Policy and Governance
The Policy and Governance Track supports research on how advanced AI is governed and how it should be governed. As AI capabilities accelerate, many of the hardest problems are no longer purely technical. They involve international coordination, policymaking amid uncertainty, state capacity, regulatory design, and translating safety goals into real-world policies and institutions. Decisions made in the next 6–12 months will shape what labs build, what governments require, and what oversight looks like for years to come.
- Stage 1: Complete the general application, including 1-2 writing samples
- Stage 2: Stream selection questions alongside possibly reference requests
- Stage 3: Interviews and work-tests
The track covers a wide range of research areas. Some streams within this track focus on concrete governance mechanisms, including evaluations, standards, safeguards, monitoring systems, and enforcement structures, while others focus on conducting policy and institutional analysis, such as comparative reviews of governance regimes, regulatory frameworks, and international coordination challenges. A separate set of streams engage with broader questions, like how advanced AI may reshape global power dynamics or how governance approaches could meaningfully reduce catastrophic risk.
We are looking for fellows who can reason and write clearly about these topics. Strong candidates in past cohorts have had backgrounds in policy, economics, law, political science, public administration, security studies, philosophy, computer science, forecasting, sociology, history, journalism, and science and technology studies.
Fellows are matched to mentors based on fit, and projects are scoped to produce concrete artifacts (e.g., policy memos, regulatory comments, technical specifications, comparative analyses, and peer-reviewed research) by the end of the program. Target audiences for the work produced in this track span AISI staff, lab governance teams, regulators, standards bodies, and the broader research and policy communities shaping frontier AI governance.
We work to advance technically grounded international coordination to reduce catastrophic risks from frontier AI, with a particular focus on China and US. We translate technical AI safety and governance tools into practical proposals for coordination.
This stream will focus on technical AI governance research -- hence the name TAIGR. We will follow an academic collaboration model and produce open research on applied AI safeguards, incidents, laws, and other impactful topics in AI governance.