trying to make them obsolete.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">AI compute and data </span><span class="s8">are</span><span class="s8"> at risk of creating the same effect. I</span><span class="s8">n their critique of dotcom neoliberalism</span><span class="s8">,</span><span class="s8"> authors Barbrook and Cameron exposed a similar socio-economic tension. The Californian Ideology claims digital technology empowers individuals</span><span class="s8">;</span><span class="s8"> however, perpetual unequal access to it creates </span><span class="s8">an apartheid between </span><span class="s8">“information-rich” and “information-poor” populations.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Finally, the development of AI compute and data depends on expensive and scar</span><span class="s8">c</span><span class="s8">e computing infrastructure and </span><span class="s8">a </span><span class="s8">highly concentrated semiconductor supply chain.</span><span class="s8"> Today, this is one of the most concentrated industries</span><span class="s8">,</span><span class="s8"> with single companies having near</span><span class="s8">-</span><span class="s8">total monopolies over the production of chips necessary </span><span class="s8">for</span><span class="s8"> the functioning of AI. This monopoly model threatens to reinforce the existing economic hierarchy.</span></p><br />
<br />
<span class="s8"></span><br />
=== <span class="s8">Contingency and alternatives</span> ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">If a different technological trajectory was plausible, the most apt time for it to have occurred would be during the transition from the Industrial Revolution to </span><span class="s8">the </span><span class="s8">“Control Revolution”. When industrial production accelerated, our society experienced a “crisis of control”, creating opportunities to organize information and communication differently.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Instead of allowing control technologies to </span><span class="s8">be monopolized within businesses and states, our societies could have pursued a more democratic and decentralized system. Barbrook and Cameron provide such an alternative path through their idea of the “electronic agora</span><span class="s8">,</span><span class="s8">” where digital networks could encourage community participation </span><span class="s8">and </span><span class="s8">direct democracy</span><span class="s8">,</span><span class="s8"> where government could actively engage with the people to shape digital infrastructure and expand access.</span><span class="s8"> These alternatives did not actually prevail because corporat</span><span class="s8">e</span><span class="s8"> and state market participants possessed greater resources and authority to shape technological development at the end of the twentieth century. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Inherently, technological development is not predetermined</span><span class="s8">;</span><span class="s8"> it can support either authoritarian or democratic arrangements.</span><span class="s8"> Today, monopolies control chip production needed for AI compute and data, but other technologies like blockchain permit democratic participation.</span></p><br />
<br />
<span class="s8"></span><br />
=== <span class="s8">Governance implication</span> ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">History always threatens to repeat itself. As Barbrook discussed, digital societies are shaped by the political context i</span><span class="s8">n</span><span class="s8"> </span><span class="s8">which</span><span class="s8"> </span><span class="s8">they develop</span><span class="s8">. It is a valid concern, then, that the development of information technology, through AI computing, would follow the same trajectory</span><span class="s8">-</span><span class="s8"> that is, be constrained to benefit the wealthy who funded its development, and ultimately harm the middle and lower classes enabling its functioning. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">However, AI’s place in our society has not yet crystallized. Technology governance does not have to adhere to this system. Such a seemingly sustainable approach to AI compute and data governance has already been broached. In 2022, the Notre Dame Journal on Emerging Technologies published an article in </span><span class="s8">its</span><span class="s8"> issue on Artificial Intelligence where the authors proposed an AI compute system based on a “dual investment strategy”</span><span class="s8">. Firstly, the model would be launched by “subsidizing and negotiating” cloud computing for </span><span class="s17">human </span><span class="s8">AI researchers through “existing” cloud vendors</span><span class="s8">,</span><span class="s8"> which would expand on existing AI compute initiatives. Secondly, the compute system would be specifically invested in as a public</span><span class="s8">ly</span><span class="s8"> owned infrastructure that would </span><span class="s8">b</span><span class="s8">e built</span><span class="s8"> and operate similarly to national libraries which own “academic supercomputing facilities”. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">The pilot program would have a “base level of compute access”</span><span class="s8"> which would keep costs of processing </span><span class="s8">down and</span><span class="s8"> enable it to meet the compute need</span><span class="s8">s</span><span class="s8"> of </span><span class="s8">a majority of</span><span class="s8"> academic researchers. Absent any strengthened legislation on the use of AI compute and data, the hardware would be accompanied by an AI ethics framework to enable sustainable technological governance. In addition to an ethical staff, the human resources needed to keep an AI compute model running would include data officers, scientists, data center and software engineers, research developers, </span><span class="s8">and </span><span class="s8">system administrators. These positions require specialized training, allowing new types of professional</span><span class="s8">s</span><span class="s8">, from any background</span><span class="s8">,</span><span class="s8"> to have access to professional prosperity in the field of AI. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">By implementing these frameworks, never neglecting the human element, and the economic and intellectual impact AI has on our society, we move from a historical determinist perspective to one acknowledging historical constraints and </span><span class="s8">learning</span><span class="s8"> from them.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8"></span></p><br />
<h3 class="s16 mwt-heading" style="text-align: justify;" ><span class="s8">Bibliography</span></h3><br />
<span class="s8"></span><div><div><p>[1] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 124, (1980)</p></div><div><p>[2] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 124, (1980)</p></div><div><p>[3] James R. Beniger, The Control Revolution: Technological and Economic Origins of the Information Society, Harvard University Press, p. 443, 450 (1986)</p></div><div><p>[4] Richard Barbrook, Andy Cameron, The Californian Ideology,&nbsp;''Science as Culture'',&nbsp;''6''(1), 44–72, 61 (1996)</p></div><div><p>[5] Anton Korinek, Jai Vipra, Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence, National Bureau of Economic Research, 10.3386/w33139, p. 11, 13-15 (2024)</p></div></div><div><div><p>[6] James R. Beniger, The Control Revolution: Technological and Economic Origins of the Information Society, Harvard University Press, p. 443, 442 (1986)</p></div><div><p>[7] Richard Barbrook, Andy Cameron, The Californian Ideology,&nbsp;''Science as Culture'',&nbsp;''6''(1), 44–72 (1996)</p></div><div><p>[8] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 130 (1980)</p></div><div><p>[9] Daniel E. Ho, Jennifer King, Russell C. Wald & Christopher Wan, The Centrality of Data and Compute for AI Innovation: A Blueprint for the National Research Cloud, 3 Notre Dame J. on Emerging Tech. 71, 81(2022)</p></div><div><p>[10] Daniel E. Ho, Jennifer King, Russell C. Wald & Christopher Wan, The Centrality of Data and Compute for AI Innovation: A Blueprint for the National Research Cloud, 3 Notre Dame J. on Emerging Tech. 71, 82 (2022)</p></div></div><br />
<br />
== Centralization of AI compute and Data - by Atmika Dechamma & Pablo Latorre ==<br />
=== Governance Issue ===<br />
AI computing capacity and data presents the governance problem of an extreme concentration of technological infrastructure and information in a restricted number of companies that privately and globally dominate the market. This affects public and private actors - such as small and medium enterprises, potential new competitors, and Global South countries - that increasingly depend on AI systems outside their control and/or are deterred from competing with established companies because of impenetrable entry barriers - most notably initial investments and operational costs (1). The institutional and legal relevance of this is that it consolidates, reproduces and amplifies asymmetries of power in favor of the “Big Tech”, reverting the technological trend from digital decentralization to physical infrastructure dependency and curbing innovation and market efficiency.<br />
<br />
=== Historical Lineage ===<br />
==== Limitation of Machine Learning ====<br />
<p style="text-align: justify;">The AI revolution was built on the limitation of human capabilities to process large information and derive efficient results - where before there existed only facilitative tools to allow for human-enabled processes, AI now offered derivations and cognitive reasoning in moments and at large scales.</p><br />
<br />
<br><br />
==== Revert to Physical Infrastructure Dependency in the rush to be the best ====<br />
<p style="text-align: justify;">The present AI model heavily relies on hardware in order to perform complex data processing for deep learning. The data centre models followed require larger model sizes (which require higher resource, information and capital investment) to be able to yield better results. Due to the limitation of resources and a rush to establish the best working model of an AI agent, data centres are built on a rudimentary model heavily dependent on massive amounts of electricity and fresh water (2).</p><br />
<br />
<br><br />
==== Regulation and Decentralization of Information ====<br />
<p style="text-align: justify;">Regulation and influence of sovereigns and institutions has resulted in data sharing and information exchange structurally through open source and cloud computing. But, while AI models claims their selling point to be accessibility for all, their information and derivations remain in a closed server, stored for the purpose of training their AI agents to be the best (3). Big AI contenders attract higher consumer and information flows overall resulting in a better developed AI model, proving disadvantageous in any market where early contenders have an advantage and accumulation of power.</p><br />
<br />
=== Mechanisms of Path Dependence ===<br />
<p style="text-align: justify;">Early on in the industry there is an expectation of human and capital investment from all stakeholders involved, this high cost for entry into the market and expected capital to sustain and develop a model by both consumer and enterprise makes for a high switching cost. For the AI model to run and scale there is a presumption that the rate of growth is dependent on the size of data fed, resulting in a better model and hence, more consumer usage. A closed centralised data loop is created but the requirement for storage and processing far surpasses current infrastructures capabilities - heavily relying on early market entry advantage and sustained capital investments taking away from smaller aspirants and hoarding of power within closed circles. Despite its physical dependency, AI data processing has unique requirements beyond legacy infrastructures (4) - larger demand and production of GPUs and designed to handle immense thermal heat generated while consuming electricity beyond current capabilities.&nbsp;</p><br />
<br />
<br><p style="text-align: justify;">The AI space largely remains unregulated due to its undefined form and fluid nature, however, this has given way for unethical and morality issues regarding data privacy, exploitation of labour and environmental harms.</p><br />
<br />
=== Politics and Distribution ===<br />
Concentration strengthens the values, interests, capacities, and authority of the “Big Tech” over other actors of public and private nature. In this context, Barbrook and Cameron (5) illuminate the ethos behind AI technology development while Winner (6) makes observable the power relations surrounding it: concentration is the consequence of an AI development anchored in the belief that it must be free from all institutional and normative restriction since it is inherently liberating and non-political which, in turn, provides a political/moral justification for the concentration (if technology is inherently liberating and non-political then there is no power relations to observe or question) that translates itself into power dynamics where the AI developer not only owns the AI technology but also decides how it is trained and deployed and which models the user can or cannot access.<br />
<br />
=== Contingency and Alternatives ===<br />
Concentration is due, first and foremost, to the fact that AI computing capacity requires massive and cutting-edge physical infrastructure - such as data centers and microprocessors - which, in turn, requires upfront investments that are unaffordable to most companies. In David’s (7) language, companies that could finance the infrastructure and position themselves first obtained self-reinforcing advantages and a “lock-in” effect in the market. In other words, concentration is the consequence of the development of AI physical infrastructure privately with no mixed or public alternatives as a public service. Therefore, there was a space for an alternative future at the end of the 1980s or the beginning of the 1990s when the privatization model of the technological infrastructure was consolidated in line with the “Californian Ideology”. In that moment governments had the chance to treat technological infrastructure as a mixed or public good rendering it universally accessible as it was the case of the Internet; this would have permitted companies of all sizes to profit from economies of scale, reducing entry barriers and fostering competition. However, this alternative path did not prevail since the Californian Ideology provided the moral/political justification to exclude governments from the development of technological infrastructure in the exact moment in which such a decision would produce structural consequences. If that path had been followed it could have contributed to collective access to economies of scale, lower entry barriers, and a more competitive AI market.<br />
<br />
=== Governance Implication ===<br />
Considering the above, public or mixed investment on AI physical infrastructure is a necessary governance measure for market decentralization and collective access to AI computing capacity and data. From an historical perspective, the proposed measure is not merely a corrective action for a market failure but for a contingent and ideological decision made between the late 1980s and early 1990s that produced a structural “path dependence” that now is necessary to change.<br />
==== References ====<br />
(1) The Quiet Re-Centralization of Tech: Why AI Is Reversing 20 Years of Platform Decentralization. (2026, January 10). Retrieved on 8 September 2026, from Medium website : [https://medium.com/@sumitbhardwaj1357/the-quiet-re-centralization-of-tech-why-ai-is-reversing-20-years-of-platform-decentralization-ce15962b6a13 https://medium.com/@sumitbhardwaj1357/the-quiet-re-centralization-of-tech-why-ai-is-reversing-20-years-of-platform-decentralization-ce15962b6a13]<br />
<br />
(2) [https://www.mdpi.com/1996-1073/19/1/137 Ginzburg-Ganz, E., Lifshits, P., Machlev, R., Belikov, J., Krieger, Z., & Levron, Y. (2025). Technical challenges of AI data center integration into power grids—A survey. <em>Energies</em>, <em>19</em>(1), 137.]<br />
<br />
(3) [https://decai-resources.s3.us-east-1.amazonaws.com/decentralized_ML_perspective-16.pdf Singh, A., Lu, C., Gupta, G., Chopra, A., Blanc, J., Klinghoffer, T., ... & Raskar, R. (2024). A perspective on decentralizing AI.]<br />
<br />
(4) The Rise of AI Data Center Models and the Decline of the General-Purpose Data Center. (Circa 2026). Retrieved on 8 September 2026, from SubZero Engineering website : [https://www.subzeroeng.com/the-decline-of-the-general-purpose-data-center/ https://www.subzeroeng.com/the-decline-of-the-general-purpose-data-center/]<br />
<br />
(5) [https://git.xpub.nl/onebigear/SI_09_reference_library/raw/commit/22bf61e1dcfed35d58fba23808212bd00584be47/Richard_Barbrook_Andy_Cameron_Californian_ideology.pdf Barbrook, R., & Cameron, A. (1996). The Californian Ideology. <em>Science as Culture</em>, <em>6</em>(1), 44-72].<br />
<br />
(6) [https://d1wqtxts1xzle7.cloudfront.net/87708502/langdon_winner_do_artifacts_have_politics-libre.pdf?1655588533=&response-content-disposition=inline%3B+filename%3DDo_Artifacts_Have_Politics.pdf&Expires=1788890463&Signature=UBBiMqkip5MfYZbkbLNAN6aE2hyZdKkER-HFcmyxXkwIZuTnMKdOGoao8ddFr-rQ5T55A8NWUOlnZkGYmi66e7XR9h99DgTELMCrh48sXjOb8KYgA48r~SUUymt1IW~R~aOKJzitMIUHcrc6yEGKK1OuaA~mrEIVOXpUjQMYjqOd26Xmk9YJEglTkqaxeR47VCCth5FvozNQIowdfjzeu8aNHnI8V7Yur1IiXY~PGvYRcN6wBtcgpVMHZUtNaI8NjmYbp2p5TBYrPMF9MCLtvpGhPlsCfsvA8Bdm6XulGwRlksZBKWvVUQ8D~M8oLu12V39YaiETIObyJqbE7ctIcQ__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA Winner, L. (2017). Do artifacts have politics?. In <em>Computer ethics</em>(pp. 177-192). Routledge].<br />
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(7) [https://sjbae.pbworks.com/f/David+1985.pdf David, P. A. (1985). Clio and the Economics of QWERTY. <em>The American economic review</em>, <em>75</em>(2), 332-337].<br />
<br />
== Centralization of AI compute and Data - by Sergey Abramov and Paul Stein ==<br />
<div><br />
=== The current governance issue ===<br />
<p>Advanced AI currently depends on a narrow group of tech giants<sup>1</sup> and semiconductor oligopolies controlling microchips and software, hyperscale cloud infrastructure, large datasets, frontier models, and distribution platforms. This presents a governance problem where this narrow group exercises control over foundational digital infrastructure. This directly affects consumers, businesses, and academia out of AI. Legally and institutionally, this matters because it creates a profound democratic deficit: this neutralizes antitrust frameworks designed for traditional markets, often bypassing conventional copyright and data privacy protections through unchecked data harvesting thereby complicating enforcement.This ultimately might affect national sovereignty as the countries that host the buildout will shape the future of AI: who controls it, what values it contains, how it is used<sup>2</sup>.</p><br />
<br><br />
=== Historical lineage ===<br />
<p>In 1987, Taiwan Semiconductor Manufacturing Company (TSMC) was founded, establishing the world’s first semiconductor fab. Instead of designing and making its own chips, TSMC only manufactured chips designed by other companies. Today, nearly 100% of the world's most advanced AI processors are manufactured by TSMC, leaving the entire global AI compute supply chain centralized under one company.</p><br />
<br><p>In 2006, Nvidia launched CUDA (Compute Unified Device Architecture), a free software layer that allowed developers to use Nvidia's graphics chips (GPUs) which later became perfect for training deep neural networks. Today, this creates a near-monopoly on AI compute hardware.</p><br />
<br><p>Soon after Amazon launched AWS, Microsoft and Google launched their own cloud platforms marking the structural pivot to the cloud service provider model, shifting computing from a distributed architecture (where companies bought and managed their own physical servers) to a centralized infrastructure. As training modern AI models requires tens of thousands of GPUs, today’s frontier AI companies are entirely dependent on the extremely expensive physical infrastructure of a handful of cloud hyper-scalers (Microsoft, Google, AWS, and Meta).</p><br />
<br><p>In 2009, Fei-Fei Li launched ImageNet, a massive database of over 14 million images, which proved that AI model performance scales directly with data volume. This created an immediate institutional advantage for consumer internet platforms (like Google and Meta), because they were already architected to collect, centralize, and store masses of user data through search engines and social networks, they possessed the unique data stack required to train high-performing AI.</p><br />
<br><br />
=== Mechanism of path dependence ===<br />
<p>The centralization of AI compute and data is a classic case of technological lock-in. When structural choices were made decades ago, they triggered powerful, self-reinforcing loops. One such loop is the switching costs and software standardisation. As developers have spent more than a decade working with CUDA, moving to a rival hardware provider (or a decentralized compute network) requires an enterprise to completely rewrite its foundational software stack. The cost of code migration, developer retraining, and potential hardware downtime force companies to stay tied to dominant hardware monopolies such as Nvidia. Commitments, licensing conditions, and exclusivity provisions add contractual costs. Fewer than 1% of cloud customers switch provider annually, identifying technical differentiation and data-transfer charges as important barriers<sup>4</sup>.</p><br />
<br><p>Network effects also matter for computing power. More customers generate more revenue, usage information, and opportunities to improve infrastructure and models. Better services attract additional users and developers, whose applications make the platform more valuable. In cloud–AI partnerships, providers may additionally obtain information about model performance and future infrastructure demand. These feedback loops strengthen firms already operating across cloud, models, software, and distribution.</p><br />
<br><br />
=== Politics and distribution ===<br />
<p>According to Langdon Winner's definition, modern AI computing infrastructure may qualify as an "inherently political technology" because its large scale and significant financial requirements not only lend themselves to, but necessitate,<sup>5</sup> centralized, hierarchical control. The physical siting of this infrastructure shows evidence of Winner’s second category of politicization of technologies, the ‘political arrangement’:<sup>6</sup> Of the five largest U.S. AI firms, four are headquartered in California,<sup>7</sup> while just one is (partially) domiciled in Texas. Texas, however, hosts twice the GPU clusters.<sup>8</sup> This placement geographically insulates beneficiaries of the data infrastructure boom from its negative externalities. The specific choice of location may itself be a deliberate preference on account of Texas’ unique approach to water usage rights.<sup>9</sup> Juxtaposition of this unequal and even exploitative balance of interests with the pontificating rhetoric of the urban, information rich, beneficiaries is evocative of the internal contradictions of the Californian Ideology - the virtual artisans existence and privileged position is still based on the exploitation of a vulnerable out-group, the "information-rich" consuming the output, the "information-poor" hosting the extraction.<sup>10</sup></p><br />
<br><br />
=== Contingency and Alternatives ===<br />
<p>Profit motive and economies of scale now concentrate investment among a few hyperscalers,<sup>11</sup> but this reflects policy choice, not government incapacity: Compute infrastructure may be inherently political, but the technology is agnostic as to where the organizing authority originates, and states have historically funded infrastructure of comparable or greater scale, while facing less pressure to show short-term returns. The clearest turning point was 1995, when the National Science Foundation retired NSFNET, the publicly funded backbone that had connected U.S. research and supercomputing centers since the mid-1980s,<sup>12</sup> handing internet infrastructure to commercial providers with no conditions attached. This was a deliberate policy decision made amid the deregulatory push of the Clinton era. The privatization that followed ushered in the private industrial dominance that persists today in the form of hyperscalers. Had a publicly governed backbone instead been scaled up, today's compute infrastructure might rest on a different foundation entirely.</p><br />
<br><br />
=== Governance implication ===<br />
<p>Despite private hyperscaler dominance, the U.S. does have a nominal public alternative: the National AI Research Resource (NAIRR), established following the National AI Initiative Act of 2020 and piloted from January 2024, which explicitly aims to democratize access to the computational resources essential to AI research.<sup>13</sup>In Europe, a comparable program is the EuroHPCJU,<sup>14</sup> an initiative intended to pool resources to build supercomputing capacity. The undertaking’s legislative basis has since been extended to include networked ‘AI factories', as well as the so-called “Gigafactories”.<sup>15</sup> The framing in language of sovereignty indicates intent to at least compete with private infrastructure initiatives. Though government-led measures cannot reverse the centralization of compute, they can democratize access - provided they are intensified. The European Commission has “set a goal of investing more than €1 billion per year in AI research and innovation”.<sup>16</sup> While laudable in its own right, it pales in comparison to the investments of industry leaders, which are approaching, if not exceeding, trillions of Dollars.</p><br />
<br />
=== References & Notes ===<br />
1.Amazon, Google, Meta, Microsoft, and Oracle collectively hold an estimated 71% of the world’s cumulative AI compute as of Q4 2025, measured in H100-equivalents of computing power.&nbsp;<p>Luke Emberson, Josh You and Venkat Somala (2026), "Five hyperscalers now own over two-thirds of global AI compute". Published online at epoch.ai. Retrieved from 'https://epoch.ai/data-insights/hyperscalers-control-most-compute' [online resource]. Accessed 7 Sept 2026.</p>2. Alasdair Phillips-Robins, Teddy Tawil and Sam Winter-Levy, ‘The Compute Coalition: How to Build the Future of AI in the Free World’ (Carnegie Endowment for International Peace, 8 June 2026) https://carnegieendowment.org/research/2026/06/the-compute-coalition-how-to-build-the-future-of-ai-in-the-free-world accessed 7 September 2026.<br />
<br />
3. Amazon Web Services (AWS), a cloud computing platform<br />
<br />
4.&nbsp;Competition and Markets Authority, Cloud Infrastructure Services: Final Decision Report (31 July 2025) https://assets.publishing.service.gov.uk/media/688b8891fdde2b8f73469544/final_decision_report.pdf accessed 7 September 2026.<br />
<br />
5. Langdon Winner, 'Do Artifacts Have Politics?' (1980) 109(1) ''Daedalus'' 121, 128.<br />
<br />
6. Ibid. 123.<br />
<br />
7. OpenAI, Anthropic, Google DeepMind, Meta AI. xAI is an exception to the rule, domiciled between Palo Alto, CA and San Antonio, TX.<br />
<br />
8. Texas’ 17 to California’s 8, cf. Texas Royalty Brokers, 'AI Clusters by State' (''Texas Royalty Brokers'', 2025) https://texasroyaltybrokers.com/ai-clusters-by-state/ accessed 7 September 2026.<br />
<br />
9. The ‘rule of capture’, established in Houston & TC Railway Co v East (Tex 1904), permits landowners to extract groundwater beneath their land without liability for depleting adjacent wells or aquifers, a doctrine now exploited by hyperscale AI data centres to draw large cooling-water volumes with minimal regulatory constraint.<br />
<br />
10. Richard Barbrook and Andy Cameron, 'The Californian Ideology' (1996) 6(1) ''Science as Culture'' 44.<br />
<br />
11. Goldman Sachs, 'Global AI Investment Is Forecast to Exceed $1 Trillion in 2026' (''Goldman Sachs Insights'', 7 August 2026) https://www.goldmansachs.com/insights/articles/global-investment-is-forecast-to-exceed-1-trillion-in-2026 accessed 7 September 2026.<br />
<br />
12. &nbsp;National Science Foundation, 'Birth of the Commercial Internet' (''NSF Impacts'') https://www.nsf.gov/impacts/internet accessed 7 September 2026.<br />
<br />
13. CASRAI, 'NAIRR: National AI Research Resource, Explained' (''CASRAI'') https://casrai.org/dictionary/term/national-ai-research-resource-nairr accessed 7 September 2026.<br />
<br />
14. Council Regulation (EU) 2021/1173 of 13 July 2021 on establishing the European High Performance Computing Joint Undertaking and repealing Regulation (EU) 2018/1488 [2021] OJ L256/1.<br />
<br />
15. Council Regulation (EU) 2026/150 of 16 January 2026 amending Regulation (EU) 2021/1173 on establishing the European High Performance Computing Joint Undertaking [2026] OJ L 2026/150.<br />
<br />
16.&nbsp;European Commission, 'Realising Europe's Digital Decade' (''European Commission'', 11 October 2024) https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/story-von-der-leyen-commission/realising-europes-digital-decade_en accessed 7 September 2026.</div></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Governance_by_history&diff=123738Governance by history2026-09-08T21:48:58Z<p>Isiklar Ceren: /* Platform Dependence in Public Communication (News) Ceren & Rodrigue */</p>
<hr />
<div>= [[Workplace surveillance]] =<br />
== Information Control and Workplace Surveillance - by Jihae Park and Mariona Fortuny Jané ==<br />
=== <span style="font-size: 12pt;" >1. The current Governance issue</span> ===<br />
=== <span style="font-size: 12pt;" >2. Historical lineage</span> ===<br />
=== <span style="font-size: 12pt;" >3. Mechanism of path dependence</span> ===<br />
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==== <span style="font-size: 12pt;" >4. Politics and distribution.</span> ====<br />
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As businesses grew too large for managers to oversee everything directly, companies replaced human judgment with formal rule-systems, as we see explained by Beniger's 'intellectual technology' (Beniger, 1986, pp. 17, 21). Algorithmic management continues this: a call once made by a supervisor's judgment is now a rule built into software that runs without one, extending a logic Beniger traces as far back as to Taylorism and the so called 'assembly line'. Winner ([https://www.jstor.org/stable/20024652 1980]) asks whether such systems must concentrate power this way or were driven there, when other designs were equally possible; nothing required shutting workers out of the decision, so leaving them out was a political choice, and not necessarily a technical necessity. Barbrook and Cameron ([https://doi.org/10.1080/09505439609526455 1996]) explain the reasoning why some can defend this 'domination': they show how 1990s tech culture sold new technologies as freedom even as it tightened control, so the rhetoric could become one of closer oversight as flexibility and autonomy. Together, authority accrues to employers, who in some systems can set and revise these oversight rules unilaterally and face less resistance because the arrangement is framed as freedom; workers bear the cost, losing the informal give-and-take they had with a human supervisor for oversight that is harder to see, question, or contest, while being told it grants them more freedom, not less.<br />
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==== <span style="font-size: 12pt;" >5. Contingency and alternatives.</span> ====<br />
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A plausible alternative happened on U.S. post WWII: in some workplaces, labor and its pacing was demanded to be set through collective bargaining and enforced jointly, by both management and union stewards monitoring compliance on the line ([https://doi.org/10.1093/icc/dtaf038 Breznitz et al., 2025, p. 211]). So, in this context, workplace surveillance could have developed as a bargained, dual-administered practice rather than a management monopoly. The 1950 "Treaty of Detroit" cut that possibility off: unions won guaranteed wages and benefits in exchange for surrendering any general claim over how work was supervised ([https://doi.org/10.1093/icc/dtaf038 Breznitz et al., 2025, pp. 210–211]). Workers depended on wages to survive, and employers controlled the wage relationship. That asymmetry meant employers, given their position of power, were able to arrange things so that, at the very least, workers would have far less capacity to sustain a fight over control itself. Thus, the "trade" wasn't a fair exchange between equals. This reflects which side could afford to hold out on which issue. Hypothetically speaking, had that joint administration model prevailed instead, this could have greatly impacted norms internationally and good practices with worker-union agreed surveillance would have become a widely accepted standard practice.<br />
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==== <span style="font-size: 12pt;" >6. Governance implication.</span> ====<br />
<br />
An interesting proposition for present-day governance that wants to fill a gap in workplace surveillance is what [https://doi.org/10.1016/j.digbus.2025.100120 Kayas, Ong and Belal (2025)] are proposing: They argue that EU law, through the GDPR and its required data protection impact assessments (DPIAs), already offers meaningful protection for workers in terms of lawful high-risk data collection and data processing. Nevertheless, these DPIAs are built around data and privacy, so they leave out several dimensions of monitoring itself: its purpose, how intrusive it is, how visible it is to the people being watched, and its effects on workers' autonomy, trust, and standing relative to management. These authors propose a "surveillance impact assessment" scoring a system against these characteristics directly, before any surveillance system is put in place. Although this mechanism "is constrained by its reliance on existing literature and the lack of empirical validation," it feels like a genuine alternative for two reasons: 1. it targets the actual mechanism at issue, and 2. at the same time it builds upon a mechanism of active participatory approach where employees have a direct say in how surveillance is designed ([https://doi.org/10.1016/j.digbus.2025.100120 Kayas et al., 2025, p. 11]), which, combined with the actual assessment, would put workers' own judgment at the centre of the one decision that affects them. It's important to note that this alternative is proposed as worth piloting, not as a proven fix, and it is fair to ask whether another mandatory assessment stacked on top of DPIAs would function as intended or simply read to workers as more compliance paperwork.<br />
<br />
==== References ====<br>* Barbrook, R., & Cameron, A. (1996). The Californian Ideology. ''Science as Culture'', 6(1), 44–72. [https://doi.org/10.1080/09505439609526455 https://doi.org/10.1080/09505439609526455]<br>* Beniger, J. R. (1986). ''The Control Revolution: Technological and Economic Origins of the Information Society''. Harvard University Press.<br>* Breznitz, D., Levy, K., Lipartito, K., & Zehavi, A. (2025). An equity-focused research agenda for workplace surveillance. ''Industrial and Corporate Change'', 35(1), 206–221. [https://doi.org/10.1093/icc/dtaf038 https://doi.org/10.1093/icc/dtaf038]<br>* Kayas, O. G., Ong, C. E., & Belal, H. M. (2025). From humans to algorithms: A sociotechnical framework of workplace surveillance. ''Digital Business'', 5, 100120. [https://doi.org/10.1016/j.digbus.2025.100120 https://doi.org/10.1016/j.digbus.2025.100120]<br>* Winner, L. (1980). Do Artifacts Have Politics? ''Daedalus'', 109(1), 121–136. [https://www.jstor.org/stable/20024652 https://www.jstor.org/stable/20024652]<br />
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<br><br />
<br />
== [[Algorithmic management and workplace surveillance - by Sebastián Muller and Kate Davey'''&nbsp;''']] ==<br />
<br />
<br />
<br />
<br />
<br />
=== 1. The current issue. ===<br />
<br><p>Algorithmic management and workplace surveillance can be defined as the use of computer-programmed procedures to coordinate labor input in an organization ([https://joint-research-centre.ec.europa.eu/scientific-activities/employment/algorithmic-management-and-digital-monitoring-work_en 1]). Simply put, it is a way to control workers, and workers generally have no say in how the system that tracks them is created. As Winner says "different people are differently situated and possess unequal degrees of power as well as unequal levels of awareness" ([https://www.jstor.org/stable/20024652?seq=7 2]).</p><br />
<p>The population affected is workers; both “white collar” and “blue collar” workers are impacted. Whether it’s Amazon tracking warehouse workers’ “Time Off Task” with handheld scanners ([https://www.wired.com/story/amazon-worker-tracking-details-revealed 3]) or Meta employees having their every click tracked ([https://www.techpolicy.press/metas-worker-surveillance-tests-eu-rules-on-ai-and-labor/ 4]) to train AI, employers have the power to watch and control their employees in an unprecedented way.</p><br />
<p>It matters legally because workers have very few rights to fight back against these surveillance programs; even the The Electronic Communications Privacy Act of 1986 allows exceptions to surveillance of employees ([https://bja.ojp.gov/program/it/privacy-civil-liberties/authorities/statutes/1285 5]).<br></p><br />
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=== <br>2. Historical lineage. ===<br />
<p><br>2.1 Panopticon: it is an architectural apparatus developed by Jeremy Bentham in 1791. The design of this building effectively generated the sense of constant monitoring, which in turn motivated the prisoners to behave as if they were being watched at all times. As human labor became commodified, capitalists began implementing measures to ensure the maximization of productivity, including the replication of this design ([https://doi.org/10.14452/MR-070-09-2019-02_2 6]). While unused today, the panopticon is widely considered as both a theoretical and practical inspiration of other forms of surveillance in the workplace.</p><br />
<p><br></p><br />
<p>2.2 Scientific management: this theory attempts to analyze and standardize workflows to improve labor productivity. Frederick Winslow Taylor, its main pioneer, used early forms of data analysis during the XX century to decrease walking distances, eliminating unnecessary movements and preventing deliberate slow-walking among workers. ([https://doi.org/10.14452/MR-070-09-2019-02_2 7]). There are many modern forms of data-driven decision-making processes in the workforce. For instance, Amazon warehouses track individual workers' scan rates in real time through handheld scanners, generating data feeds to track and evaluate performance ([https://www.theverge.com/2019/4/25/18516004/amazon-warehouse-fulfillment-centers-productivity-firing-terminations 8]).</p><br />
<p><br></p><br />
<p>2.3 PC in the workplace: John Blankenbaker designed the first commercially available personal computer in 1971 ([https://www.computerhistory.org/revolution/personal-computers/17/297 9]), however, it wasn’t until the mid-1980s that the use of personal computers in the workplace became an industry standard. This achievement gave rise to the digital monitoring of work, which in turn allowed employers to monitor employees in real-time, effectively replacing the human eye with a more efficient surveillance mechanism. This represents one of the key aspects of modern-day workplace monitoring.<br><br></p><br />
<p><br></p><br />
<br />
=== 3. Mechanism of path dependence. ===<br />
'''<br>'''When analyzing the historic lineage of work surveillance, it is possible to point out two main path dependencies mechanisms in place.<p>Firstly, it is clear that many of the technological developments that arose through these events have one major goal, which is to increase wealth within a hierarchical ecosystem. Employers resort to several mechanisms to maximize profits and cut inefficiencies at the expense of workers.&nbsp;</p><br />
<p>In addition, standardization can also be singled out as a key mechanism at play. Once one corporation implements any of these developments (such as the digital monitoring of the workplace), the market incentives would force the rest to do the same in order to be profitable and remain competitive.</p><br />
<br />
=== 4. Politics and distribution. ===<br />
<br>One simple answer to this question would be that capitalists implement and leverage these mechanisms to increase their wealth while the working class remains powerless and unable to withdraw itself from the system in force.&nbsp;<p>However, if we resort to Winner's framework, we see that the technical elements of these technologies are not intrinsically capitalist, since workplace surveillance can also be observed in alternative regimes (including chattel slavery and the Soviet regime). It seems that, rather than being exclusively tied to capitalistic values, the methods in question respond to strong hierarchical structures.</p><br />
<p>In addition, even under a libertarian framework, structural inequalities are still present, allowing a privileged class to enjoy individual freedoms while segregated groups keep performing low-income jobs ([https://www.metamute.org/editorial/articles/californian-ideology 10]), arguably still subject to surveillance. Thus, not only are these technologies compatible with hierarchical top-down forms of government, but also with structures that allow such hierarchies to form without state intervention.</p><br />
<p>That said, this form of management seems less compatible with democratic societies, which tend not only to value individual liberties but to turn them into enforceable rights (including workers' privacy, health and integrity), thus establishing boundaries for workplace surveillance. This could explain why studies of American business leaders have found them unhappy with democratic scruples ([https://www.jstor.org/stable/20024652 11]).</p><br />
<p><br></p><br />
<br />
=== 5. Contingency and alternatives. ===<br />
<p><br></p><br />
<p>Bush writes about the memex, a machine that could extend a person’s memory and that the memory would belong to the person who owned it. As Bush expands, “For mature thought there is no mechanical substitute" ([https://dl.acm.org/doi/pdf/10.1145/227181.227186 12]). His idea was that a machine could take over the repetitive nature of someone’s job, while the person could record their own thoughts for their own use. Bush’s memex was never created, but the idea inspired products like Microsoft’s Productivity Score that were made for employers (the buyers) not for the person whose memory it used (the worker).</p><br />
<p>This immediately brings to mind Meta's Model Capability Initiative, which was done to train AI agents the company hopes to sell to other employers as well as watch their employees ([https://www.reuters.com/sustainability/boards-policy-regulation/meta-start-capturing-employee-mouse-movements-keystrokes-ai-training-data-2026-04-21/ 13]). If this was Bush’s memex, it would belong to the employee using it, not Meta.&nbsp;</p><br />
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<br />
=== 6. Governance implication.<br> ===<br />
Democratic oversight of the use of algorithms as a form of surveillance is essential to ensure that workers’ rights are not overstepped in the name of efficiency. As such we propose: all workers should have a legal right to be consulted and approve a surveillance program before a company installs and uses it. A tracking system should be a group decision, not an inevitable, unilateral one. While the United States has very little protections for workers in terms of surveillance, the EU leads the way with the GDPR, specifically Article 22 ([http://data.europa.eu/eli/reg/2016/679/oj 14]), and the AI Act Article 5 ([http://data.europa.eu/eli/reg/2024/1689/oj 15]). It’s also worth noting that in December 2026, the Platform Work Directive ([https://eur-lex.europa.eu/eli/dir/2024/2831/oj/eng 16]) will come into effect which will ban automated termination.<br />
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== [[Platform Dependence in Public Communication (News)]] Ceren & Rodrigue ==<br />
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Public communication is the conveyance of a message to a large group of people. This includes public announcements, advertisements in public spaces, social media broadcasts, news delivered in reporting, editorials, opinion pieces, and even political campaigns. Platform dependence is the reliance on a third party platform or digital infrastructure to reach the audience of the public communication, the public. Platform dependence in public communication therefore includes reliance on private companies like Meta (Facebook), state television channels, or telecommunications providers who provide and control access to, and develop the infrastructure of such platforms. For the purpose of this exercise, news will be utilized as the main example of public communication. It is very difficult to discuss news without highlighting the deep entanglement it shares with with information. For our purpose 'information' will have the the following characteristics; it can be learned, processed, archived, and it's worth correlates to its rarity.<sup>[[#fn1|[1]]]</sup> News is the end result of the process of taking this information from one form to another, and transmitting to a wider, typically public audience is what we will anchor our definition of 'news' to be. <br />
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Those who are affected by platform dependence in public communication are the communicators and the public alike. News outlets are mainly for-profit organizations. These organizations’ reliance on third party digital platforms grows day-by-day to maintain their popularity and engagement ultimately deciding the revenue generated from advertisers. The public on the other hand are provided catchier and more diluted information, gaining just enough knowledge to grab their attention while not being provided substantial knowledge on matters. Additionally, members of the public who do not have the resources to access such platforms and digital services remain “information poor”.&nbsp;<sup>6</sup> Digital rich, the virtual class of tech-professional and entrepreneurs benefit from the dependence to their platforms.<br />
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This is crucial as platform dependence may threaten democracy and free political expression. Platforms, run by private parties, can be run according to their political beliefs. Social media platforms aiming to keep users online utilize algorithms that provide their users with their confirmed preferences, not allowing the conveyance of a truly heterogeneous catalogue of news. The original ideal of the democratic electronic agora is undermined when private corporations control the flow of news and the infrastructure on which they are provided.<br />
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=== Historical Lineage ===<br />
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Modern form of this can be traced to Renaissance Europe,<sup>[[#fn2|[2]]]</sup> where a single innovation displaced established networks of collecting, processing and sharing news.The church, merchants, students, and diplomats were core participants in this ecosystem.<sup>[[#fn3|[3]]]</sup> The invention of printing in the 15th century was a seismic point in history as it offered new possibilities for the dissemination of information and therefore news. Initially, printing benefitted from the existing networks more than the networks benefitted from printing. This was the case until the networks were unrecognisably transformed. A trend we will see come to see throughout the history of the news. A clear instance of this is Johann Carolus's ''Relation aller Fürnemmen und gedenckwürdigen Historien'', a handwritten newspaper delivered weekly to the elite class of the time. The mode of production and the means of distribution were constrained by the available technology rather than strategy. The mode of mode production decreased the cost, time and later revolutionised the network as production could be localised and dependency on transporting was reduced.&nbsp;<br><br />
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One of the first paying customer for press was the Church, selling indulgences. During this era the Church and the State were in a clear symbiotic relationship making drawing a separation between the two difficult. They both deeply understood Beniger's principle that control depends on information processing and communication working together.<sup>[[#fn4|[4]]]&nbsp;</sup>By introducing hurdles of licensing the type of content that could be printed on one hand and benefitting from the industrial might of this innovation they had effectively consolidated power and control. Interesting, this contrasts what takes place generations later in the computing revolutions, where proximity to the state purposely unstated in order to appeal to the mass.<sup>[[#fn5|[5]]]</sup> <sup></sup><br />
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The next evolution of news takes place when transmission is once again innovated with the radio. With radio reach could reach could be decoupled from cost, reliance on aging networks such as the now matured postal system. Control was could now be on content and move closer to physics on licensing who could be broadcast rights. This changed the trajectory of new's as it birth the state broadcaster, responsible for broadcasting news to anyone with a receiver on the appropriate frequency. News outlet now had legitimate diverse alternative methods of production and distribution. The television followed not after, however it mostly followed the trajectory of the radio with the caveat that it dominated due to ability to generate commercial revenue through advertisement and optionality it provided.&nbsp;&nbsp;<br />
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=== Mechanism of Path Dependence ===<br />
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The public is generally partakes in the consumption of content on social media. Hence, with its 3 billion monthly active users for example, Instagram has an installed base for news outlets to depend upon (Instagram Revenue and Usage Statistics (2026), n.d.). The audiences of news outlets spend an increasing amount of their time on social media platforms, which gives results in a habitual entrenchment for these news outlets: the means of reaching the audience is dependent on their habits of content consumption. An indirect contractual entrenchment may also be discussed, as news outlets have obligations to their advertisers (who may request the upkeep of views/clicks on the news platforms they pay to advertise in). Cultural entrenchment should not be disregarded: the public expects to receive their news on social media platforms they readily frequent, and many news outlets meet this expectation. Hence, news outlets must partake in building a presence in social media platforms if they wish to compete.<br />
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=== Politics and Distribution ===<br />
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Barbook argues that although the California Ideology claims that state power will be decreased and individuals will be empowered through decentralized networks enabled by digital technologies, he demonstrates that public communication is in fact not immune to undemocratic powers. These include private corporations: these corporations may gatekeep in choosing when and how to provide access to their platforms, while finetuning how users navigate their platforms. By enabling access to content that users tend to agree with, those who manage these platforms enable public opinion to shift to extremes. Being “fed” the same narrative and not being challenged to see an opposing perspective ultimately provides fewer choices to the consumer of the information, the general public. Therefore, individual agency is constrained by platform architecture and control, not liberated by it.<br />
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=== Point Of No Return ===<br />
In examining the lineage of news and its eventual platform dependency, the diminishing returns of technological advancement for the industry become evident. Revenue has not been a particular focus of this article. The broadcast era was the era in which news outlets earned some of their largest revenues and were at their most independent. It was during this time that news outlets initiated the unbundling of one of their main revenue generators, the classified advertisement. By initiating this [https://stratechery.com/2017/the-great-unbundling/ unbundling] without any afterthought on capitalising on its timely advantages, news outlets entered their relationships with social media platforms in a weakened position. Searching for a saviour and giving the platform the credentials and reputation they needed in the early days in return. Reminiscent of the trend identified earlier. An example of a new's outlet that has navigated this journey with more diligence is [https://business.columbia.edu/insights/ai-transformative-tech/how-new-york-times-company-reinventing-itself-digital-age The New York Times].<br />
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=== Governance Implication & Proposition ===<br />
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It's clear that complete avoidance of these platforms on the part of news outlet is a Heculean request! New's outlets have flocked to these platforms due to their substantial audience and lock on audience. It's virtually impossible for a single organisation to mount a significant rebellion without self harming. A proposal is to approach the problem more as a herd and invest and cultivate more alternative open platforms for example [https://en.wikipedia.org/wiki/Bluesky Bluesky]&nbsp; and [https://joinmastodon.org Mastadon]. The benefit that these platforms bring about begin with not only optionality from the current dependencies but governance via protocol.<br />
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=== Footnotes ===<br />
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# <span id="fn1"></span>Mark Greengrass, Thierry Rentet and Stéphane Gal, ‘The Hinterland of the Newsletter: Handling Information in Space and Time’ in Joad Raymond and Noah Moxham (eds), News Networks in Early Modern Europe (Brill 2016) http://www.jstor.org/stable/10.1163/j.ctt1w8h1ng.34 accessed 7 September 2026; ‘Michel Serres Prononce En Sorbonne La Conférence Inaugurale Du Programme Paris Nouveaux Mondes - La Chancellerie Des Universités de Paris’ (La Chancellerie des Universités de Paris, 1 January 2013) https://www.sorbonne.fr/michel-serres-prononce-en-sorbonne-la-conference-inaugurale-du-programme-paris-nouveaux-mondes/ accessed 7 September 2026. James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986).<br />
# <span id="fn2"></span>Brendan Dooley, Making News in Renaissance Europe (1st edn, Cambridge University Press 2026) https://doi.org/10.1017/9781009358835.<br />
# <span id="fn3"></span>Andrew Pettegree, The Invention of News: How the World Came to Know about Itself (Yale University Press 2014). Helmer Helmers, ‘Public Diplomacy in Early Modern Europe: Towards a New History of News’ (2016) 22 Media History 401 https://doi.org/10.1080/13688804.2016.1174570.<br />
# <span id="fn4"></span>James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986) P24-25<br />
# <span id="fn5"></span>Richard Barbrook and Andy Cameron, The Californian Ideology (1996)<br><br />
#Richard Barbrook and Andy Cameron, The Californian Ideology (1996)<br />
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= Centralization of AI Compute and Data =<br />
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== Centralization of AI Compute and Data - by Sisi Hammoudi & Juliette Chamot ==<br />
=== Governance issue ===<br />
<span class="s8">Today, several path-dependence phenomena are emerging across advanced computing technologies. This assignment addresses one of them: the </span><span class="s8">centralisation</span><span class="s8"> of AI compute and data. Training and running frontier AI systems now depends on a handful of hyperscale providers, namely Amazon, Microsoft, Google, and Nvidia, which dominates the GPU market. In other words, near monopolies exist throughout the supply chain. This concentration creates a governance problem affecting public and private actors alike, both legally and institutionally. On the institutional side, it prevents public administrations, and states other than the US or China, from reaching sovereign AI capacity. It also raises competition-law concerns, since dominant market positions can prevent the market from delivering the best products at the best prices to consumers. Finally, AI developers, like states, are often forced into contracts with hyperscale providers, creating a structural dependence on them.</span><br />
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=== <span class="s8">Historical lineage</span> ===<br />
==== <span class="s8"><span class="s8">1945</span></span> ====<br />
<span class="s8"><span class="s8">Wartime scientific instruments should have been redirected to extend human command over knowledge, helping establish the postwar model of sustained federal funding for computing research (Vannevar Bush's, "As We May Think », 1945).</span></span><br />
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<span class="s8"><span class="s8"></span></span><br />
==== <span class="s8"><span class="s8">1990s</span></span> ====<br />
<span class="s8"><span class="s8">The privatisation of the NSFNET established the idea that critical digital infrastructure, even though publicly subsidised, could legitimately be privately owned. The EU Commission followed the US's lead, recommending privatisation and deregulation of telecommunications and media as the best way to build the "infobahn" though EU members could instead have chosen nationalisation of the infrastructure (Barbrook & Cameron, "The Californian Ideology," 1996).</span></span><br />
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<span class="s8"><span class="s8"></span></span><br />
==== <span class="s8"><span class="s8">2006</span></span> ====<br />
<span class="s8"><span class="s8"></span></span><div class="s13">Hyperscale cloud computing turned massive fixed capital investment in data centresinto a rentable service, favouring firms able to invest at scale.</div><br />
<div class="s13">Same period: Nvidia's proprietary CUDA software, released alongside its GPUs, became the de facto standard for machine learning, locking in a decade of tooling and expertise around one firm's hardware.</div><br />
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==== <span class="s8"><span class="s8"><span class="s8"><span class="s8">From 2022</span></span></span></span> ====<br />
<span class="s8"><span class="s8"><span class="s8"><span class="s8"><span class="s8"><span class="s8">Semiconductor export controls and the CHIPS Act turned compute into an explicit instrument of geopolitical strategy.</span></span></span></span></span></span></div><br />
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=== <span class="s8">Mechanisms of path dependance</span><span class="s8"></span> ===<br />
<span class="s8"><span class="s8">Several mechanisms drive this </span><span class="s8">centralisation</span><span class="s8">, but path-dependence ones dominate. Because AI compute is a capital-intensive industry, new entrants struggle to compete with </span><span class="s8">hyperscalers</span><span class="s8"> that have already sunk huge sums into infrastructure, a barrier that produces monopoly-like situations. This dynamic, known as increasing returns, generates system-scale economies that harden into a near-irreversibility of investment (David, "Clio and the Economics of QWERTY," 1985). It overlaps with a second mechanism, </span><span class="s8">standardisation</span><span class="s8">, itself a form of technical interrelatedness: researchers' investment in Nvidia's CUDA-based tooling locks the field into that ecosystem regardless of whether better alternatives exist. A further mechanism is legal and contractual entrenchment. For example, Microsoft's stake in OpenAI binds developers to a specific provider by agreement rather than technical necessity.</span></span><br />
=== Politics and distribution ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">Technology does not have a history of distributing power equally. Rather, its development has strengthened the interests and authority of powerful groups that already possessed economic and political resource</span><span class="s8">s, and it is yet to be determined whether AI compute and data will follow suit</span><span class="s8">. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Author Langdon Winner illustrates </span><span class="s8">the historical con</span><span class="s8">s</span><span class="s8">traints of technological development</span><span class="s8"> with the case of New York from </span><span class="s8">the </span><span class="s8">1920s to the 1970s. He argued that the city’s roads, bridges, and parks’ physical arrangement contained “explicit and implicit political purpose</span><span class="s8">.</span><span class="s8">”</span><span class="s8"> </span><span class="s8">These infrastructures privileged wealthy and white communities while restricting poor and Black populations’ choice of mobility. Similarly, the development of industrial machinery increased productivity, simultaneously weakening union and non-union worker</span><span class="s8">s’</span><span class="s8"> bargaining power.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">In the twentieth century, f</span><span class="s8">ollowing the Industrial Revolution, a Control Revolution emerged from the increasing need to manage </span><span class="s8">expanding production, transportation, and information flows requiring strengthened organizational bureaucratic control.</span><span class="s8"> This was heavily shaped by the political context of post-World War II warfare.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Therefore, the bearer of the initial cost of technology is the person putting in the capital to erect it</span><span class="s8">,</span><span class="s8"> but ultimately, the person bearing the long-term cost of technology, whose choices diminish</span><span class="s8">,</span><span class="s8"> </span><span class="s8">is</span><span class="s8"> not the rich and privileged, but the everyday person subject to technologies. Forced to adapt, to reshape their professional skills to adapt to an environment trying to make them obsolete.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">AI compute and data </span><span class="s8">are</span><span class="s8"> at risk of creating the same effect. I</span><span class="s8">n their critique of dotcom neoliberalism</span><span class="s8">,</span><span class="s8"> authors Barbrook and Cameron exposed a similar socio-economic tension. The Californian Ideology claims digital technology empowers individuals</span><span class="s8">;</span><span class="s8"> however, perpetual unequal access to it creates </span><span class="s8">an apartheid between </span><span class="s8">“information-rich” and “information-poor” populations.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Finally, the development of AI compute and data depends on expensive and scar</span><span class="s8">c</span><span class="s8">e computing infrastructure and </span><span class="s8">a </span><span class="s8">highly concentrated semiconductor supply chain.</span><span class="s8"> Today, this is one of the most concentrated industries</span><span class="s8">,</span><span class="s8"> with single companies having near</span><span class="s8">-</span><span class="s8">total monopolies over the production of chips necessary </span><span class="s8">for</span><span class="s8"> the functioning of AI. This monopoly model threatens to reinforce the existing economic hierarchy.</span></p><br />
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<span class="s8"></span><br />
=== <span class="s8">Contingency and alternatives</span> ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">If a different technological trajectory was plausible, the most apt time for it to have occurred would be during the transition from the Industrial Revolution to </span><span class="s8">the </span><span class="s8">“Control Revolution”. When industrial production accelerated, our society experienced a “crisis of control”, creating opportunities to organize information and communication differently.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Instead of allowing control technologies to </span><span class="s8">be monopolized within businesses and states, our societies could have pursued a more democratic and decentralized system. Barbrook and Cameron provide such an alternative path through their idea of the “electronic agora</span><span class="s8">,</span><span class="s8">” where digital networks could encourage community participation </span><span class="s8">and </span><span class="s8">direct democracy</span><span class="s8">,</span><span class="s8"> where government could actively engage with the people to shape digital infrastructure and expand access.</span><span class="s8"> These alternatives did not actually prevail because corporat</span><span class="s8">e</span><span class="s8"> and state market participants possessed greater resources and authority to shape technological development at the end of the twentieth century. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">Inherently, technological development is not predetermined</span><span class="s8">;</span><span class="s8"> it can support either authoritarian or democratic arrangements.</span><span class="s8"> Today, monopolies control chip production needed for AI compute and data, but other technologies like blockchain permit democratic participation.</span></p><br />
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<span class="s8"></span><br />
=== <span class="s8">Governance implication</span> ===<br />
<p class="s16" style="text-align: justify;"><span class="s8">History always threatens to repeat itself. As Barbrook discussed, digital societies are shaped by the political context i</span><span class="s8">n</span><span class="s8"> </span><span class="s8">which</span><span class="s8"> </span><span class="s8">they develop</span><span class="s8">. It is a valid concern, then, that the development of information technology, through AI computing, would follow the same trajectory</span><span class="s8">-</span><span class="s8"> that is, be constrained to benefit the wealthy who funded its development, and ultimately harm the middle and lower classes enabling its functioning. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">However, AI’s place in our society has not yet crystallized. Technology governance does not have to adhere to this system. Such a seemingly sustainable approach to AI compute and data governance has already been broached. In 2022, the Notre Dame Journal on Emerging Technologies published an article in </span><span class="s8">its</span><span class="s8"> issue on Artificial Intelligence where the authors proposed an AI compute system based on a “dual investment strategy”</span><span class="s8">. Firstly, the model would be launched by “subsidizing and negotiating” cloud computing for </span><span class="s17">human </span><span class="s8">AI researchers through “existing” cloud vendors</span><span class="s8">,</span><span class="s8"> which would expand on existing AI compute initiatives. Secondly, the compute system would be specifically invested in as a public</span><span class="s8">ly</span><span class="s8"> owned infrastructure that would </span><span class="s8">b</span><span class="s8">e built</span><span class="s8"> and operate similarly to national libraries which own “academic supercomputing facilities”. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">The pilot program would have a “base level of compute access”</span><span class="s8"> which would keep costs of processing </span><span class="s8">down and</span><span class="s8"> enable it to meet the compute need</span><span class="s8">s</span><span class="s8"> of </span><span class="s8">a majority of</span><span class="s8"> academic researchers. Absent any strengthened legislation on the use of AI compute and data, the hardware would be accompanied by an AI ethics framework to enable sustainable technological governance. In addition to an ethical staff, the human resources needed to keep an AI compute model running would include data officers, scientists, data center and software engineers, research developers, </span><span class="s8">and </span><span class="s8">system administrators. These positions require specialized training, allowing new types of professional</span><span class="s8">s</span><span class="s8">, from any background</span><span class="s8">,</span><span class="s8"> to have access to professional prosperity in the field of AI. </span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8">By implementing these frameworks, never neglecting the human element, and the economic and intellectual impact AI has on our society, we move from a historical determinist perspective to one acknowledging historical constraints and </span><span class="s8">learning</span><span class="s8"> from them.</span></p><br />
<p class="s16" style="text-align: justify;"><span class="s8"></span></p><br />
<h3 class="s16 mwt-heading" style="text-align: justify;" ><span class="s8">Bibliography</span></h3><br />
<span class="s8"></span><div><div><p>[1] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 124, (1980)</p></div><div><p>[2] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 124, (1980)</p></div><div><p>[3] James R. Beniger, The Control Revolution: Technological and Economic Origins of the Information Society, Harvard University Press, p. 443, 450 (1986)</p></div><div><p>[4] Richard Barbrook, Andy Cameron, The Californian Ideology,&nbsp;''Science as Culture'',&nbsp;''6''(1), 44–72, 61 (1996)</p></div><div><p>[5] Anton Korinek, Jai Vipra, Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence, National Bureau of Economic Research, 10.3386/w33139, p. 11, 13-15 (2024)</p></div></div><div><div><p>[6] James R. Beniger, The Control Revolution: Technological and Economic Origins of the Information Society, Harvard University Press, p. 443, 442 (1986)</p></div><div><p>[7] Richard Barbrook, Andy Cameron, The Californian Ideology,&nbsp;''Science as Culture'',&nbsp;''6''(1), 44–72 (1996)</p></div><div><p>[8] Langdon Winner, Do Artifacts Have Politics, Daedalus, Winter, 1980, Vol. 109, No. 1, Modern Technology: Problem or Opportunity? pp. 121-136, 130 (1980)</p></div><div><p>[9] Daniel E. Ho, Jennifer King, Russell C. Wald & Christopher Wan, The Centrality of Data and Compute for AI Innovation: A Blueprint for the National Research Cloud, 3 Notre Dame J. on Emerging Tech. 71, 81(2022)</p></div><div><p>[10] Daniel E. Ho, Jennifer King, Russell C. Wald & Christopher Wan, The Centrality of Data and Compute for AI Innovation: A Blueprint for the National Research Cloud, 3 Notre Dame J. on Emerging Tech. 71, 82 (2022)</p></div></div><br />
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== Centralization of AI compute and Data - by Atmika Dechamma & Pablo Latorre ==<br />
=== Governance Issue ===<br />
AI computing capacity and data presents the governance problem of an extreme concentration of technological infrastructure and information in a restricted number of companies that privately and globally dominate the market. This affects public and private actors - such as small and medium enterprises, potential new competitors, and Global South countries - that increasingly depend on AI systems outside their control and/or are deterred from competing with established companies because of impenetrable entry barriers - most notably initial investments and operational costs (1). The institutional and legal relevance of this is that it consolidates, reproduces and amplifies asymmetries of power in favor of the “Big Tech”, reverting the technological trend from digital decentralization to physical infrastructure dependency and curbing innovation and market efficiency.<br />
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=== Historical Lineage ===<br />
==== Limitation of Machine Learning ====<br />
<p style="text-align: justify;">The AI revolution was built on the limitation of human capabilities to process large information and derive efficient results - where before there existed only facilitative tools to allow for human-enabled processes, AI now offered derivations and cognitive reasoning in moments and at large scales.</p><br />
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==== Revert to Physical Infrastructure Dependency in the rush to be the best ====<br />
<p style="text-align: justify;">The present AI model heavily relies on hardware in order to perform complex data processing for deep learning. The data centre models followed require larger model sizes (which require higher resource, information and capital investment) to be able to yield better results. Due to the limitation of resources and a rush to establish the best working model of an AI agent, data centres are built on a rudimentary model heavily dependent on massive amounts of electricity and fresh water (2).</p><br />
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==== Regulation and Decentralization of Information ====<br />
<p style="text-align: justify;">Regulation and influence of sovereigns and institutions has resulted in data sharing and information exchange structurally through open source and cloud computing. But, while AI models claims their selling point to be accessibility for all, their information and derivations remain in a closed server, stored for the purpose of training their AI agents to be the best (3). Big AI contenders attract higher consumer and information flows overall resulting in a better developed AI model, proving disadvantageous in any market where early contenders have an advantage and accumulation of power.</p><br />
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=== Mechanisms of Path Dependence ===<br />
<p style="text-align: justify;">Early on in the industry there is an expectation of human and capital investment from all stakeholders involved, this high cost for entry into the market and expected capital to sustain and develop a model by both consumer and enterprise makes for a high switching cost. For the AI model to run and scale there is a presumption that the rate of growth is dependent on the size of data fed, resulting in a better model and hence, more consumer usage. A closed centralised data loop is created but the requirement for storage and processing far surpasses current infrastructures capabilities - heavily relying on early market entry advantage and sustained capital investments taking away from smaller aspirants and hoarding of power within closed circles. Despite its physical dependency, AI data processing has unique requirements beyond legacy infrastructures (4) - larger demand and production of GPUs and designed to handle immense thermal heat generated while consuming electricity beyond current capabilities.&nbsp;</p><br />
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<br><p style="text-align: justify;">The AI space largely remains unregulated due to its undefined form and fluid nature, however, this has given way for unethical and morality issues regarding data privacy, exploitation of labour and environmental harms.</p><br />
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=== Politics and Distribution ===<br />
Concentration strengthens the values, interests, capacities, and authority of the “Big Tech” over other actors of public and private nature. In this context, Barbrook and Cameron (5) illuminate the ethos behind AI technology development while Winner (6) makes observable the power relations surrounding it: concentration is the consequence of an AI development anchored in the belief that it must be free from all institutional and normative restriction since it is inherently liberating and non-political which, in turn, provides a political/moral justification for the concentration (if technology is inherently liberating and non-political then there is no power relations to observe or question) that translates itself into power dynamics where the AI developer not only owns the AI technology but also decides how it is trained and deployed and which models the user can or cannot access.<br />
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=== Contingency and Alternatives ===<br />
Concentration is due, first and foremost, to the fact that AI computing capacity requires massive and cutting-edge physical infrastructure - such as data centers and microprocessors - which, in turn, requires upfront investments that are unaffordable to most companies. In David’s (7) language, companies that could finance the infrastructure and position themselves first obtained self-reinforcing advantages and a “lock-in” effect in the market. In other words, concentration is the consequence of the development of AI physical infrastructure privately with no mixed or public alternatives as a public service. Therefore, there was a space for an alternative future at the end of the 1980s or the beginning of the 1990s when the privatization model of the technological infrastructure was consolidated in line with the “Californian Ideology”. In that moment governments had the chance to treat technological infrastructure as a mixed or public good rendering it universally accessible as it was the case of the Internet; this would have permitted companies of all sizes to profit from economies of scale, reducing entry barriers and fostering competition. However, this alternative path did not prevail since the Californian Ideology provided the moral/political justification to exclude governments from the development of technological infrastructure in the exact moment in which such a decision would produce structural consequences. If that path had been followed it could have contributed to collective access to economies of scale, lower entry barriers, and a more competitive AI market.<br />
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=== Governance Implication ===<br />
Considering the above, public or mixed investment on AI physical infrastructure is a necessary governance measure for market decentralization and collective access to AI computing capacity and data. From an historical perspective, the proposed measure is not merely a corrective action for a market failure but for a contingent and ideological decision made between the late 1980s and early 1990s that produced a structural “path dependence” that now is necessary to change.<br />
==== References ====<br />
(1) The Quiet Re-Centralization of Tech: Why AI Is Reversing 20 Years of Platform Decentralization. (2026, January 10). Retrieved on 8 September 2026, from Medium website : [https://medium.com/@sumitbhardwaj1357/the-quiet-re-centralization-of-tech-why-ai-is-reversing-20-years-of-platform-decentralization-ce15962b6a13 https://medium.com/@sumitbhardwaj1357/the-quiet-re-centralization-of-tech-why-ai-is-reversing-20-years-of-platform-decentralization-ce15962b6a13]<br />
<br />
(2) [https://www.mdpi.com/1996-1073/19/1/137 Ginzburg-Ganz, E., Lifshits, P., Machlev, R., Belikov, J., Krieger, Z., & Levron, Y. (2025). Technical challenges of AI data center integration into power grids—A survey. <em>Energies</em>, <em>19</em>(1), 137.]<br />
<br />
(3) [https://decai-resources.s3.us-east-1.amazonaws.com/decentralized_ML_perspective-16.pdf Singh, A., Lu, C., Gupta, G., Chopra, A., Blanc, J., Klinghoffer, T., ... & Raskar, R. (2024). A perspective on decentralizing AI.]<br />
<br />
(4) The Rise of AI Data Center Models and the Decline of the General-Purpose Data Center. (Circa 2026). Retrieved on 8 September 2026, from SubZero Engineering website : [https://www.subzeroeng.com/the-decline-of-the-general-purpose-data-center/ https://www.subzeroeng.com/the-decline-of-the-general-purpose-data-center/]<br />
<br />
(5) [https://git.xpub.nl/onebigear/SI_09_reference_library/raw/commit/22bf61e1dcfed35d58fba23808212bd00584be47/Richard_Barbrook_Andy_Cameron_Californian_ideology.pdf Barbrook, R., & Cameron, A. (1996). The Californian Ideology. <em>Science as Culture</em>, <em>6</em>(1), 44-72].<br />
<br />
(6) [https://d1wqtxts1xzle7.cloudfront.net/87708502/langdon_winner_do_artifacts_have_politics-libre.pdf?1655588533=&response-content-disposition=inline%3B+filename%3DDo_Artifacts_Have_Politics.pdf&Expires=1788890463&Signature=UBBiMqkip5MfYZbkbLNAN6aE2hyZdKkER-HFcmyxXkwIZuTnMKdOGoao8ddFr-rQ5T55A8NWUOlnZkGYmi66e7XR9h99DgTELMCrh48sXjOb8KYgA48r~SUUymt1IW~R~aOKJzitMIUHcrc6yEGKK1OuaA~mrEIVOXpUjQMYjqOd26Xmk9YJEglTkqaxeR47VCCth5FvozNQIowdfjzeu8aNHnI8V7Yur1IiXY~PGvYRcN6wBtcgpVMHZUtNaI8NjmYbp2p5TBYrPMF9MCLtvpGhPlsCfsvA8Bdm6XulGwRlksZBKWvVUQ8D~M8oLu12V39YaiETIObyJqbE7ctIcQ__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA Winner, L. (2017). Do artifacts have politics?. In <em>Computer ethics</em>(pp. 177-192). Routledge].<br />
<br />
(7) [https://sjbae.pbworks.com/f/David+1985.pdf David, P. A. (1985). Clio and the Economics of QWERTY. <em>The American economic review</em>, <em>75</em>(2), 332-337].<br />
<br />
== Centralization of AI compute and Data - by Sergey Abramov and Paul Stein ==<br />
<div><br />
=== The current governance issue ===<br />
<p>Advanced AI currently depends on a narrow group of tech giants<sup>1</sup> and semiconductor oligopolies controlling microchips and software, hyperscale cloud infrastructure, large datasets, frontier models, and distribution platforms. This presents a governance problem where this narrow group exercises control over foundational digital infrastructure. This directly affects consumers, businesses, and academia out of AI. Legally and institutionally, this matters because it creates a profound democratic deficit: this neutralizes antitrust frameworks designed for traditional markets, often bypassing conventional copyright and data privacy protections through unchecked data harvesting thereby complicating enforcement.This ultimately might affect national sovereignty as the countries that host the buildout will shape the future of AI: who controls it, what values it contains, how it is used<sup>2</sup>.</p><br />
<br><br />
=== Historical lineage ===<br />
<p>In 1987, Taiwan Semiconductor Manufacturing Company (TSMC) was founded, establishing the world’s first semiconductor fab. Instead of designing and making its own chips, TSMC only manufactured chips designed by other companies. Today, nearly 100% of the world's most advanced AI processors are manufactured by TSMC, leaving the entire global AI compute supply chain centralized under one company.</p><br />
<br><p>In 2006, Nvidia launched CUDA (Compute Unified Device Architecture), a free software layer that allowed developers to use Nvidia's graphics chips (GPUs) which later became perfect for training deep neural networks. Today, this creates a near-monopoly on AI compute hardware.</p><br />
<br><p>Soon after Amazon launched AWS, Microsoft and Google launched their own cloud platforms marking the structural pivot to the cloud service provider model, shifting computing from a distributed architecture (where companies bought and managed their own physical servers) to a centralized infrastructure. As training modern AI models requires tens of thousands of GPUs, today’s frontier AI companies are entirely dependent on the extremely expensive physical infrastructure of a handful of cloud hyper-scalers (Microsoft, Google, AWS, and Meta).</p><br />
<br><p>In 2009, Fei-Fei Li launched ImageNet, a massive database of over 14 million images, which proved that AI model performance scales directly with data volume. This created an immediate institutional advantage for consumer internet platforms (like Google and Meta), because they were already architected to collect, centralize, and store masses of user data through search engines and social networks, they possessed the unique data stack required to train high-performing AI.</p><br />
<br><br />
=== Mechanism of path dependence ===<br />
<p>The centralization of AI compute and data is a classic case of technological lock-in. When structural choices were made decades ago, they triggered powerful, self-reinforcing loops. One such loop is the switching costs and software standardisation. As developers have spent more than a decade working with CUDA, moving to a rival hardware provider (or a decentralized compute network) requires an enterprise to completely rewrite its foundational software stack. The cost of code migration, developer retraining, and potential hardware downtime force companies to stay tied to dominant hardware monopolies such as Nvidia. Commitments, licensing conditions, and exclusivity provisions add contractual costs. Fewer than 1% of cloud customers switch provider annually, identifying technical differentiation and data-transfer charges as important barriers<sup>4</sup>.</p><br />
<br><p>Network effects also matter for computing power. More customers generate more revenue, usage information, and opportunities to improve infrastructure and models. Better services attract additional users and developers, whose applications make the platform more valuable. In cloud–AI partnerships, providers may additionally obtain information about model performance and future infrastructure demand. These feedback loops strengthen firms already operating across cloud, models, software, and distribution.</p><br />
<br><br />
=== Politics and distribution ===<br />
<p>According to Langdon Winner's definition, modern AI computing infrastructure may qualify as an "inherently political technology" because its large scale and significant financial requirements not only lend themselves to, but necessitate,<sup>5</sup> centralized, hierarchical control. The physical siting of this infrastructure shows evidence of Winner’s second category of politicization of technologies, the ‘political arrangement’:<sup>6</sup> Of the five largest U.S. AI firms, four are headquartered in California,<sup>7</sup> while just one is (partially) domiciled in Texas. Texas, however, hosts twice the GPU clusters.<sup>8</sup> This placement geographically insulates beneficiaries of the data infrastructure boom from its negative externalities. The specific choice of location may itself be a deliberate preference on account of Texas’ unique approach to water usage rights.<sup>9</sup> Juxtaposition of this unequal and even exploitative balance of interests with the pontificating rhetoric of the urban, information rich, beneficiaries is evocative of the internal contradictions of the Californian Ideology - the virtual artisans existence and privileged position is still based on the exploitation of a vulnerable out-group, the "information-rich" consuming the output, the "information-poor" hosting the extraction.<sup>10</sup></p><br />
<br><br />
=== Contingency and Alternatives ===<br />
<p>Profit motive and economies of scale now concentrate investment among a few hyperscalers,<sup>11</sup> but this reflects policy choice, not government incapacity: Compute infrastructure may be inherently political, but the technology is agnostic as to where the organizing authority originates, and states have historically funded infrastructure of comparable or greater scale, while facing less pressure to show short-term returns. The clearest turning point was 1995, when the National Science Foundation retired NSFNET, the publicly funded backbone that had connected U.S. research and supercomputing centers since the mid-1980s,<sup>12</sup> handing internet infrastructure to commercial providers with no conditions attached. This was a deliberate policy decision made amid the deregulatory push of the Clinton era. The privatization that followed ushered in the private industrial dominance that persists today in the form of hyperscalers. Had a publicly governed backbone instead been scaled up, today's compute infrastructure might rest on a different foundation entirely.</p><br />
<br><br />
=== Governance implication ===<br />
<p>Despite private hyperscaler dominance, the U.S. does have a nominal public alternative: the National AI Research Resource (NAIRR), established following the National AI Initiative Act of 2020 and piloted from January 2024, which explicitly aims to democratize access to the computational resources essential to AI research.<sup>13</sup>In Europe, a comparable program is the EuroHPCJU,<sup>14</sup> an initiative intended to pool resources to build supercomputing capacity. The undertaking’s legislative basis has since been extended to include networked ‘AI factories', as well as the so-called “Gigafactories”.<sup>15</sup> The framing in language of sovereignty indicates intent to at least compete with private infrastructure initiatives. Though government-led measures cannot reverse the centralization of compute, they can democratize access - provided they are intensified. The European Commission has “set a goal of investing more than €1 billion per year in AI research and innovation”.<sup>16</sup> While laudable in its own right, it pales in comparison to the investments of industry leaders, which are approaching, if not exceeding, trillions of Dollars.</p><br />
<br />
=== References & Notes ===<br />
1.Amazon, Google, Meta, Microsoft, and Oracle collectively hold an estimated 71% of the world’s cumulative AI compute as of Q4 2025, measured in H100-equivalents of computing power.&nbsp;<p>Luke Emberson, Josh You and Venkat Somala (2026), "Five hyperscalers now own over two-thirds of global AI compute". Published online at epoch.ai. Retrieved from 'https://epoch.ai/data-insights/hyperscalers-control-most-compute' [online resource]. Accessed 7 Sept 2026.</p>2. Alasdair Phillips-Robins, Teddy Tawil and Sam Winter-Levy, ‘The Compute Coalition: How to Build the Future of AI in the Free World’ (Carnegie Endowment for International Peace, 8 June 2026) https://carnegieendowment.org/research/2026/06/the-compute-coalition-how-to-build-the-future-of-ai-in-the-free-world accessed 7 September 2026.<br />
<br />
3. Amazon Web Services (AWS), a cloud computing platform<br />
<br />
4.&nbsp;Competition and Markets Authority, Cloud Infrastructure Services: Final Decision Report (31 July 2025) https://assets.publishing.service.gov.uk/media/688b8891fdde2b8f73469544/final_decision_report.pdf accessed 7 September 2026.<br />
<br />
5. Langdon Winner, 'Do Artifacts Have Politics?' (1980) 109(1) ''Daedalus'' 121, 128.<br />
<br />
6. Ibid. 123.<br />
<br />
7. OpenAI, Anthropic, Google DeepMind, Meta AI. xAI is an exception to the rule, domiciled between Palo Alto, CA and San Antonio, TX.<br />
<br />
8. Texas’ 17 to California’s 8, cf. Texas Royalty Brokers, 'AI Clusters by State' (''Texas Royalty Brokers'', 2025) https://texasroyaltybrokers.com/ai-clusters-by-state/ accessed 7 September 2026.<br />
<br />
9. The ‘rule of capture’, established in Houston & TC Railway Co v East (Tex 1904), permits landowners to extract groundwater beneath their land without liability for depleting adjacent wells or aquifers, a doctrine now exploited by hyperscale AI data centres to draw large cooling-water volumes with minimal regulatory constraint.<br />
<br />
10. Richard Barbrook and Andy Cameron, 'The Californian Ideology' (1996) 6(1) ''Science as Culture'' 44.<br />
<br />
11. Goldman Sachs, 'Global AI Investment Is Forecast to Exceed $1 Trillion in 2026' (''Goldman Sachs Insights'', 7 August 2026) https://www.goldmansachs.com/insights/articles/global-investment-is-forecast-to-exceed-1-trillion-in-2026 accessed 7 September 2026.<br />
<br />
12. &nbsp;National Science Foundation, 'Birth of the Commercial Internet' (''NSF Impacts'') https://www.nsf.gov/impacts/internet accessed 7 September 2026.<br />
<br />
13. CASRAI, 'NAIRR: National AI Research Resource, Explained' (''CASRAI'') https://casrai.org/dictionary/term/national-ai-research-resource-nairr accessed 7 September 2026.<br />
<br />
14. Council Regulation (EU) 2021/1173 of 13 July 2021 on establishing the European High Performance Computing Joint Undertaking and repealing Regulation (EU) 2018/1488 [2021] OJ L256/1.<br />
<br />
15. Council Regulation (EU) 2026/150 of 16 January 2026 amending Regulation (EU) 2021/1173 on establishing the European High Performance Computing Joint Undertaking [2026] OJ L 2026/150.<br />
<br />
16.&nbsp;European Commission, 'Realising Europe's Digital Decade' (''European Commission'', 11 October 2024) https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/story-von-der-leyen-commission/realising-europes-digital-decade_en accessed 7 September 2026.</div></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Platform_Dependence_in_Public_Communication_(News)_-_Ceren_Isiklar_%26_Rodrigue_Kayembe&diff=123598Platform Dependence in Public Communication (News) - Ceren Isiklar & Rodrigue Kayembe2026-09-08T15:14:26Z<p>Isiklar Ceren: </p>
<hr />
<div><p>8 September 2026 - Platform Dependence in Public Communication - Ceren and Rodrique (work in progress)</p><p>I.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PLATFORM DEPENDENCE IN PUBLIC COMMUNICATION – WHAT IS IT , WHO IS AFFECTED BY IT AND WHY IT MATTERS LEGALLY AND INSTITUTIONALLY – C</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Public communication is the conveyance of a message to a large group of people. This includes public announcements, advertisements in public spaces, social media broadcasts, news delivered in reporting, editorials, opinion pieces, and even political campaigns. Platform dependence is the reliance on a third party platform or digital infrastructure to reach the audience of the public communication, the public. Platform dependence in public communication therefore includes reliance on private companies like Meta (Facebook), state television channels, or telecommunications providers who provide and control access to, and develop the infrastructure of such platforms. For the purpose of this exercise, news will be utilized as the main example of public communication. News is the end result of the process of taking this information from one form to another, and transmitting to a wider, typically public audience is what we will anchor our definition of 'news' to be.&nbsp;</p><p>B.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Those who are affected by platform dependence in public communication are the communicators and the public alike. News outlets are mainly for-profit organizations. These organizations’ reliance on third party digital platforms grows day-by-day to maintain their popularity and engagement (such as on social media platforms) ultimately deciding the revenue generated from advertisers. The public on the other hand are provided catchier and more diluted information, gaining just enough knowledge to grab their attention while not being provided substantial knowledge on matters. Additionally,i members of the public who do not have the resources to access such platforms and digital services remain “information poor”. Digital rich, the virtual class of tech-professional and entrepreneurs benefit from the dependence to their platforms.</p><p>C.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This is crucial as platform dependence may threaten democracy and free political expression. Platforms, run by private parties, can be run according to their political beliefs. Social media platforms aiming to keep users online utilize algorithms that provide their users with their confirmed preferences, not allowing the conveyance of a truly heteregenious catalogue of news. The original ideal of the democratic electronic agora is undermined when private corporations control the flow of news and the infrastructure on which they are provided.</p><p>II.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HISTORICAL LINEAGE – HISTORICAL MOMENTS/DECISIONS/INSTITUTIONAL ARRANGEMENTS - R</p><p>&lt;span class="mwt-editable mwt-comment" id="R1788969355165" " draggable="false" contenteditable="true"&gt; obsidian</p><p>It is very difficult to discuss news without highlighting the deep entanglement it shares with information. For our purpose 'information' will have the following characteristics; it can be learned, processed, archived, and it's worth correlates to its rarity.<sup class="footnote-ref" data-footnote-id="fnref-1"></sup></p><br />
<br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-1 [1]]<p><sup class="footnote-ref" data-footnote-id="fnref-1"></sup>There is and has always been an obvious tension between the rarity that gives information its worth and the act of transmission that makes it less rare. Modern form of this can be traced to Renaissance Europe, <sup class="footnote-ref" data-footnote-id="fnref-2"></sup></p><br />
<br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-2 [2]]<p><sup class="footnote-ref" data-footnote-id="fnref-2"></sup>where a single innovation not only leaned on but also displaced established pattern of trusted networks collecting, processing and sharing news by way of the church, merchants, students, diplomats and so on. <sup class="footnote-ref" data-footnote-id="fnref-3"></sup></p><br />
<br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-3 [3]]<p>This innovation is the invention of printing in the 15th century. It had consequences beyond those imagined by its inventor, as it offered new possibilities for the dissemination of news. It must be reiterated that printing benefitted from the existing networks and not the other way around. This is evident by Johann Carolus' &nbsp;''Relation aller Fürnemmen und gedenckwürdigen Historien'' handwritten weekly newspaper for an elite audience fruitfully running prior to the advent of printing. However, the printing press coupled with existing network and infrastructure of the postal system brought industrialisation and scale unknown to the trade and the world at the time. One of the first paying customer for press was the Church, selling indulgences. Beniger's stands: control depends on information processing and communication working together. The printing press era had both ingredients, what could be published and the means of publishing.<sup class="footnote-ref" data-footnote-id="fnref-4"></sup></p><br />
<br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-4 [4]]<p><sup class="footnote-ref" data-footnote-id="fnref-4"></sup>'''Nonetheless, a strong parallel between the press and later computing revolutions it's stated relationship with state. '''<sup class="footnote-ref" data-footnote-id="fnref-5"></sup></p><br />
<br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-5 [5]]<p><sup class="footnote-ref" data-footnote-id="fnref-5"></sup>With the former seeming to lean more towards the state and the other in the opposite direction.</p><p>The next pivotal historical point which disturbs the way in which news is transmitted is by way of the radio. The radio is huge leap frog as it permitted the decoupling of reach from cost, reliance on aging network such as the postal system. Where the method of control under print was through the content printed, the radio moved closer to physics on licensing broadcast rights. This changed the trajectory of news as it birthed the state owned monopoly broadcaster, responsible for broadcasting news to anyone with a receiver on the other end within appropriate frequency. News outlets now had more than one method for distributing news and for the first time had a way of engaging in dialogue on the news of the day as it makes it way via print and sound-wave. Diversity of dependency is an important aspect of this stage in history.</p><p>III.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; MECHANISM OF PATH DEPENDENCE - C</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The public is generally partaking in consuming content on social media. Hence, with its 3 billion monthly active users for example, Instagram has an installed base for news outlets to depend upon (Instagram Revenue and Usage Statistics (2026), n.d.). The audiences of news outlets spend an increasing amount of their time on social media platforms, which gives results in a habitual entrenchment for these news outlets: the means of reaching the audience is dependent on their habits of content consumption. An indirect contractual entrenchment may also be discussed, as news outlets have obligations to their advertisers (who may request the upkeep of views/clicks on the news platforms they pay to advertise in). Cultural entrenchment should not be disregarded: the public expects to receive their news on social media platforms they readily frequent, and many news outlets meet this expectation. Hence, news outlets must partake in building a presence in social media platforms if they wish to compete.</p><p>IV.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; POLITICS AND DISTRIBUTION – WHOSE INTERESTS ARE STRENGTHENED AND WHO HAS FEWER CHOICES - C</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <span>Barbook argues that although the California Ideology claims that state power will be decreased and individuals will be empowered through decentralized networks enabled by digital technologies, he demonstrates that public communication is in fact not immune to undemocratic powers. These include private corporations: these corporations may gatekeep in choosing when and how to provide access to their platforms, while finetuning how users navigate their platforms. </span></p><p><span style="text-decoration: line-through;"></span>By enabling access to content that users tend to agree with, those who manage these platforms enable public opinion to shift to extremes. Being “fed” the same narrative and not being challenged to see an opposing perspective ultimately provides fewer choices to the consumer of the information, the general public. Therefore, individual agency is constrained by platform architecture and control, not liberated by it.</p><p>V.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; AT WHAT POINT IN HISTORY WAS A DIFFERENT TRAJECTORY POSSIBLE? - R</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; News not subscribing to / presenting news on social media as platform (?)</p><p>VI.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GOVERNANCE IMPLICATION – ONE PROPOSITION FOR CURRENT DAY GOVERNANCE - R</p><p>OPEN PLATFORMS (ALTERNATIVE FACEBOOK A)</p><section class="footnotes"><hr><br />
#<p>Mark Greengrass, Thierry Rentet and Stéphane Gal, ‘The Hinterland of the Newsletter: Handling Information in Space and Time’ in Joad Raymond and Noah Moxham (eds), News Networks in Early Modern Europe (Brill 2016)</p><br />
[http://www.jstor.org/stable/10.1163/j.ctt1w8h1ng.34 http://www.jstor.org/stable/10.1163/j.ctt1w8h1ng.34]<p>accessed 7 September 2026; ‘Michel Serres Prononce En Sorbonne La Conférence Inaugurale Du Programme Paris Nouveaux Mondes - La Chancellerie Des Universités de Paris’ (La Chancellerie des Universités de Paris, 1 January 2013)</p><br />
[https://www.sorbonne.fr/michel-serres-prononce-en-sorbonne-la-conference-inaugurale-du-programme-paris-nouveaux-mondes/ https://www.sorbonne.fr/michel-serres-prononce-en-sorbonne-la-conference-inaugurale-du-programme-paris-nouveaux-mondes/]<p>accessed 7 September 2026. James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986).</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-1 ↩︎]<br />
#<p>Brendan Dooley, Making News in Renaissance Europe (1st edn, Cambridge University Press 2026)</p><br />
[https://doi.org/10.1017/9781009358835 https://doi.org/10.1017/9781009358835]<p>.</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-2 ↩︎]<br />
#<p>Andrew Pettegree, The Invention of News: How the World Came to Know about Itself (Yale University Press 2014). Helmer Helmers, ‘Public Diplomacy in Early Modern Europe: Towards a New History of News’ (2016) 22 Media History 401</p><br />
[https://doi.org/10.1080/13688804.2016.1174570 https://doi.org/10.1080/13688804.2016.1174570]<p>.</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-3 ↩︎]<br />
#<p>James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986) P24-25</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-4 ↩︎]<br />
#<p>Richard Barbrook and Andy Cameron, The Californian Ideology (1996)</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-5 ↩︎]<br />
</section></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Platform_Dependence_in_Public_Communication_(News)_-_Ceren_Isiklar_%26_Rodrigue_Kayembe&diff=123597Platform Dependence in Public Communication (News) - Ceren Isiklar & Rodrigue Kayembe2026-09-08T15:11:14Z<p>Isiklar Ceren: </p>
<hr />
<div><p>8 September 2026 - Platform Dependence in Public Communication - Ceren and Rodrique (work in progress)</p><p>I.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PLATFORM DEPENDENCE IN PUBLIC COMMUNICATION – WHAT IS IT , WHO IS AFFECTED BY IT AND WHY IT MATTERS LEGALLY AND INSTITUTIONALLY – C</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Public communication is the conveyance of a message to a large group of people. This includes public announcements, advertisements in public spaces, social media broadcasts, news delivered in reporting, editorials, opinion pieces, and even political campaigns. Platform dependence is the reliance on a third party platform or digital infrastructure to reach the audience of the public communication, the public. Platform dependence in public communication therefore includes reliance on private companies like Meta (Facebook), state television channels, or telecommunications providers who provide and control access to, and develop the infrastructure of such platforms. For the purpose of this exercise, news will be utilized as the main example of public communication. News is the end result of the process of taking this information from one form to another, and transmitting to a wider, typically public audience is what we will anchor our definition of 'news' to be.&nbsp;</p><p>B.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Those who are affected by platform dependence in public communication are the communicators and the public alike. News outlets are mainly for-profit organizations. These organizations’ reliance on third party digital platforms grows day-by-day to maintain their popularity and engagement (such as on social media platforms) ultimately deciding the revenue generated from advertisers. The public on the other hand are provided catchier and more diluted information, gaining just enough knowledge to grab their attention while not being provided substantial knowledge on matters. Additionally,i members of the public who do not have the resources to access such platforms and digital services remain “information poor”. Digital rich, the virtual class of tech-professional and entrepreneurs benefit from the dependence to their platforms.</p><p>C.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This is crucial as platform dependence may threaten democracy and free political expression. Platforms, run by private parties, can be run according to their political beliefs. Social media platforms aiming to keep users online utilize algorithms that provide their users with their confirmed preferences, not allowing the conveyance of a truly heteregenious catalogue of news. The original ideal of the democratic electronic agora is undermined when private corporations control the flow of news and the infrastructure on which they are provided.</p><p>II.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HISTORICAL LINEAGE – HISTORICAL MOMENTS/DECISIONS/INSTITUTIONAL ARRANGEMENTS - R</p><p>&lt;span class="mwt-editable mwt-comment" id="R1788969355165" " draggable="false" contenteditable="true"&gt; obsidian</p><p>It is very difficult to discuss news without highlighting the deep entanglement it shares with information. For our purpose 'information' will have the following characteristics; it can be learned, processed, archived, and it's worth correlates to its rarity.<sup class="footnote-ref" data-footnote-id="fnref-1"></sup></p><br />
<br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-1 [1]]<p><sup class="footnote-ref" data-footnote-id="fnref-1"></sup>There is and has always been an obvious tension between the rarity that gives information its worth and the act of transmission that makes it less rare. Modern form of this can be traced to Renaissance Europe, <sup class="footnote-ref" data-footnote-id="fnref-2"></sup></p><br />
<br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-2 [2]]<p><sup class="footnote-ref" data-footnote-id="fnref-2"></sup>where a single innovation not only leaned on but also displaced established pattern of trusted networks collecting, processing and sharing news by way of the church, merchants, students, diplomats and so on. <sup class="footnote-ref" data-footnote-id="fnref-3"></sup></p><br />
<br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-3 [3]]<p>This innovation is the invention of printing in the 15th century. It had consequences beyond those imagined by its inventor, as it offered new possibilities for the dissemination of news. It must be reiterated that printing benefitted from the existing networks and not the other way around. This is evident by Johann Carolus' &nbsp;''Relation aller Fürnemmen und gedenckwürdigen Historien'' handwritten weekly newspaper for an elite audience fruitfully running prior to the advent of printing. However, the printing press coupled with existing network and infrastructure of the postal system brought industrialisation and scale unknown to the trade and the world at the time. One of the first paying customer for press was the Church, selling indulgences. Beniger's stands: control depends on information processing and communication working together. The printing press era had both ingredients, what could be published and the means of publishing.<sup class="footnote-ref" data-footnote-id="fnref-4"></sup></p><br />
<br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-4 [4]]<p><sup class="footnote-ref" data-footnote-id="fnref-4"></sup>'''Nonetheless, a strong parallel between the press and later computing revolutions it's stated relationship with state. '''<sup class="footnote-ref" data-footnote-id="fnref-5"></sup></p><br />
<br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-5 [5]]<p><sup class="footnote-ref" data-footnote-id="fnref-5"></sup>With the former seeming to lean more towards the state and the other in the opposite direction.</p><p>The next pivotal historical point which disturbs the way in which news is transmitted is by way of the radio. The radio is huge leap frog as it permitted the decoupling of reach from cost, reliance on aging network such as the postal system. Where the method of control under print was through the content printed, the radio moved closer to physics on licensing broadcast rights. This changed the trajectory of new's as it birth the state owned monopoly broadcaster, responsible for broadcasting news to anyone with a receiver on the other end within appropriate frequency. News outlet now had more than one method for distributing news and for the first time had a way of engaging in dialogue on the news of the day as it makes it way via print and sound-wave. Diversity of dependency is an important aspect of this stage in history.</p><p>III.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; MECHANISM OF PATH DEPENDENCE - C</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The public is generally partaking in consuming content on social media. Hence, with its 3 billion monthly active users for example, Instagram has an installed base for news outlets to depend upon (Instagram Revenue and Usage Statistics (2026), n.d.). The audiences of news outlets spend an increasing amount of their time on social media platforms, which gives results in a habitual entrenchment for these news outlets: the means of reaching the audience is dependent on their habits of content consumption. An indirect contractual entrenchment may also be discussed, as news outlets have obligations to their advertisers (who may request the upkeep of views/clicks on the news platforms they pay to advertise in). Cultural entrenchment should not be disregarded: the public expects to receive their news on social media platforms they readily frequent, and many news outlets meet this expectation. Hence, news outlets must partake in building a presence in social media platforms if they wish to compete.</p><p>IV.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; POLITICS AND DISTRIBUTION – WHOSE INTERESTS ARE STRENGTHENED AND WHO HAS FEWER CHOICES - C</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <span>Barbook argues that although the California Ideology claims that state power will be decreased and individuals will be empowered through decentralized networks enabled by digital technologies, he demonstrates that public communication is in fact not immune to undemocratic powers. These include private corporations: these corporations may gatekeep in choosing when and how to provide access to their platforms, while finetuning how users navigate their platforms. </span></p><p><span style="text-decoration: line-through;"></span>By enabling access to content that users tend to agree with, those who manage these platforms enable public opinion to shift to extremes. Being “fed” the same narrative and not being challenged to see an opposing perspective ultimately provides fewer choices to the consumer of the information, the general public. Therefore, individual agency is constrained by platform architecture and control, not liberated by it.</p><p>V.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; AT WHAT POINT IN HISTORY WAS A DIFFERENT TRAJECTORY POSSIBLE? - R</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; News not subscribing to / presenting news on social media as platform (?)</p><p>VI.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GOVERNANCE IMPLICATION – ONE PROPOSITION FOR CURRENT DAY GOVERNANCE - R</p><p>OPEN PLATFORMS (ALTERNATIVE FACEBOOK A)</p><section class="footnotes"><hr><br />
#<p>Mark Greengrass, Thierry Rentet and Stéphane Gal, ‘The Hinterland of the Newsletter: Handling Information in Space and Time’ in Joad Raymond and Noah Moxham (eds), News Networks in Early Modern Europe (Brill 2016)</p><br />
[http://www.jstor.org/stable/10.1163/j.ctt1w8h1ng.34 http://www.jstor.org/stable/10.1163/j.ctt1w8h1ng.34]<p>accessed 7 September 2026; ‘Michel Serres Prononce En Sorbonne La Conférence Inaugurale Du Programme Paris Nouveaux Mondes - La Chancellerie Des Universités de Paris’ (La Chancellerie des Universités de Paris, 1 January 2013)</p><br />
[https://www.sorbonne.fr/michel-serres-prononce-en-sorbonne-la-conference-inaugurale-du-programme-paris-nouveaux-mondes/ https://www.sorbonne.fr/michel-serres-prononce-en-sorbonne-la-conference-inaugurale-du-programme-paris-nouveaux-mondes/]<p>accessed 7 September 2026. James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986).</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-1 ↩︎]<br />
#<p>Brendan Dooley, Making News in Renaissance Europe (1st edn, Cambridge University Press 2026)</p><br />
[https://doi.org/10.1017/9781009358835 https://doi.org/10.1017/9781009358835]<p>.</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-2 ↩︎]<br />
#<p>Andrew Pettegree, The Invention of News: How the World Came to Know about Itself (Yale University Press 2014). Helmer Helmers, ‘Public Diplomacy in Early Modern Europe: Towards a New History of News’ (2016) 22 Media History 401</p><br />
[https://doi.org/10.1080/13688804.2016.1174570 https://doi.org/10.1080/13688804.2016.1174570]<p>.</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-3 ↩︎]<br />
#<p>James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986) P24-25</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-4 ↩︎]<br />
#<p>Richard Barbrook and Andy Cameron, The Californian Ideology (1996)</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-5 ↩︎]<br />
</section></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Platform_Dependence_in_Public_Communication_(News)_-_Ceren_Isiklar_%26_Rodrigue_Kayembe&diff=123592Platform Dependence in Public Communication (News) - Ceren Isiklar & Rodrigue Kayembe2026-09-08T15:02:55Z<p>Isiklar Ceren: </p>
<hr />
<div><p>8 September 2026 - Platform Dependence in Public Communication - Ceren and Rodrique (work in progress)</p><br />
<p>I.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PLATFORM DEPENDENCE IN PUBLIC COMMUNICATION – WHAT IS IT , WHO IS AFFECTED BY IT AND WHY IT MATTERS LEGALLY AND INSTITUTIONALLY – C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Public communication is the conveyance of a message to a large group of people. This includes public announcements, advertisements in public spaces, social media broadcasts, news delivered in reporting, editorials, opinion pieces, and even political campaigns. Platform dependence is the reliance on a third party platform or digital infrastructure to reach the audience of the public communication, the public. Platform dependence in public communication therefore includes reliance on private companies like Meta (Facebook), state television channels, or telecommunications providers who provide and control access to, and develop the infrastructure of such platforms. For the purpose of this exercise, news will be utilized as the main example of public communication. News is the end result of the process of taking this information from one form to another, and transmitting to a wider, typically public audience is what we will anchor our definition of 'news' to be.&nbsp;</p><br />
<p>B.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Those who are affected by platform dependence in public communication are the communicators and the public alike. News outlets are mainly for-profit organizations. These organizations’ reliance on third party digital platforms grows day-by-day to maintain their popularity and engagement (such as on social media platforms) ultimately deciding the revenue generated from advertisers. The public on the other hand are provided catchier and more diluted information, gaining just enough knowledge to grab their attention while not being provided substantial knowledge on matters. Additionally,i members of the public who do not have the resources to access such platforms and digital services remain “information poor”. Digital rich, the virtual class of tech-professional and entrepreneurs benefit from the dependence to their platforms.</p><br />
<p>C.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This is crucial as platform dependence may threaten democracy and free political expression. Platforms, run by private parties, can be run according to their political beliefs. Social media platforms aiming to keep users online utilize algorithms that provide their users with their confirmed preferences, not allowing the conveyance of a truly heteregenious catalogue of news. The original ideal of the democratic electronic agora is undermined when private corporations control the flow of news and the infrastructure on which they are provided.</p><br />
<p>II.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HISTORICAL LINEAGE – HISTORICAL MOMENTS/DECISIONS/INSTITUTIONAL ARRANGEMENTS - R</p><br />
<p>&lt;span class="mwt-editable mwt-comment" id="R1788969355165" " draggable="false" contenteditable="true"&gt; obsidian </p><br />
<p>It is very difficult to discuss news without highlighting the deep entanglement it shares with information. For our purpose 'information' will have the following characteristics; it can be learned, processed, archived, and it's worth correlates to its rarity.<sup class="footnote-ref" data-footnote-id="fnref-1"></sup></p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-1 [1]]<p><sup class="footnote-ref" data-footnote-id="fnref-1"></sup>There is and has always been an obvious tension between the rarity that gives information its worth and the act of transmission that makes it less rare. Modern form of this can be traced to Renaissance Europe, <sup class="footnote-ref" data-footnote-id="fnref-2"></sup></p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-2 [2]]<p><sup class="footnote-ref" data-footnote-id="fnref-2"></sup>where a single innovation not only leaned on but also displaced established pattern of trusted networks collecting, processing and sharing news by way of the church, merchants, students, diplomats and so on. <sup class="footnote-ref" data-footnote-id="fnref-3"></sup></p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-3 [3]]<p>This innovation is the invention of printing in the 15th century. It had consequences beyond those imagined by its inventor, as it offered new possibilities for the dissemination of news. It must be reiterated that printing benefitted from the existing networks and not the other way around. This is evident by Johann Carolus' &nbsp;''Relation aller Fürnemmen und gedenckwürdigen Historien'' handwritten weekly newspaper for an elite audience fruitfully running prior to the advent of printing. However, the printing press coupled with existing network and infrastructure of the postal system brought industrialisation and scale unknown to the trade and the world at the time. One of the first paying customer for press was the Church, selling indulgences. Beniger's stands: control depends on information processing and communication working together, and the this innovation at that current point time supplied both at once.<sup class="footnote-ref" data-footnote-id="fnref-4"></sup></p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-4 [4]]<p><sup class="footnote-ref" data-footnote-id="fnref-4"></sup>Nonetheless, a strong parallel between the press and later computing revolutions it's stated relationship with state. <sup class="footnote-ref" data-footnote-id="fnref-5"></sup></p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fn-5 [5]]<p><sup class="footnote-ref" data-footnote-id="fnref-5"></sup>With the former seeming to lean more towards the state and the other in the opposite direction.</p><br />
<p>The next pivotal historical point which disturbs the way in which news is transmitted is by way of the radio. The radio is huge leap frog as it permitted the decoupling of reach from cost, reliance on aging network such as the postal system. Where the method of control under print was through the content printed, the radio moved closer to physics on licensing broadcast rights. This changed the trajectory of new's as it birth the state owned monopoly broadcaster, responsible for broadcasting news to anyone with a receiver on the other end within appropriate frequency. News outlet now had more than one method for distributing news and for the first time had a way of engaging in dialogue on the news of the day as it makes it way via print and sound-wave. Diversity of dependency is an important aspect of this stage in history.</p><br />
<br />
<br />
<p>III.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; MECHANISM OF PATH DEPENDENCE - C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The public is generally partaking in consuming content on social media. Hence, with its 3 billion monthly active users for example, Instagram has an installed base for news outlets to depend upon (Instagram Revenue and Usage Statistics (2026), n.d.). The audiences of news outlets spend an increasing amount of their time on social media platforms, which gives results in a habitual entrenchment for these news outlets: the means of reaching the audience is dependent on their habits of content consumption. An indirect contractual entrenchment may also be discussed, as news outlets have obligations to their advertisers (who may request the upkeep of views/clicks on the news platforms they pay to advertise in). Cultural entrenchment should not be disregarded: the public expects to receive their news on social media platforms they readily frequent, and many news outlets meet this expectation. Hence, news outlets must partake in building a presence in social media platforms if they wish to compete.</p><br />
<p>IV.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; POLITICS AND DISTRIBUTION – WHOSE INTERESTS ARE STRENGTHENED AND WHO HAS FEWER CHOICES - C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <span>Barbook argues that although the California Ideology claims that state power will be decreased and individuals will be empowered through decentralized networks enabled by digital technologies, he demonstrates that public communication is in fact not immune to undemocratic powers. These include private corporations: these corporations may gatekeep in choosing when and how to provide access to their platforms, while finetuning how users navigate their platforms. </span></p><br />
<p><span style="text-decoration: line-through;"></span>By enabling access to content that users tend to agree with, those who manage these platforms enable public opinion to shift to extremes. Being “fed” the same narrative and not being challenged to see an opposing perspective ultimately provides fewer choices to the consumer of the information, the general public. Therefore, individual agency is constrained by platform architecture and control, not liberated by it.</p><br />
<p>V.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; AT WHAT POINT IN HISTORY WAS A DIFFERENT TRAJECTORY POSSIBLE? - R</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; News not subscribing to / presenting news on social media as platform (?)</p><br />
<p>VI.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GOVERNANCE IMPLICATION – ONE PROPOSITION FOR CURRENT DAY GOVERNANCE - R</p><br />
<p>OPEN PLATFORMS (ALTERNATIVE FACEBOOK A)</p><br />
<section class="footnotes"><hr><br />
#<p>Mark Greengrass, Thierry Rentet and Stéphane Gal, ‘The Hinterland of the Newsletter: Handling Information in Space and Time’ in Joad Raymond and Noah Moxham (eds), News Networks in Early Modern Europe (Brill 2016)</p><br />
[http://www.jstor.org/stable/10.1163/j.ctt1w8h1ng.34 http://www.jstor.org/stable/10.1163/j.ctt1w8h1ng.34]<p>accessed 7 September 2026; ‘Michel Serres Prononce En Sorbonne La Conférence Inaugurale Du Programme Paris Nouveaux Mondes - La Chancellerie Des Universités de Paris’ (La Chancellerie des Universités de Paris, 1 January 2013)</p><br />
[https://www.sorbonne.fr/michel-serres-prononce-en-sorbonne-la-conference-inaugurale-du-programme-paris-nouveaux-mondes/ https://www.sorbonne.fr/michel-serres-prononce-en-sorbonne-la-conference-inaugurale-du-programme-paris-nouveaux-mondes/]<p>accessed 7 September 2026. James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986).</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-1 ↩︎]<br />
#<p>Brendan Dooley, Making News in Renaissance Europe (1st edn, Cambridge University Press 2026)</p><br />
[https://doi.org/10.1017/9781009358835 https://doi.org/10.1017/9781009358835]<p>.</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-2 ↩︎]<br />
#<p>Andrew Pettegree, The Invention of News: How the World Came to Know about Itself (Yale University Press 2014). Helmer Helmers, ‘Public Diplomacy in Early Modern Europe: Towards a New History of News’ (2016) 22 Media History 401</p><br />
[https://doi.org/10.1080/13688804.2016.1174570 https://doi.org/10.1080/13688804.2016.1174570]<p>.</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-3 ↩︎]<br />
#<p>James Ralph Beniger, The Control Revolution: Technological and Economic Origins of the Information Society (Harvard Univ Press 1986) P24-25</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-4 ↩︎]<br />
#<p>Richard Barbrook and Andy Cameron, The Californian Ideology (1996)</p><br />
[https://wiki.ivir.nl/index.php?title=Platform_dependence_in_public_communication&action=tinymceedit#fnref-5 ↩︎]<br />
</section></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Platform_Dependence_in_Public_Communication_(News)_-_Ceren_Isiklar_%26_Rodrigue_Kayembe&diff=123565Platform Dependence in Public Communication (News) - Ceren Isiklar & Rodrigue Kayembe2026-09-07T20:21:40Z<p>Isiklar Ceren: </p>
<hr />
<div><p>8 September 2026 - Platform Dependence in Public Communication - Ceren and Rodrique (work in progress)</p><br />
<p>I.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PLATFORM DEPENDENCE IN PUBLIC COMMUNICATION – WHAT IS IT , WHO IS AFFECTED BY IT AND WHY IT MATTERS LEGALLY AND INSTITUTIONALLY – C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Public communication is the conveyance of a message to a large group of people. This includes public announcements, advertisements in public spaces, social media broadcasts, news delivered in reporting, editorials, opinion pieces, and even political campaigns. Platform dependence is the reliance on a third party platform or digital infrastructure to reach the audience of the public communication, the public. Platform dependence in public communication therefore includes reliance on private companies like Meta (Facebook), state television channels, or telecommunications providers who provide and control access to, and develop the infrastructure of such platforms. For the purpose of this exercise, news will be utilized as the main example of public communication.</p><br />
<p>B.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Those who are affected by platform dependence in public communication are the communicators and the public alike. News outlets are mainly for-profit organizations. These organizations’ reliance on third party digital platforms grows day-by-day to maintain their popularity and engagement (such as on social media platforms) ultimately deciding the revenue generated from advertisers. The public on the other hand are provided catchier and more diluted information, gaining just enough knowledge to grab their attention while not being provided substantial knowledge on matters. Additionally,i members of the public who do not have the resources to access such platforms and digital services remain “information poor”. Digital rich, the virtual class of tech-professional and entrepreneurs benefit from the dependence to their platforms.</p><br />
<p>C.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This is crucial as platform dependence may threaten democracy and free political expression. Platforms, run by private parties, can be run according to their political beliefs. Social media platforms aiming to keep users online utilize algorithms that provide their users with their confirmed preferences, not allowing the conveyance of a truly heteregenious catalogue of news. The original ideal of the democratic electronic agora is undermined when private corporations control the flow of news and the infrastructure on which they are provided.</p><br />
<p>II.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HISTORICAL LINEAGE – 3-5 HISTORICAL MOMENTS/DECISIONS/INSTITUTIONAL ARRANGEMENTS - R</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Spoken word – print press – radio & TV – Online on news site – news sites migrating to social media platforms and diluting and gamifying (making the title intriguing – catchy - algorithm). Newspapers have lost nuances and they are more clickbaity now, different writers had different voices. News are not provided by news outlets anymore but anyone with a microphone/keyboard.</p><br />
<p>III.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; MECHANISM OF PATH DEPENDENCE - C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The public is generally partaking in consuming content on social media. Hence, with its 3 billion monthly active users for example, Instagram has an installed base for news outlets to depend upon (Instagram Revenue and Usage Statistics (2026), n.d.). The audiences of news outlets spend an increasing amount of their time on social media platforms, which gives results in a habitual entrenchment for these news outlets: the means of reaching the audience is dependent on their habits of content consumption. An indirect contractual entrenchment may also be discussed, as news outlets have obligations to their advertisers (who may request the upkeep of views/clicks on the news platforms they pay to advertise in). Cultural entrenchment should not be disregarded: the public expects to receive their news on social media platforms they readily frequent, and many news outlets meet this expectation. Hence, news outlets must partake in building a presence in social media platforms if they wish to compete.</p><br />
<p>IV.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; POLITICS AND DISTRIBUTION – WHOSE INTERESTS ARE STRENGTHENED AND WHO HAS FEWER CHOICES - C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <span>Barbook argues that although the California Ideology claims that state power will be decreased and individuals will be empowered through decentralized networks enabled by digital technologies, he demonstrates that public communication is in fact not immune to undemocratic powers. These include private corporations: these corporations may gatekeep in choosing when and how to provide access to their platforms, while finetuning how users navigate their platforms. </span></p><br />
<p><span style="text-decoration: line-through;"></span>By enabling access to content that users tend to agree with, those who manage these platforms enable public opinion to shift to extremes. Being “fed” the same narrative and not being challenged to see an opposing perspective ultimately provides fewer choices to the consumer of the information, the general public. Therefore, individual agency is constrained by platform architecture and control, not liberated by it.</p><br />
<p>V.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; AT WHAT POINT IN HISTORY WAS A DIFFERENT TRAJECTORY POSSIBLE? - R</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; News not subscribing to / presenting news on social media as platform (?)</p><br />
<p>VI.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GOVERNANCE IMPLICATION – ONE PROPOSITION FOR CURRENT DAY GOVERNANCE - R</p><br />
<p>OPEN PLATFORMS (ALTERNATIVE FACEBOOK A)</p></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Platform_Dependence_in_Public_Communication_(News)_-_Ceren_Isiklar_%26_Rodrigue_Kayembe&diff=123564Platform Dependence in Public Communication (News) - Ceren Isiklar & Rodrigue Kayembe2026-09-07T19:54:16Z<p>Isiklar Ceren: </p>
<hr />
<div><p>8 September 2026 - Platform Dependence in Public Communication - Ceren and Rodrique (work in progress)</p><br />
<p>I.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PLATFORM DEPENDENCE IN PUBLIC COMMUNICATION – WHAT IS IT , WHO IS AFFECTED BY IT AND WHY IT MATTERS LEGALLY AND INSTITUTIONALLY – C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Public communication is the conveyance of a message to a large group of people. This includes public announcements, advertisements in public spaces, social media broadcasts, news delivered in reporting, editorials, opinion pieces, and even political campaigns. Platform dependence is the reliance on a third party platform or digital infrastructure to reach the audience of the public communication, the public. Platform dependence in public communication therefore includes reliance on private companies like Meta (Facebook), state television channels, or telecommunications providers who provide and control access to, and develop the infrastructure of such platforms. For the purpose of this exercise, news will be utilized as the main example of public communication.</p><br />
<p>B.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Those who are affected by platform dependence in public communication are the communicators and the public alike. News outlets are mainly for-profit organizations. These organizations’ reliance on third party digital platforms grows day-by-day to maintain their popularity and engagement (such as on social media platforms) ultimately deciding the revenue generated from advertisers. The public on the other hand are provided catchier and more diluted information, gaining just enough knowledge to grab their attention while not being provided substantial knowledge on matters. Additionally,i members of the public who do not have the resources to access such platforms and digital services remain “information poor”. Digital rich, the virtual class of tech-professional and entrepreneurs benefit from the dependence to their platforms.</p><br />
<p>C.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This is crucial as platform dependence may threaten democracy and free political expression. Platforms, run by private parties, can be run according to their political beliefs. Social media platforms aiming to keep users online utilize algorithms that provide their users with their confirmed preferences, not allowing the conveyance of a truly heteregenious catalogue of news. The original ideal of the democratic electronic agora is undermined when private corporations control the flow of news and the infrastructure on which they are provided.</p><br />
<p>II.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HISTORICAL LINEAGE – 3-5 HISTORICAL MOMENTS/DECISIONS/INSTITUTIONAL ARRANGEMENTS - R</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Spoken word – print press – radio & TV – Online on news site – news sites migrating to social media platforms and diluting and gamifying (making the title intriguing – catchy - algorithm). Newspapers have lost nuances and they are more clickbaity now, different writers had different voices. News are not provided by news outlets anymore but anyone with a microphone/keyboard.</p><br />
<p>III.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; MECHANISM OF PATH DEPENDENCE - C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Network effect. Installed base. Habitual entrenchment. Contractual entrenchment / financial obligations (advertisers requesting the upkeep of # of views/clicks). Culturally if every other outlet is doing it then you want to be included.</p><br />
<p>IV.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; POLITICS AND DISTRIBUTION – WHOSE INTERESTS ARE STRENGTHENED AND WHO HAS FEWER CHOICES - C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <span style="text-decoration: line-through;">Barbook argues that although the California Ideology claims that state power will be decreased and individuals will be empowered through decentralized networks enabled by digital technologies, he demonstrates that public communication is dependent on certain mechanisms. These are: state subsidization: internet could be invented with the aid of the state. Minitel &nbsp;- first successful public interactive network – was created through immense investment by the french government.</span></p><br />
<p><span style="text-decoration: line-through;">&nbsp;corporate gatekeeping: microsoft controlled access points – delayed 95’s launch so that community participations in the cyberspace could be included and such programs were not yet launched. Hence, a libertarian capitalist depended on state intervention.</span></p><br />
<p><span style="text-decoration: line-through;">ideological filtering: platforms enforce ideological boundaries. </span>ENCOURAGES / ENABLES EXTREMITY ON ALL SIDES – BEING FED THE SAME NARRATIVE AND NOT BEING CHALLENGED TO SEE ANOTHER PERSPECTIVE. CONSUMER HAS FEWER CHOICES</p><br />
<p>Individual agency is constrained by platform architecture and control, not liberated by it.</p><br />
<p>B.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Cybernetics – communication and control</p><br />
<p>Cyernetic concept hetertarchy – third and alternative way between market and hierarchy.</p><br />
<p>C.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Inventing the Internet: predecessor arpanet. US Department of Defense’s Research projects Agency founded this. Originally aimed to ease researchers running projects on remote computers. Design of arpanet and theinternet favored military values such as survivability, flexibility and high performance, over commercial goals like low cost, simplicity and consunmer appeal. &nbsp;</p><br />
<p>Packet switching US v UK: US —&gt; ( Baran) The need for survivable comunications – us military was working on it during cold war in case of russia strike. UK—&gt; affordability and commercial use (Davies).</p><br />
<p>V.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; AT WHAT POINT IN HISTORY WAS A DIFFERENT TRAJECTORY POSSIBLE? - R</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; News not subscribing to / presenting news on social media as platform (?)</p><br />
<p>VI.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GOVERNANCE IMPLICATION – ONE PROPOSITION FOR CURRENT DAY GOVERNANCE - R</p><br />
<p>OPEN PLATFORMS (ALTERNATIVE FACEBOOK A)</p></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Platform_Dependence_in_Public_Communication_(News)_-_Ceren_Isiklar_%26_Rodrigue_Kayembe&diff=123563Platform Dependence in Public Communication (News) - Ceren Isiklar & Rodrigue Kayembe2026-09-07T19:43:40Z<p>Isiklar Ceren: </p>
<hr />
<div><p>DATE</p><br />
<p>Platform Dependence in Public Communication</p><br />
<p>I.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PLATFORM DEPENDENCE IN PUBLIC COMMUNICATION – WHAT IS IT , WHO IS AFFECTED BY IT AND WHY IT MATTERS LEGALLY AND INSTITUTIONALLY – C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Public communication is the conveyance of a message to a large group of people. This includes public announcements, advertisements in public spaces, social media broadcasts, news delivered in reporting, editorials, opinion pieces, and even political campaigns. Platform dependence is the reliance on a third party platform or digital infrastructure to reach the audience of the public communication, the public. Platform dependence in public communication therefore includes reliance on private companies like Meta (Facebook), state television channels, or telecommunications providers who provide and control access to, and develop the infrastructure of such platforms. For the purpose of this exercise, news will be utilized as the main example of public communication.</p><br />
<p>B.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Those who are affected by platform dependence in public communication are the communicators and the public alike. The information poor are affected- they may not have access to digital services. Digital rich benefit ( the virtual class of tech professional and entrepreneurs).</p><br />
<p>C.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This matters legally and institutionally because – democratic institutions can be affected since platform dependence threatens democracy and free political expression. The original ideal of the democratic electronic agora is undermined when private corporations control the infrastructure.</p><br />
<p>II.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HISTORICAL LINEAGE – 3-5 HISTORICAL MOMENTS/DECISIONS/INSTITUTIONAL ARRANGEMENTS - R</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Spoken word – print press – radio & TV – Online on news site – news sites migrating to social media platforms and diluting and gamifying (making the title intriguing – catchy - algorithm). Newspapers have lost nuances and they are more clickbaity now, different writers had different voices. News are not provided by news outlets anymore but anyone with a microphone/keyboard.</p><br />
<p>III.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; MECHANISM OF PATH DEPENDENCE - C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Network effect. Installed base. Habitual entrenchment. Contractual entrenchment / financial obligations (advertisers requesting the upkeep of # of views/clicks). Culturally if every other outlet is doing it then you want to be included.</p><br />
<p>IV.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; POLITICS AND DISTRIBUTION – WHOSE INTERESTS ARE STRENGTHENED AND WHO HAS FEWER CHOICES - C</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <span style="text-decoration: line-through;">Barbook argues that although the California Ideology claims that state power will be decreased and individuals will be empowered through decentralized networks enabled by digital technologies, he demonstrates that public communication is dependent on certain mechanisms. These are: state subsidization: internet could be invented with the aid of the state. Minitel &nbsp;- first successful public interactive network – was created through immense investment by the french government.</span></p><br />
<p><span style="text-decoration: line-through;">&nbsp;corporate gatekeeping: microsoft controlled access points – delayed 95’s launch so that community participations in the cyberspace could be included and such programs were not yet launched. Hence, a libertarian capitalist depended on state intervention.</span></p><br />
<p><span style="text-decoration: line-through;">ideological filtering: platforms enforce ideological boundaries. </span>ENCOURAGES / ENABLES EXTREMITY ON ALL SIDES – BEING FED THE SAME NARRATIVE AND NOT BEING CHALLENGED TO SEE ANOTHER PERSPECTIVE. CONSUMER HAS FEWER CHOICES</p><br />
<p>Individual agency is constrained by platform architecture and control, not liberated by it.</p><br />
<p>B.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Cybernetics – communication and control</p><br />
<p>Cyernetic concept hetertarchy – third and alternative way between market and hierarchy.</p><br />
<p>C.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Inventing the Internet: predecessor arpanet. US Department of Defense’s Research projects Agency founded this. Originally aimed to ease researchers running projects on remote computers. Design of arpanet and theinternet favored military values such as survivability, flexibility and high performance, over commercial goals like low cost, simplicity and consunmer appeal. &nbsp;</p><br />
<p>Packet switching US v UK: US —&gt; ( Baran) The need for survivable comunications – us military was working on it during cold war in case of russia strike. UK—&gt; affordability and commercial use (Davies).</p><br />
<p>V.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; AT WHAT POINT IN HISTORY WAS A DIFFERENT TRAJECTORY POSSIBLE? - R</p><br />
<p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; News not subscribing to / presenting news on social media as platform (?)</p><br />
<p>VI.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GOVERNANCE IMPLICATION – ONE PROPOSITION FOR CURRENT DAY GOVERNANCE - R</p><br />
<p>OPEN PLATFORMS (ALTERNATIVE FACEBOOK A)</p></div>Isiklar Cerenhttps://wiki.ivir.nl/index.php?title=Platform_Dependence_in_Public_Communication_(News)_-_Ceren_Isiklar_%26_Rodrigue_Kayembe&diff=123562Platform Dependence in Public Communication (News) - Ceren Isiklar & Rodrigue Kayembe2026-09-07T17:19:02Z<p>Isiklar Ceren: </p>
<hr />
<div><p>DATE</p><p>Platform Dependence in Public Communication</p><p>I.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PLATFORM DEPENDENCE IN PUBLIC COMMUNICATION – WHAT IS IT , WHO IS AFFECTED BY IT AND WHY IT MATTERS LEGALLY AND INSTITUTIONALLY – C</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Platform dependence is the reliance on private companies like microsoft or telecommunications providers to control access to / develop digital communication infrastucture.</p><p>B.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The information poor are affected- they may not have access to digital services. Digital rich benefit ( the virtual class of tech professional and entrepreneurs).</p><p>C.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This matters legally and institutionally because – democratic institutions can be affected since platform dependence threatens democracy and free political expression. The original ideal of the democratic electronic agora is undermined when private corporations control the infrastructure.</p><p>II.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; HISTORICAL LINEAGE – 3-5 HISTORICAL MOMENTS/DECISIONS/INSTITUTIONAL ARRANGEMENTS - R</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Spoken word – print press – radio & TV – Online on news site – news sites migrating to social media platforms and diluting and gamifying (making the title intriguing – catchy - algorithm). Newspapers have lost nuances and they are more clickbaity now, different writers had different voices. News are not provided by news outlets anymore but anyone with a microphone/keyboard.</p><p>III.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; MECHANISM OF PATH DEPENDENCE - C</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Network effect. Installed base. Habitual entrenchment. Contractual entrenchment / financial obligations (advertisers requesting the upkeep of # of views/clicks). Culturally if every other outlet is doing it then you want to be included.</p><p>IV.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; POLITICS AND DISTRIBUTION – WHOSE INTERESTS ARE STRENGTHENED AND WHO HAS FEWER CHOICES - C</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <span style="text-decoration: line-through;" >Barbook argues that although the California Ideology claims that state power will be decreased and individuals will be empowered through decentralized networks enabled by digital technologies, he demonstrates that public communication is dependent on certain mechanisms. These are: state subsidization: internet could be invented with the aid of the state. Minitel &nbsp;- first successful public interactive network – was created through immense investment by the french government.</span></p><p><span style="text-decoration: line-through;" >&nbsp;corporate gatekeeping: microsoft controlled access points – delayed 95’s launch so that community participations in the cyberspace could be included and such programs were not yet launched. Hence, a libertarian capitalist depended on state intervention.</span></p><p><span style="text-decoration: line-through;" >ideological filtering: platforms enforce ideological boundaries. </span>ENCOURAGES / ENABLES EXTREMITY ON ALL SIDES – BEING FED THE SAME NARRATIVE AND NOT BEING CHALLENGED TO SEE ANOTHER PERSPECTIVE. CONSUMER HAS FEWER CHOICES</p><p>Individual agency is constrained by platform architecture and control, not liberated by it.</p><p>B.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Cybernetics – communication and control</p><p>Cyernetic concept hetertarchy – third and alternative way between market and hierarchy.</p><p>C.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Inventing the Internet: predecessor arpanet. US Department of Defense’s Research projects Agency founded this. Originally aimed to ease researchers running projects on remote computers. Design of arpanet and theinternet favored military values such as survivability, flexibility and high performance, over commercial goals like low cost, simplicity and consunmer appeal. &nbsp;</p><p>Packet switching US v UK: US —&gt; ( Baran) The need for survivable comunications – us military was working on it during cold war in case of russia strike. UK—&gt; affordability and commercial use (Davies).</p><p>V.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; AT WHAT POINT IN HISTORY WAS A DIFFERENT TRAJECTORY POSSIBLE? - R</p><p>A.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; News not subscribing to / presenting news on social media as platform (?)</p><p>VI.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; GOVERNANCE IMPLICATION – ONE PROPOSITION FOR CURRENT DAY GOVERNANCE - R</p><p>OPEN PLATFORMS (ALTERNATIVE FACEBOOK A)</p></div>Isiklar Ceren