Frontier AI Governance Course
BlueDot Impact
The only structured, free, current syllabus focused specifically on how policy for frontier models is made. Cohort-based course of about 40 hours covering frontier AI evidence, the institutions and power dynamics shaping AI governance, competing regulatory strategies, and debates such as open-weight models. Units combine curated readings with facilitated discussion led by practitioners.
More resources on AI Policy & Regulation
Scaling Laws
Weekly interview and rapid-response podcast on AI law and policy, covering federal preemption of state AI laws, frontier model regulation, AI assurance and liability. Hosted by law professor Alan Rozenshtein and Kevin Frazier with policymakers, researchers and lab staff.
U.S. Tort Liability for Large-Scale Artificial Intelligence Damages: A Primer for Developers and Policymakers
Explains how existing U.S. tort law, including negligence and products liability, would apply to AI developers whose models cause or are misused to cause large-scale harm, and how safety practices and legislation could change developers' liability exposure. Written for non-lawyers: this is the clearest rigorous free primer aimed at policy audiences rather than litigators.
Copyright and Artificial Intelligence, Part 3: Generative AI Training
Report from the U.S. Copyright Office analyzing whether training generative AI models on copyrighted works infringes, how the four fair-use factors apply to training and outputs, and policy options including voluntary and collective licensing. Draws on over 10,000 public comments. Learners should note it was released amid the dismissal of the Register of Copyrights and that 2025 district court rulings (Bartz v. Anthropic, Kadrey v. Meta) reached partly different conclusions.
Computing Power and the Governance of Artificial Intelligence
Argues that AI compute is detectable, excludable, quantifiable and produced by a concentrated supply chain, making it a practical lever for governance. Analyzes export controls, compute thresholds, reporting and allocation mechanisms, and the risks and limits of compute-based policy. The concepts (FLOP thresholds, chip export controls, know-your-customer for cloud) underpin the EU AI Act GPAI systemic-risk threshold and US export control policy.
China's AI Policy at the Crossroads: Balancing Development and Control in the DeepSeek Era
The most current rigorous, free treatment that covers both China's regulatory instruments and the policy process behind them. Traces Chinese AI policy through four eras up to 2025, covering the CAC algorithm registry, generative AI measures, 2025 labeling rules for synthetic content, bureaucratic rivalry between regulators, and the AI+ industrial initiative. Explains how Chinese AI rules are drafted and revised.
Digital Empires: The Global Battle to Regulate Technology
Comparative study of the American market-driven, Chinese state-driven and European rights-driven models of technology regulation, and how they collide internationally across antitrust, data privacy, content moderation and artificial intelligence. Supplies the framework for comparing US, Chinese and EU AI policy.