Literature & evidence base

Lascoumes, P. & Le Galès, P. (2007). Introduction: Understanding Public Policy through Its Instruments — From the Nature of Instruments to the Sociology of Public Policy Instrumentation. Governance 20(1): 1-21. See also Hood (1983) The Tools of Government, ch. 1-2; Salamon (2002) The Tools of Government: A Guide to the New Governance, pp. 1-47; Howlett (2011) Designing Public Policies, ch. 3-5.

✦ AIWarns "AI safety research is lagging" and present governance initiatives "lack the mechanisms and institutions to prevent misuse and recklessness", urging adaptive governance plus safety R&D.

✦ AIMaps deepfake harms across privacy, democracy, and national security and evaluates civil, criminal, and regulatory responses as fakes grow "increasingly resistant to detection".

✦ AIExperiment finds people "are more likely to feel uncertain than to be misled by deepfakes, but this resulting uncertainty, in turn, reduces trust in news on social media".

✦ AIExperiments show "audio and visual information enables more accurate discernment than text alone" — humans rely more on how something is said than on transcript content.

✦ AIArgues deepfakes pose an epistemic threat because they "reduce the amount of information that videos carry to viewers", undermining knowledge acquired from video evidence.

✦ AIEstimates "one more robot per thousand workers reduces the employment-to-population ratio by 0.2 percentage points and wages by 0.42%" — the displacement evidence policy debates cite.

✦ AIEstimates computerisation probabilities for 702 occupations, finding about 47% of total US employment "at risk" — the headline figure framing displacement and retraining policy.

✦ AIFinds around 80% of the U.S. workforce "could have at least 10% of their work tasks affected" by LLMs, which exhibit "traits of general-purpose technologies".

✦ AIProposes "model cards" — short documents accompanying trained models with benchmarked evaluation across conditions — the template transparency mandates reference.

✦ AIProposes "that every dataset be accompanied with a datasheet that documents its motivation, composition, collection process, recommended uses" for transparency and accountability.

✦ AIArgues the GDPR mandates only "meaningful, but properly limited, information" about automated decisions — a right to be informed, not a right to explanation of specific decisions.

✦ AICritiques accountability models resting on "ideals and logics of transparency", presenting ten limitations of transparency as a route to algorithmic accountability.

✦ AIArgues AI regulation "has primarily focused on conventional AI models, not LGAIMs" and should target "concrete high-risk applications, and not the pre-trained model itself".

✦ AIFinds existing GPAIS definitions "do not provide sufficient guidance" and proposes "a functional definition of the term that facilitates its governance within the EU".

✦ AIAudit of commercial classifiers showing "darker-skinned females are the most misclassified group (with error rates of up to 34.7%)" versus 0.8% for lighter-skinned males.

✦ AIComparative US/EU/UK analysis concluding "there is no standardised human rights framework and regulatory requirements that can be easily applied to FRT rollout".

✦ AIArgues the EU framework already contains norms "directly or indirectly applicable to facial recognition" in policing, and drafts a dedicated rights-protective law for its use.

✦ 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.

✦ AICritiques the EU TDM regime: "an excessively broad definition of TDM" makes data-driven AI development dependent on an exception, with narrow beneficiaries and lawful-access hurdles.

✦ AIShows foundation models "are trained on copyrighted material" and warns "fair use is not guaranteed", urging technical mitigations to keep training and deployment within fair use.

✦ AIExamines how the EU AI Act, liability regimes, GDPR, copyright and cybersecurity rules apply to generative AI, identifying gaps and proposing targeted regulatory refinements.

✦ AIAudit of 1,800+ AI training datasets finds "licence omission rates of more than 70% and error rates of more than 50%" on popular hosting sites.

✦ AIA widely used US care-management algorithm is racially biased — "at a given risk score, Black patients are considerably sicker" — because it predicts costs, not illness.

✦ AIArgues regulators of adaptive AI/ML medical software must shift from a product-centric approach to "a system view" covering human-AI interaction and organizational context.

✦ AIAudit of 130 FDA-approved medical AI devices finds evaluation gaps — mostly retrospective, scant multi-site testing — "that can mask vulnerabilities of devices when they are deployed on patients".

✦ AIMaps 222 US- and 240 EU-approved AI/ML medical devices (2015–20); of 124 approved in both regions, 80 were first approved in Europe — grounding pathway-stringency debates.

✦ AIShows a recidivism instrument satisfying predictive parity "may lead to considerable disparate impact when recidivism prevalence differs across groups".

✦ AIProves calibration and balanced error rates cannot coexist: "except in highly constrained special cases, there is no method that can satisfy these three conditions simultaneously".

✦ AIFinds COMPAS "is no more accurate or fair than predictions made by people with little or no criminal justice expertise"; a two-feature linear model matches it.

✦ AISurveys six fairness definitions: "impossible to maximize accuracy and fairness at the same time, and impossible simultaneously to satisfy all kinds of fairness".

✦ AISystematic testing showed "available detection tools are neither accurate nor reliable" and biased toward classing AI text as human-written — fragile ground for misconduct sanctions.

✦ AIFinds "GPT detectors are biased against non-native English writers", frequently misclassifying their writing as AI-generated — a fairness flaw in detector-backed integrity policies.

✦ AISurveys of 457 students and 180 staff ground an "AI Ecological Education Policy Framework" spanning pedagogical, governance and operational dimensions.

✦ AIDiagnoses a global AI governance deficit and, weighing new centralized institutions against coordinating existing ones, recommends foregrounding the OECD as the centre for AI policy expertise.

✦ AIMaps global AI governance and sets a dual agenda: "an empirical approach, aimed at mapping and explaining" it and "a normative approach, aimed at developing and applying standards".

✦ AIMaps a nascent, "polycentric and fragmented" AI governance regime in which the OECD holds "considerable epistemic authority and norm-setting power".

✦ AISurvey of algorithmic employment-assessment vendors' bias-mitigation claims, examining how "algorithmic de-biasing techniques interface with, and create challenges for, antidiscrimination law".

✦ AIField study of 391 NYC employers under LL 144: only 18 posted bias-audit reports; employer discretion over scope yields "null compliance", blunting the first AEDT bias-audit mandate.

✦ AIFrom qualitative interviews with 16 experts and practitioners, finds "LL 144 has not effectively established an auditing regime": undefined key terms, auditor data-access barriers, contested auditor roles.

✦ AISurveys EU data-protection, non-discrimination and social-acquis rules for governing "automated systems in high-risk settings such as the workplace", drawing lessons for the proposed EU AI Act.

✦ AIProposes counterfactual explanations — "the smallest change to the world that can be made to obtain a desirable outcome" — to help individuals understand, contest and alter automated decisions.

✦ AIAnalysing public submissions on Australia's AI Ethics Framework, treats contesting algorithmic decisions as "an important safeguard for individuals" and maps what contestability should require.

✦ AISynthesises contestable-AI research into a generative design framework for AI systems that are "responsive to human intervention throughout the system lifecycle".

✦ AIShows the UK National AI Strategy 'stabilises: AI as an autonomous and inevitable force', revealing how national strategies fix actors, capital flows, and power relations.

✦ AIProposes 'a concise yet nuanced concept of technology sovereignty' for innovation policy amid geopolitical competition, explicitly distinguishing it from costly 'near autarky'.

✦ AITraces how the contested concept is now understood 'more as a discursive practice in politics and policy than as a legal or organisational concept' in digital policy debates.

✦ AIFive case studies argue digital sovereignty 'affects everyone, whether digital users or not' and make 'the case for a hybrid system of control' with democratic legitimacy for the EU.

✦ AIAnalysis of GAIA-X, Bundescloud and Microsoft's EU cloud reveals 'a performative coupling of innovation and political ideas of control, territoriality and sovereignty'.

✦ 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.'

✦ 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.

✦ AITheorizes 'data colonialism' as a new extractive order that normalizes appropriating human life through 'data relations,' enabling 'the capitalization of life without limit.'

✦ 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.

✦ AIArgues the CJEU's controller-based route for applying EU law to national-security surveillance 'creates significant legal uncertainties,' proposing a data-subject-focused scope instead.

✦ AIContends 'utility and harm calculations can conceal the complex nature of contemporary digital surveillance practices,' rethinking human-rights-law tests for bulk communications surveillance.

✦ AIProposes agent identifiers, real-time monitoring and activity logs to give governance actors visibility — "where, why, how, and by whom certain AI agents are used."

✦ AIProposes "agent infrastructure": external technical systems for attributing actions "to specific agents, their users, or other actors," shaping interactions, and remediating harms.

✦ AIMaps six access levels for generative AI where "each level, from fully closed to fully open, can be viewed as an option along a gradient," grounding release-policy tradeoffs.

✦ AI"Open foundation models can benefit society by promoting competition, accelerating innovation, and distributing power," but regulation risks an uneven impact on open vs. closed models.

✦ AIOnline experiment (n=595) found 'provenance information often lowered trust and caused users to doubt deceptive media,' though it could similarly reduce trust in truthful media.

✦ AIArgues legislation should require foundation-model developers to 'demonstrate a reliable detection mechanism for the content it generates, as a condition of its public release.'

✦ AICanonical policy paper 'quantifying the approximate financial and environmental costs of training' NLP models, with 'actionable recommendations to reduce costs and improve equity.'

✦ AI'Four best practices can reduce ML training energy by up to 100x and CO2 emissions up to 1000x'; predicts training's total carbon footprint will plateau, then shrink.

✦ AIPresents 'a systematic framework for describing the effects of machine learning (ML) on GHG emissions' and suggests 'policy levers' for shaping ML's climate impacts.

✦ AIMeasures deployment energy/carbon per 1,000 inferences, finding 'multi-purpose, generative architectures are orders of magnitude more expensive than task-specific systems.'

✦ AIArgues "America's chokepoint strategy is increasingly proving to be a fallacy": Chinese chipmakers have "managed to circumvent these measures" in four ways, accelerating domestic innovation.

✦ AITraces how the AI Act's legal text shifted across versions among the terms 'AI system, general purpose AI system, foundation model, and generative AI', exposing definitional instability in the regime.

✦ AIAnalyses how the AI Act's risk-based model handles general-purpose and foundation models whose 'autonomous content generation challenges legal categories of authorship, accountability, and control'.

✦ AIExamines friction between foundation-model training and the GDPR, noting models that 'memorize and leak pieces of training data' cannot be treated as anonymous.

✦ AIAnalyses how geopolitics reshapes semiconductor global value chains and East-Asian rivalry/catch-up, the structural backdrop against which chip export controls operate.

✦ AIEmpirically estimates the economic effects of US semiconductor export controls on China, a non-Western quantitative assessment of control efficacy.

✦ AIThe 'chokepoint' and 'panopticon' theory of how states exploit central network hubs for coercion — the IR foundation for using concentrated chip supply chains as export-control leverage.

✦ AIComparative study of facial-recognition regulation for arrests across democracies finds frameworks are inconsistent and unclear, raising privacy and civil-liberties risks.

✦ AIThrough regulatory case studies, argues facial recognition in policing requires a tailored governance framework grounded in necessity and proportionality rather than ad hoc deployment.

✦ AIArgues meaningful public participation and an oversight framework should govern police adoption of FRT, presenting co-constructed policymaking as a model for addressing surveillance concerns.

✦ AIScoping review mapping the empirical evidence base on law-enforcement FRT, identifying gaps in research on real-world identification use and its governance.

✦ AIArgues states have an "international obligation...to domestically regulate" facial recognition as an unacceptable-risk AI system to protect human rights and the rule of law.

✦ AIAnalyses India's Aadhaar as a biometric mode of governance that links bodies to databases, producing new regimes of welfare inclusion and exclusion.

✦ AIAnalysing Bridges v South Wales Police, shows live AFR was ruled unlawful on Article 8 privacy, data-protection-impact-assessment, and public-sector-equality-duty grounds.

✦ AIArgues retrospective facial recognition is a step change in police surveillance whose chilling effects and weak legal basis demand an evolved human-rights framework.

✦ AIFirst RCT field trials of predictive policing report algorithmic hotspot predictions led to crime reductions versus analyst-designated patrols.

✦ AISystematic review of 161 articles finds claimed effectiveness underpins legitimacy of predictive policing in the UK and US while algorithmic bias and data-concentration concerns persist.

✦ AISynthesises a decade of AI-in-criminal-justice research, flagging "algorithmic bias, opacity, and due process" and recommending safeguards for equity and accountability.

✦ AIProves mathematically that learning from discovered-crime data sends police repeatedly to the same neighbourhoods "regardless of the true crime rate," and shows how to correct it.

✦ AIArgues data-driven predictive policing can produce disparate racial impacts even when well-intentioned, and proposes algorithmic impact statements as a legal remedy.

✦ AIUK case study maps algorithmic tools used across the criminal-justice system and finds fragmented governance and weak transparency over their deployment.

✦ AIEmpirical study of Kentucky's mandatory pretrial risk assessment finds an initial small detention drop that dissipated as judges reverted, with limited net change and modest disparity effects.

✦ AIFinds freedom-of-information regimes "generally only grant access to existing documents" and that with "no mature standard for documenting AI models," public-sector AI transparency is limited.

✦ AIProposes that GDPR algorithmic impact assessments be combined with individual rights to produce layered, system-and-individual explanations of automated decisions.

✦ AIArgues algorithmic impact assessments depend on how "impacts" are co-constructed, and that AIA regimes must define who measures impacts and to whom accountability is owed.

✦ AICritiques Amsterdam/Helsinki AI registers as risking "ethics theater" by decontextualising and depoliticising algorithmic systems used in the digital welfare state.

✦ AIExamines the tension between AI Act disclosure duties and trade-secret protection, identifying which technical details lack trade-secret eligibility to enable transparency.

✦ AISynthesises interdisciplinary evidence to argue that legally mandated human oversight of AI is often ineffective ('rubber-stamp') unless effectiveness conditions are explicitly designed for.

✦ AIAnalyses how AI-audit mandates create a new political economy of auditing, warning that audit markets can entrench rather than constrain power without underlying governance.

✦ AIArgues the UK Online Safety Act 2023 inadequately addresses non-consensual intimate deepfakes as image-based sexual abuse, leaving enforcement and takedown gaps.

✦ AIThematic analysis of 319 state deepfake bills (2019-2024) finds a fragmented patchwork concentrated on political and sexually-explicit content.

✦ AIArgues deepfake threat to recordings is overstated once social norms are recognised and that policy has been overly focused on technological interventions.

✦ AIArgues detector-based solutions depend on scarce institutional trust and risk undermining epistemic autonomy, so purely technological fixes for deepfakes are dim.

✦ AIFive survey experiments (>15,000 US adults) show false 'it's a deepfake/fake news' claims can help politicians retain support, evidencing the liar's dividend.

✦ AIArgues fragmented US tort doctrines (defamation, publicity, IIED) are ill-suited to deepfake harms and draws remedial lessons from Chinese and Singaporean law.

✦ AICritiques the EU AI Act's placement of deepfakes in the 'limited risk' tier, leaving transparency obligations as the only direct safeguard without bans or victim remedies.

✦ AIWarns a narrow reading of 'existing' in the AI Act's deepfake definition could exclude synthetic media from transparency duties, urging a teleological interpretation.

✦ AIArgues US, EU and Chinese regimes fail to assign audio-deepfake liability to 'landlords of creativity' (foundation-model providers) and proposes holding them accountable.

✦ AISurvey of >16,000 respondents across 10 countries finds NSII victimization/perpetration persists even where specific laws exist, suggesting current laws under-deter.

✦ AISystematizes watermarking for AI content, formalizing robustness/security goals and limits that directly ground regulatory provenance and labeling mandates.

✦ AIEmpirical audit finds only 38% of AI image generators implement adequate watermarking and 18% deepfake labelling, exposing a compliance gap under EU AI Act Article 50.

✦ AIAnalyses China's 2022 deep-synthesis and 2023 generative-AI rules, including mandatory labelling/watermarking of synthetic content as a provenance-governance model.

✦ AIQualitative analysis of public commentary on Sora finds blurred real/fake boundaries drive demand for law-enforced AI-content labelling and provenance.

✦ AIRecasts GDPR Art. 22's right to contest as the core due-process remedy and maps administrative, procedural and technical transparency mechanisms to implement it.

✦ AIArgues administrative-law principles (reasons, review, contestation) should structure remedies and procedural fairness for public-sector automated decisions.

✦ AIUser study (N=267) finds contestability (appeal processes) drives procedural-fairness perceptions while human oversight alone shows no significant effect.

✦ AIField study shows marginalized public-service users need intermediaries and informal channels for contestation, challenging individualistic right-to-contest designs.

✦ AISpeculative design of a contestable public-AI system specifies concrete redress affordances: explanations, appeal channels, an adversarial arena and a duty to respond.

✦ AIEmpirically elicits what decision subjects need for contestation to be 'meaningful', informing the design of effective remedies and appeal mechanisms for ADM.

✦ AITask-based framework: automation's displacement effect shifts the task content of production against labor and can reduce labor demand even as it raises productivity, counterbalanced only by new-task reinstatement.

✦ AIEstimates 50–70% of changes in the U.S. wage structure over four decades are accounted for by relative wage declines of worker groups specialized in routine tasks in rapidly-automating industries.

✦ AIArgues commentators overstate machine substitution and ignore complementarities: automation substitutes for some tasks but raises demand for the labor that complements it, explaining persistent employment.

✦ AITask-based model estimates AI raises TFP only ~0.66% over ten years and warns benefits may not be broadly shared, tempering claims of large near-term macroeconomic and labor effects.

✦ AIStaggered rollout of a GPT-based assistant to 5,172 support agents raised issues-resolved-per-hour 14% on average and 34% for novices, compressing the skill gap rather than displacing high-skill workers.

✦ AIProposes 'privacy due diligence' as a human-rights-based regulatory approach to algorithmic management and worker monitoring, arguing data-protection law alone inadequately constrains employer surveillance.

✦ AIIdentifies regulatory gaps from algorithmic management (privacy harms, information asymmetries, loss of human agency) and sets out a concrete policy blueprint to address them.

✦ AIEvaluates UK equality and data-protection law against algorithmic hiring tools and proposes a 'transparent recruitment scheme' incentivizing publication of equality metrics from data-protection impact assessments.

✦ AIArgues existing European equality law is 'remarkably robust' against algorithmic management discrimination but that opacity and enforcement gaps blunt its effect, mapping where reform is needed.

✦ AIArgues collective bargaining and worker co-determination, not just individual data rights, are essential governance tools for regulating AI-driven algorithmic management at work.

✦ AIAnalyzes the 2024 EU Platform Work Directive through Fairwork evidence, assessing its employment-status and algorithmic-management provisions and charting a path toward a proposed ILO platform-work Convention.

✦ AIEmpirical socio-legal study of employer AI hiring systems showing how design and deployment choices generate discrimination that current anti-discrimination law struggles to reach.

✦ AIDemonstrates empirically that authentic assessment alone does not safeguard academic integrity against generative AI, implying institutions need policy-level redesign rather than reliance on assessment format.

✦ AISurvey at a diverse U.S. public research university finds ChatGPT adoption and instructor support vary by student demographics and field, raising educational-equity concerns for AI-in-education policy.

✦ AIReviews 32 empirical studies and concludes assessment should be transformed to cultivate self-regulated, responsible learning and integrity rather than relying on AI-text detection alone.

✦ AISystematic review (29 studies) builds an AI-literacy competency framework varying by learner group, offering a reference for designing AI curricula and education-policy learning pathways.

✦ AIEuropean Network for Academic Integrity policy recommendations: institutions should set transparent rules on permitted AI use, require disclosure, and not penalize tools for tasks they were authorized for.

✦ AISurvey informing the University of Liverpool integrity code finds 54.1% support tools like Grammarly but 70.4% oppose using ChatGPT to write whole essays, guiding nuanced AI-use policy.

✦ AIArgues medical LLMs are likely device-like clinical decision support and that 'the urgent need to enforce existing regulations' is the key safeguard against unsafe deployment.

✦ AIFinds general-purpose LLMs 'readily produced device-like decision support across a range of scenarios,' implying they should fall under medical-device regulation if clinically deployed.

✦ AIContends external validation 'does not guarantee generalizability' and proposes recurring local validation as the safer regulatory paradigm for clinical AI.

✦ AIAnalyzes the SaMD prespecification and algorithm change protocol mechanism (FDA predetermined change control) for governing continuously-learning medical-device algorithms.

✦ AIProposes a post-market governance framework for AI/ML medical devices addressing performance drift and ongoing monitoring beyond initial approval.

✦ AICalls for a new regulatory category/oversight for medical LLMs, warning existing device frameworks were not designed for general-purpose generative models.

✦ AISets out the WHO/ITU Global Initiative on AI for Health's strategic priorities to harmonize international regulatory and governance standards for health AI.

✦ AIDocuments that most FDA AI/ML devices clear via the 510(k) pathway with limited clinical validation and poor transparency, exposing regulatory evidence gaps.

✦ AIArgues 'governments should evaluate advanced [biological] models and if needed impose safety measures' to mitigate AI-enabled biosecurity catastrophic risk.

✦ AIReviews biosecurity and dual-use risks at the AI-synthetic-biology interface and maps governance pathways for emerging catastrophic threats.

✦ AIDistinguishes 'decisive' (sudden takeover) from 'accumulative' AI existential risk, arguing governance must address gradual societal erosion as well as abrupt scenarios.

✦ AIArgues international law imposes a precautionary-principle obligation on states to regulate AI to mitigate the threat of human extinction.

✦ AIAnalyzes how AI-driven detection/concealment in nuclear arsenals reshapes strategic stability and proliferation risk, with governance implications.

✦ AIProvides a 440-task benchmark across 11 harm categories measuring whether LLM agents resist or comply with harmful multi-step tool-use tasks, grounding safety-evaluation regimes for agents.

✦ AIExamines whether Article-14 human oversight of high-risk/autonomous AI can actually deliver fairness, probing the limits of human-in-the-loop as a governance mechanism.

✦ AIArgues LLM training on scraped web data should be assessed under Art. 9 GDPR (sensitive data), and that consent and the 'manifestly made public' route leave only a 'limited amount of personal data' lawfully usable.

✦ AIContends the UK opt-in/opt-out framing is a 'missed opportunity'; a broadened research exception plus market-entry transparency and creator remuneration would better serve both innovation and rightsholders.

✦ AIArgues Art. 3 CDSM Directive's scientific-research TDM exception 'does not grant rightsholders any control' and can be a 'safe harbor' for training openly released foundation models without licensing data.

✦ AIComparatively maps US (industry-oriented fair use), EU (rights-oriented TDM opt-out) and a proposed UN fair-remuneration approach to copyright at the generative-AI training stage.

✦ AIRejects blanket lawful/unlawful verdicts on AI training, proposing 'an analytical framework for making that assessment in particular cases' for where owners' rights end and use freedoms begin.

✦ AIExamines post-LAION practical obstacles to the EU TDM opt-out (robots.txt, machine-readability, memorisation): 'While the TDM exceptions may seem workable in theory, implementing them in practice presents a variety of practical…

✦ AIProposes 'structured access' (controlled, arm's-length cloud interactions) as a middle path between open release and full closure, restricting dangerous capabilities while preserving beneficial use and scrutiny.

✦ AIA 14-dimension survey of 45+ systems finds many self-described 'open source' models are 'open weight at best' and providers seek to 'evade scientific, legal and regulatory scrutiny' under the EU AI Act's open-source exemption.

✦ AIProposes a UN-backed International Artificial Intelligence Agency modelled on the IAEA, arguing 'only an IAIA can legitimately oversee a global AI governance framework involving all major powers.'

✦ AIReproduces and annotates the first legally binding international AI treaty, grounding cross-border AI governance in legality, proportionality, transparency, accountability and non-discrimination across the AI lifecycle.

✦ AIArgues states increasingly assert 'strategic digital sovereignty...through selective alliances with firms and other governments,' fragmenting global AI infrastructure into techno-blocs rather than multilateral order.

✦ AIQualitative content analysis of ~12 national AI strategies (2017-2019) shows governments deploy 'sovereigntist AI projects' that reconfigure public-private ordering via hybrid governance and marketization.

✦ AIComparing China, US, France and Germany strategies, the authors show national AI policy documents 'talk AI into being' through competing sovereignty/leadership imaginaries that perform political reality.

✦ AINational AI strategies mobilize democratic, sociotechnical and data imaginaries that frame sovereign AI capacity as a means for democracies to overcome governance challenges.

✦ AIUS and Chinese drives for sovereign AI/cloud dominance depend on reorganizing land, energy and regulatory systems to sustain large-scale national computing power.

✦ AIInterrogates the EU 'AI sovereignty' agenda, showing the goal is under-specified and risks serving incumbent industrial interests rather than European publics.

✦ AIArgues the EU's pursuit of AI-based digital sovereignty in security is a 'false promise' given dependence on non-EU compute, data and chip supply chains.

✦ AICase study of Gaia-X finds no singular EU meaning of digital sovereignty but six competing conceptions across security, economy and rights domains.

✦ AIShows Gaia-X paradoxically incorporates dominant US cloud providers, undermining the very European digital sovereignty it was meant to advance.

✦ AISystematic review of 341 publications maps how data, digital and cyber sovereignty are conceptualized and the control challenges they pose across stakeholders.

✦ AICritically traces digital sovereignty's origins and uses, arguing the frame masks contested objectives and should be 'unthought' to clarify governance practice.

✦ AIArgues technological sovereignty rhetoric drives a 'geo-dirigiste' turn in EU industrial policy (e.g. semiconductors) blending security and competitiveness logics.

✦ AITheorizes AI through Quijano's 'colonial matrix of power', showing global production imbalances extract value from majority-world labor for Northern firms.

✦ AIComparative analysis finds China, India and South Africa pursue divergent state digital-sovereignty models shaped by distinct development trajectories and rights regimes.

✦ AIProposes five design principles for African-centred AI data governance, warning that reliance on non-African frameworks undermines local and regional inclusivity.

✦ AIMaps the political drivers and trends of emerging African national AI policies, situating sovereignty and development framings against external dependency.

✦ AIOffers a framework to evaluate global AI governance initiatives, recommending capacity-building so Global South states can meaningfully participate in standard-setting.

✦ AISurveys Latin American critical data studies, advancing concepts of statistical, epistemic and national sovereignty as decolonial framings for AI/data governance.

✦ AICompares AI policy 'design spaces' across Latin American states, showing how development and capacity constraints shape divergent governance choices.

✦ AIArgues Western tech monopolies practice 'algorithmic colonialism' in Africa, with profit-driven AI solutions reproducing colonial power asymmetries.

✦ AIEmpirically shows LLMs encode their creators' ideologies, supporting policy incentives for home-grown models reflecting local cultural views, especially in low-resource-language regions.

✦ 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.

✦ AIAnalyses how the CJEU in Privacy International and La Quadrature du Net subjected member-state national-security surveillance to EU law, turning the national-security boundary into a contested struggle over competence.

✦ AICase note on the ECtHR Grand Chamber's first post-Snowden bulk-interception ruling, holding bulk surveillance not per se disproportionate but requiring end-to-end independent oversight safeguards.

✦ AIArgues data-retention mandates justified by national security amount to mass surveillance and proposes an evaluative framework because such 'highly intrusive proposals' lack an agreed basis for assessment.

✦ AITraces how the AI Act's law-enforcement and national-security exceptions widened during negotiations, producing 'double standards for fundamental rights protection' and gaps in the regulatory framework.

✦ AIIdentifies how the AI Act's military, defence and national-security exclusions leave biometric and satellite-imaging surveillance under-regulated, arguing for a global standard to close these gaps.

✦ AIExamines how predictive-policing and predictive-justice systems interact with data-protection law and the AI Act's law-enforcement provisions, exposing accountability and oversight shortfalls.

✦ AIArgues the AI Act's Article 5 surveillance prohibitions are undercut by broad law-enforcement and security exceptions, so 'enforcement of fundamental rights and data protection law' must do the heavy lifting against mass survei…

✦ AICanonical estimate projecting AI servers could consume 85-134 TWh/year by 2027 (comparable to a small country), framing disclosure of AI electricity use as a policy problem.

✦ AIEstimates training GPT-3 in US data centres can evaporate ~5.4 million litres of water and projects 4.2-6.6 billion m3 of AI water withdrawal by 2027, arguing water use needs reporting and scheduling.

✦ AIProvides a standardized, reproducible methodological framework (and calculator) to estimate the carbon footprint of any computational task from runtime, hardware and grid location.

✦ AILife-cycle estimate finding BLOOM's training emitted ~24.7 tCO2e from dynamic power but ~50.5 tCO2e once manufacturing and idle/operational consumption are counted, motivating full-lifecycle reporting.

✦ AICoins 'Green AI', arguing compute/energy efficiency should be reported as a first-class evaluation metric alongside accuracy to curb the rising environmental cost of deep learning.

✦ AISurveys evidence that ML's carbon cost is under-measured and calls for tools to quantify training footprints and a shift to sustainable AI infrastructure as a governance priority.

✦ AIAnalyses the legal levers (AI Act energy-reporting duties, Energy Efficiency Directive data-centre KPIs, sustainability reporting) for governing AI's climate footprint and their disclosure gaps.

✦ AIShows embodied (manufacturing) carbon can rival operational emissions for computing systems, grounding the case that AI footprint accounting and rules must include hardware lifecycle, not just training energy.

✦ 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.

✦ AIA 60-reference review weighing AI innovation and economic competitiveness against ethical safeguards.

✦ AIFrames national AI strategies on a development/control/promotion axis, the lens for a promotion-and-leadership national AI posture.

✦ AIPRISMA systematic review (553 of 22,711 screened studies) of responsible-AI principles and practice, including transparency and accountability.

✦ AICross-jurisdiction legal evaluation of pretrial algorithmic risk-assessment tools and their contested fairness and accuracy.

Mitchell et al. (2019), 'Model Cards for Model Reporting,' FAccT '19

Hubinger, E., et al. (2019), 'Risks from Learned Optimization in Advanced Machine Learning Systems.'

✦ AIArgues labour law must protect worker dignity under algorithmic management, urging a "human-in-command approach" with social partners governing automation.

✦ AIUsing the 2007 US 'China Rule', finds sanctioned Chinese firms raised R&D by ~49% and patenting by ~41% — evidence export controls can accelerate the target's indigenous innovation.

✦ AIUS National Academies' AI consensus-study hub.

✦ AICommentary on how anthropomorphic AI language obscures accountability.

Analyzes the Oct 2022 controls as "weaponizing its dominant chokepoint positions in the global semiconductor value chain" to block China's access to AI chips, design software, and equipment.

✦ AIAda Lovelace Institute policy briefing.

✦ AIRecommends stronger platform data-access rules so independent researchers can study automated systems in the public interest.

✦ AIUS voluntary AI risk-management framework (Govern/Map/Measure/Manage).

✦ AIInternational committee developing AI standards.

✦ AIOECD tracker of real-world AI incidents and hazards.

✦ AIEU agency report whose predictive-policing feedback-loop simulation shows biased crime data amplifying over-policing of minorities.

✦ AIFlagship inclusive-AI-for-development report: 118 mostly-Global-South countries absent from AI governance; infrastructure, data and skills divides.