Research / Sources
Legal research on AI governance. law-ai.org
An interview with LawAI's Christoph Winter on the EU AI Act and the General-Purpose AI Code of Practice, covering how frontier model providers comply and what it means for providers outside the EU.
Argues that the US should use the threat of throttling AI chip or development trade to secure a mutual US-China deal to pace frontier AI development, citing recent agent containment incidents.
Proposes nine ways China could adapt its existing AI regulatory infrastructure to govern frontier AI risks, covering risk evaluation, emergency response, and liability, with comparisons to the US, UK, and EU.
Analyses Germany's decision to establish a national AI Safety and Security Institute to build government capacity for evaluating frontier AI capabilities and risks, and its place in the international network.
A policy commentary arguing that U.S. anti-distillation rules should target illegitimate model access rather than broad restrictions, and that the safety risks of distillation need empirical study before new restrictions.
Argues the US-China 'AI race' framing is misguided and that deregulatory moves, like rescinding frontier safety reporting requirements, weaken safety without real strategic benefit.
Legal analysis of obstacles to implementing the December 2025 US executive order aimed at preempting state AI laws, covering litigation, funding restrictions, reporting standards and FTC Act preemption.
Proposes treaty-following AI agents that are technically built to comply with international agreements on advanced AI, arguing this can serve as a commitment and cooperation mechanism for managing AI risks.
A book on designing global AI governance institutions and regimes, addressing how to regulate advanced AI and keep governance effective as AI disrupts international law and politics.
Argues that the U.S. and China should jointly back a single leading AI lab instead of racing, to avoid arms-race conflict and pursue transformative AI cooperatively.
Commentary arguing that AGI could undermine nuclear deterrence between superpowers, creating grave international security risks regardless of who wins the AGI race.
Argues that the U.S. should pursue international cooperation with China rather than an AI race after DeepSeek's r1 release, using game-theoretic reasoning about racing dynamics and proposing joint development and mutual transparency.
Argues that highly capable AI could cause catastrophic harms in Global South countries through weak institutions and other vulnerabilities, and that stakeholders must act now to influence its development.
Proposes a framework for deciding which AI governance issues should be internationalised, finding strongest benefits for compute oversight, model evaluations, incident monitoring and risk management protocols.
Argues that the Global AI Majority is largely excluded from AI development and governance, and proposes interest alignment, participatory architecture and safety assurance to address dual-use and frontier-state restrictions.
Examines whether an international framework convention on AI, with later protocols, could address global AI governance gaps better than piecemeal treaties, and argues for a hybrid design.
Proposes a two-track international framework for scientific assessment of AI risks: a UN-led process on broad AI issues and an independent annual report on advanced AI risks.
Proposes a U.S.-led international framework, 'Chips for Peace', that pairs AI safety regulation, benefit-sharing and nonproliferation commitments, modelled on the Atoms for Peace approach to nuclear technology.
Examines where binding international law could control advanced AI, covering controls on risky end uses, on AI development, and on compute inputs, and the structural obstacles to hard governance.
Argues that AI compute is an effective point for governing AI development and deployment, surveys current compute-based policies, and assesses their readiness for safety and misuse prevention.
A literature review and taxonomy of advanced AI governance research, covering technical parameters, threat models, actors, levers of governance, and pathways to influence.
A literature review of seven proposed institutional models for international AI governance, including emergency response and enforcement of restrictions, with directions for further research.
Proposes an International AI Organization that certifies state jurisdictions for compliance with international AI oversight standards, enforced through import and export controls on AI supply chains to mitigate advanced AI risks.