Governance approaches grounded in development-rights / digital-self-determination / Global-South-sovereignty arguments rather than EU/US risk-based framings. Loudest in Brazil, India, ASEAN, African Union policy discourse.
Definition & scope
The cross-jurisdiction picture below shows how each of 45 tracked instruments treats this topic. The patterns vary substantially — and 34 regimes are silent, leaving gaps that future policy work could address.
Definitional contestation
"Development-rights framing" is an umbrella the article uses for several doctrines the scholarship treats as analytically distinct, and conflating them obscures what an instrument is doing. At least four strands recur. (1) The "right to development" / inclusive-growth strand grounds AI governance in equitable benefit-sharing and the 2030 Agenda — the register of A/RES/78/265 and Brazil's PL 2338/2023 "inclusive growth, sustainable development and well-being" (Art. 3 I). (2) Data colonialism, after Couldry and Mejias 1, is a critical-theoretic diagnosis of an extractive order appropriating human life as data — a critique, not a prescription; cognate decolonial work reads AI through the "colonial matrix of power" 2. (3) Data sovereignty concerns a state's meaningful control over the infrastructure, data and software it depends on, often operationalised as localisation 3. (4) Digital self-determination is narrower and rights-of-the-person centred, extending beyond data location to "data about oneself" and consent 4. These are not interchangeable: a state can pursue data sovereignty while doing little for individual self-determination, and the decolonial critique does not entail any sovereign remedy — so coding an instrument "governs" on inclusive-growth language while it is silent on sovereignty is a classification hazard the per-cell verdicts should be read against.
Regulatory approaches
Where instruments engage this topic, they do so through a small set of recurring modalities rather than a shared mechanism. The dominant modality is hortatory principle-and-preamble: founding-principles clauses naming development as an object of the regime. Brazil's PL 2338/2023 lists "inclusive growth, sustainable development and well-being" and "self-determination" among its Art. 3 principles, even as the operative architecture is a risk-tiered design modelled on the EU AI Act (OECD.AI policy profile, Bill No. 2338 of 2023). A second modality is the soft-law capacity-building obligation: the China-led UN GA resolution (1 July 2024) urges "expanding public and private investment" so developing countries can "share the dividends of AI development," while the US-led A/RES/78/265 (21 March 2024) commits to "closing the AI divides … between and within countries" — scholarship frames such capacity-building as the route to meaningful Global-South participation in standard-setting 5. A third, harder-edged modality is data-flow control as a sovereignty instrument — though India's DPDP Act 2023 retreated from mandatory localisation to a "negative list" under § 16, permitting cross-border transfer by default. A fourth is strategy-document framing without binding text, exemplified by the African Union Continental AI Strategy (2024), whose "Africa-owned, people-centred, development-oriented" priorities track scholarship warning that reliance on non-African frameworks undermines local inclusivity 6.
Key fault lines
The genuine disagreements run deeper than a single open question. First, even at the UN the framing split: 2024 produced two consensus resolutions — the US-led A/RES/78/265 emphasising safe, trustworthy systems for sustainable development, and a China-led capacity-building resolution co-sponsored by a Global-South-plus coalition foregrounding investment, technology transfer and bridging the divide. Commentators read the pairing as competing emphases — rights-and-safety versus development-and-access — rather than settled consensus, echoing critiques that "ethical AI" guidelines create de facto norms weak on inequality 7. Second is the Brussels-effect dispute: critics argue the EU AI Act's extraterritorial reach (Art. 2(1)(c)) exports priorities to states that did not shape them — a tension scholarship situates within the "paradox of participation" facing Global-South actors in AI governance 8. Third is whether the frame is a critique or a tested prescription: the extraction it names is empirically anchored, but cost evidence on its commonest proxy, data localisation, points the other way — Ferracane and van der Marel (2021) and Bauer et al. (2014) associate restrictions with lower productivity 9, while comparative work finds states pursue divergent digital-sovereignty models shaped by distinct development trajectories 10, and no study shows sovereignty framing advances local AI capability. The compatibility of development-rights framing with the EU's rights-based design therefore remains genuinely contested, not merely open.
Coverage across jurisdictions
Historical primacy & cross-jurisdiction tension
First addressed by OECD AI Principles (Recommendation) on (implicit). Subsequent regimes have either codified, diverged from, or remained silent on this baseline.
- Forum-shoppingUN GA Resolution on Safe, Secure, Trustworthy AI↔EU AI Act
- Forum-shoppingIndia Digital Personal Data Protection Act + AI Advisory (MEITY)↔Executive Order 14110 on Safe, Secure, Trustworthy AI
- Forum-shoppingBrazil AI Bill (PL 2338/2023)↔Executive Order 14179 — Removing Barriers to American Leadership in AI
Compare jurisdictions: EU vs US · EU vs UK · EU vs CN
Enforcement & impact
Silent regimes — gap signal
Instruments that do not address Development-Rights Framings — candidates for future policy work.
- EU AI ActEU
- Executive Order 14110 on Safe, Secure, Trustworthy AIUS
- Executive Order 14179 — Removing Barriers to American Leadership in AIUS
- UK Pro-Innovation Approach to AI Regulation (White Paper)UK
- G7 Hiroshima AI Process Code of ConductG7
- NIST AI Risk Management FrameworkUS
- Bletchley Declaration on AI Safetyglobal
- Seoul Declaration on Safe, Innovative and Inclusive AIglobal
- NIST AI RMF Generative AI ProfileUS
- California SB-1047: Safe and Secure Innovation for Frontier AI Models ActUS
- Anthropic Responsible Scaling Policy (RSP) v2US
- OpenAI Preparedness FrameworkUS
- Google DeepMind Frontier Safety FrameworkUS
- Meta Frontier AI FrameworkUS
- UK-US AI Safety Institute Memorandum of Understandingglobal
- White House Voluntary AI CommitmentsUS
- Singapore Model AI Governance Framework for Generative AISG
- Japan METI AI Guidelines for BusinessJP
- General Data Protection Regulation (GDPR)EU
- EU General-Purpose AI Code of PracticeEU
- OMB Memorandum M-24-10 (Advancing Governance, Innovation, and Risk Management for Agency Use of AI)US
- GSA Generative AI and Specialized Computing Infrastructure Acquisition Resource GuideUS
- DoD Responsible AI Strategy and Implementation PathwayUS
- FedRAMP AI Cloud Procurement GuidanceUS
- DFARS Subpart 252.204 (Safeguarding Covered Defense Information and Cyber Incident Reporting)US
- California SB-53: Transparency in Frontier Artificial Intelligence Act (TFAIA)US
- California SB 243: Companion ChatbotsUS
- California SB 942: AI Transparency ActUS
- Revised Product Liability Directive (Directive (EU) 2024/2853)EU
- Directive (EU) 2024/2831 on improving working conditions in platform workEU
- Provisions on the Administration of Deep Synthesis of Internet Information ServicesCN
- New York RAISE Act: Responsible AI Safety and Education ActUS
- TAKE IT DOWN Act (Tools to Address Known Exploitation by Immobilizing Technological Deepfakes on Websites and Networks Act)US
- Italy Law No. 132/2025 on Artificial Intelligence (Legge 23 settembre 2025, n. 132)IT
See also
Further reading
21 academic & grey-literature sources bearing on this topic — catalogued metadata with a primary link; one-line findings are ✦ AI-generated summaries, labeled as such (charter §7.9). Browse the full literature index.
- A Framework for Evaluating Global AI Governance Initiatives Peer-reviewed✦ AIOffers a framework to evaluate global AI governance initiatives, recommending capacity-building so Global South states can meaningfully participate in standard-setting.
- Large language models reflect the ideology of their creators Peer-reviewed✦ AIEmpirically shows LLMs encode their creators' ideologies, supporting policy incentives for home-grown models reflecting local cultural views, especially in low-resource-language regions.
- "We know what we are doing": the politics and trends in artificial intelligence policies in Africa Peer-reviewed✦ AIMaps the political drivers and trends of emerging African national AI policies, situating sovereignty and development framings against external dependency.
- Latin American critical data studies Peer-reviewed✦ AISurveys Latin American critical data studies, advancing concepts of statistical, epistemic and national sovereignty as decolonial framings for AI/data governance.
- The ethics of AI or techno-solutionism? UNESCO's policy guidance on AI in education Peer-reviewed✦ AICritiques UNESCO's AI-in-education guidance as techno-solutionism that can facilitate Big Tech access to Global South education under a 'capacity development' framing.
- Compute North vs. Compute South: The Uneven Possibilities of Compute-based AI Governance Around the Globe Peer-reviewed✦ AICensus of hyperscale cloud regions shows a divide between "Compute North" states hosting training-relevant compute and a Compute South, shaping who can wield compute-based governance.
- Models of State Digital Sovereignty From the Global South: Diverging Experiences From China, India and South Africa Peer-reviewed✦ AIComparative analysis finds China, India and South Africa pursue divergent state digital-sovereignty models shaped by distinct development trajectories and rights regimes.
- Toward a trustworthy and inclusive data governance policy for the use of artificial intelligence in Africa Peer-reviewed✦ AIProposes five design principles for African-centred AI data governance, warning that reliance on non-African frameworks undermines local and regional inclusivity.
- Artificial Intelligence in the Colonial Matrix of Power Peer-reviewed✦ AITheorizes AI through Quijano's 'colonial matrix of power', showing global production imbalances extract value from majority-world labor for Northern firms.
- Designing artificial intelligence policy: Comparing design spaces in Latin America Peer-reviewed✦ AICompares AI policy 'design spaces' across Latin American states, showing how development and capacity constraints shape divergent governance choices.
- At the Tensions of South and North: Critical Roles of Global South Stakeholders in AI Governance Peer-reviewed✦ AIMaps Global South-centred AI-governance discourse and the paradox of participation, offering 'three roles for Global South actors to substantively engage in AI governance processes.'
- Emerging Consensus on 'Ethical AI': Human Rights Critique of Stakeholder Guidelines Peer-reviewed✦ AIHuman-rights audit of 15 'ethical AI' guidelines finds they create 'a set of de facto norms' that re-interpret human rights, are weak on inequality, and lack enforceable accountability.
- Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence Peer-reviewed✦ AIArgues 'post-colonial and decolonial theories' should shape AI's advance as sociotechnical foresight, proposing critical technical practice and reverse tutelage to protect vulnerable populations.
- Algorithmic Colonization of Africa Peer-reviewed✦ AIArgues Western tech monopolies practice 'algorithmic colonialism' in Africa, with profit-driven AI solutions reproducing colonial power asymmetries.
- Data Colonialism: Rethinking Big Data's Relation to the Contemporary Subject Peer-reviewed✦ AITheorizes 'data colonialism' as a new extractive order that normalizes appropriating human life through 'data relations,' enabling 'the capitalization of life without limit.'
- Balancing the tradeoff between regulation and innovation for artificial intelligence: command-and-control vs self-regulatory approaches Peer-reviewed✦ AICompares top-down command-and-control vs bottom-up self-regulatory AI governance, analysing the regulation-vs-innovation tradeoff a deregulatory order resolves toward removing barriers.
- Position Paper: If Innovation in AI Systematically Violates Fundamental Rights, Is It Innovation at All? Preprint✦ AIArgues regulation is the foundation of AI innovation rather than its brake (accepted, NeurIPS 2025 position-paper track).
- AI, Global Governance, and Digital Sovereignty Preprint✦ AITheorises digital sovereignty as entangled with institutional control over AI infrastructure and sovereign competence.
- The digital labour of artificial intelligence in Latin America: Argentina, Brazil, and Venezuela Preprint✦ AISurvey and interviews of 911 precarious AI data workers across Argentina, Brazil and Venezuela (the data-colonialism strand).
- Technology and Innovation Report 2025: Inclusive Artificial Intelligence for Development Official (grey)✦ AIFlagship inclusive-AI-for-development report: 118 mostly-Global-South countries absent from AI governance; infrastructure, data and skills divides.
- Emerging divides in the transition to artificial intelligence (OECD Regional Development Papers No. 147) Working paper✦ AIWorking paper measuring how 2023-24 AI adoption reinforces existing divides across places and firms.
References
Sources cited inline in the analysis (linked from the superscript markers), then the primary instrument sources behind the classifications.
- Nick Couldry, Ulises A. Mejias (2019) Data Colonialism: Rethinking Big Data's Relation to the Contemporary Subject, Television & New Media. 10.1177/1527476418796632 — Theorizes 'data colonialism' as a new extractive order that normalizes appropriating human life through 'data relations,' enabling 'the capitalization of life without limit.' ↩
- James Muldoon, Boxi A. Wu (2023) Artificial Intelligence in the Colonial Matrix of Power, Philosophy & Technology. 10.1007/s13347-023-00687-8 — Theorizes AI through Quijano's 'colonial matrix of power', showing global production imbalances extract value from majority-world labor for Northern firms. ↩
- Swati Srivastava, Justin Bullock AI, Global Governance, and Digital Sovereignty. arXiv:2410.17481 — Theorises digital sovereignty as entangled with institutional control over AI infrastructure and sovereign competence. ↩
- Patrik Hummel, Matthias Braun, Max Tretter, Peter Dabrock (2021) Data sovereignty: A review, Big Data & Society. source — Systematic review of 341 publications maps how data, digital and cyber sovereignty are conceptualized and the control challenges they pose across stakeholders. ↩
- Huw Roberts, Mariarosaria Taddeo, Luciano Floridi (2026) A Framework for Evaluating Global AI Governance Initiatives, Global Policy. 10.1111/1758-5899.70164 — Offers a framework to evaluate global AI governance initiatives, recommending capacity-building so Global South states can meaningfully participate in standard-setting. ↩
- Jake Okechukwu Effoduh, Ugochukwu Ejike Akpudo, Jude Dzevela Kong (2024) Toward a trustworthy and inclusive data governance policy for the use of artificial intelligence in Africa, Data & Policy. 10.1017/dap.2024.26 — Proposes five design principles for African-centred AI data governance, warning that reliance on non-African frameworks undermines local and regional inclusivity. ↩
- Sakiko Fukuda-Parr, Elizabeth Gibbons (2021) Emerging Consensus on 'Ethical AI': Human Rights Critique of Stakeholder Guidelines, Global Policy. 10.1111/1758-5899.12965 — Human-rights audit of 15 'ethical AI' guidelines finds they create 'a set of de facto norms' that re-interpret human rights, are weak on inequality, and lack enforceable accountability. ↩
- Marie-Therese Png (2022) At the Tensions of South and North: Critical Roles of Global South Stakeholders in AI Governance, ACM FAccT. 10.1145/3531146.3533200 — Maps Global South-centred AI-governance discourse and the paradox of participation, offering 'three roles for Global South actors to substantively engage in AI governance processes.' ↩
- 10.1007/s10290-021-00417-2 ↩
- Min Jiang (2024) Models of State Digital Sovereignty From the Global South: Diverging Experiences From China, India and South Africa, Policy & Internet. 10.1002/poi3.427 — Comparative analysis finds China, India and South Africa pursue divergent state digital-sovereignty models shaped by distinct development trajectories and rights regimes. ↩
- CN-GENAI-2023: PRC has invoked development rights in UN AI debates (2024 GA)
- OECD-AI-PRIN: Principle 1.1 'inclusive growth' brushes against development-rights framing
- COE-AI-CONV: Rights-based framing partly overlaps with development-rights doctrine but not explicitly
- UN-RES-2024: Operative paragraphs frame AI through development-rights + digital divide lens; co-sponsored by Global-South coalition
- IN-DPDP-2023: Digital India framing centres development rights + tech-sovereignty; explicit in DPDPA preamble + MEITY's AI Mission documents
- BR-AIBILL-2024: PL 2338/2023 Arts. 3-4 (founding principles include 'sustainable development' + 'human dignity' — distinct from EU AIA's rights-only framing)
- ASEAN-AI-GUIDE-2024: Guide centres 'pragmatic + flexible' implementation reflecting member-state development trajectories
- AU-AI-STRATEGY-2024: AU Strategy §§1-3 (AI as continental development priority + data-coloniality framing)
- UNESCO-AI-ETHICS-2021: Policy Area 'Development and International Cooperation', para 79 (+ Diversity Principle para 67) — AI-for-development bound to the values/principles
- JP-AIPROMO-2025: Act No. 53 of 2025, Arts. 1 & 3(3)
- UN-GDC-2024: GDC Objective 5, para 55(c) and capacity-building partnerships (A/RES/79/1, Annex I)
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11 instruments tracked.
Does governance work? — the social-science evidence
What the peer-reviewed social science shows: whether the harm this topic addresses is empirically real, and whether governance of it works. The badge is the epistemic status of the evidence(not the policy debate) — “thin” or “absent” efficacy evidence is itself a finding (the “second silence”). Each epistemic-status label is Policy Window's editorial assessment of the cited evidence base (a structured classification), not a verdict any single source issues.
Development-rights framing is a normative/doctrinal frame, so its empirical status splits: the underlying North-South asymmetry it responds to is real and documented, but the claim that a development-rights diagnosis is the correct one is contested doctrine, not a settled finding. The strongest empirical anchor is the exploitative-data-labour evidence — Miceli & Posada's (2022) multi-method qualitative study of Latin American annotation work (Foucauldian dispositif analysis of 210 instruction documents, 55 interviews, plus participant observation) found workers paid cents-per-task with strict surveillance and whose worldviews are subordinated to requesters' — which substantiates the extraction the frame names, building on the data-colonialism thesis (Couldry & Mejias 2019), and extended by comparative political-economy work on AI annotation 'data empires' (Wu, Muldoon & Xia 2025). Honest caveat: whether 'digital self-determination' or 'Global-South sovereignty' is the right operational response (and whether it conflicts with the EU AIA's rights-based design) is a conceptual/legal question with essentially no empirical evidence base — the frame is established as a critique, thin as a tested governance prescription.
Sources: Miceli & Posada 2022, 'The Data-Production Dispositif' (Proc. ACM Hum.-Comput. Interact. 6, CSCW2, Art. 460:1-37); Couldry & Mejias 2019, 'Data Colonialism' (Television & New Media 20(4):336-349); Wu, Muldoon & Xia 2025, 'Global data empires' (Big Data & Society 12(2))
There is no rigorous impact evaluation showing that development-rights / digital-self-determination / sovereignty governance achieves its stated developmental or self-determination aims — the evidence that the frame 'works' as policy is itself missing, largely because the frame is recent, heterogeneous, and rarely instantiated in a single measurable instrument. The closest empirical literature studies one common operational proxy (data localization) and measures economic cost rather than the frame's goals: Ferracane, Kren & van der Marel's (2020) firm/industry productivity analysis finds data-policy restrictiveness associated with lower TFP in data-intensive downstream sectors, Ferracane & van der Marel's (2021) gravity analysis finds data restrictions inhibit trade in digital services, and Bauer, Lee-Makiyama, van der Marel & Verschelde's (2014) GTAP general-equilibrium estimates project GDP losses from localization across seven jurisdictions including Brazil and India. None tests whether sovereignty framing reduces extractive asymmetry or advances local AI capability — so claims on both the benefit and cost sides rest on weak or indirect evidence.
Sources: Ferracane, Kren & van der Marel 2020, 'Do data policy restrictions impact the productivity performance of firms and industries?' (Review of International Economics 28(3):676-722); Ferracane & van der Marel 2021, 'Do data policy restrictions inhibit trade in services?' (Review of World Economics 157(4):727-776); Bauer, Lee-Makiyama, van der Marel & Verschelde 2014, 'The Costs of Data Localisation: Friendly Fire on Economic Recovery' (ECIPE Occasional Paper 3/2014)