Harvard University

Harvard Kennedy School - AI Governance and Policy

United States · MPP/PhD/Executive

Harvard Kennedy School is a global leader in AI governance and policy research, integrating perspectives from public policy, technology assessment, and international relations to study AI regulatory frameworks, international AI governance, and policy safeguards for AI alignment. The school has trained a large number of policymakers and researchers in the field of AI governance.

学术历史

Harvard Kennedy School was established in 1936 (as the successor to the Graduate School of Public Administration) and is one of the world's most influential public policy schools. AI governance research has a long history at the Kennedy School: the Belfer Center for Science and International Affairs has addressed the intersection of AI safety and national security since the 2010s, and its Technology and Public Policy project covers AI regulation. The Kennedy School collaborates with the Berkman Klein Center to offer interdisciplinary AI governance courses. Researchers such as Mathew Mathews participate in academic advisory work for U.S. AI policy development. The school regularly hosts AI governance policy workshops and executive education programs.

当前状态

Harvard Kennedy School currently operates AI governance-related projects: the Belfer Center's AI Safety and National Security Initiative, Tech Policy Lab, and research on AI and international governance. The school offers AI governance and policy courses (IGA series) and runs Executive Education programs training AI policymakers. The school maintains close collaborations with federal agencies including the White House Office of Science and Technology Policy and NIST. It regularly publishes AI governance policy reports and recommendations.

实验室 / 研究中心

关键人物

标志性成果

• Cross-disciplinary research framework for AI safety and national security: situating AI alignment within the context of international security and strategic stability
• Sheila Jasanoff's Science and Technology Studies (STS) methodology: providing institutional analysis tools for AI governance
• AI policymaker training: cultivating global AI governance talent through Executive Education programs
• Academic advisory participation in U.S. AI policy development: providing research support for policies such as the NIST AI Risk Management Framework

学术资源

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