FAI AI Team
We work arms-length with policymakers in Congress and the executive branch on timely, practical AI policy issues, while also conducting original research into future-oriented topics that may arise under plausible AI trajectories that have yet to enter the mainstream. High level themes include frontier AI governance, robotics / reindustrialization, and institutional disruption.
Stream overview
Example projects complementary to existing work streams (also open to original pitches):
- Anticipating AI policy and governance implications of continual learning
- Model regulatory sandbox legislation to enable positive diffusion
- Practical mechanism design and governance frameworks for independent assurance organizations / 3rd party auditing ecosystems as imagined by bills like the Frontier AI Act
- Exploring geopolitical and supply chain implications of an industrial explosion
- AI cybersecurity preparedness; policy interventions and threat analysis
- Mitigating power concentration risks through novel corporate governance models
- Conservative / center-right AI talent development and rapid placement
Mentors
Samuel Hammond is director of Artificial Intelligence Policy and chief economist at the Foundation for American Innovation, where his research focuses on artificial intelligence and the institutional impact of emerging technologies. He previously worked as the director of social policy for the Niskanen Center, where he remains a senior fellow; as an economist for the Government of Canada specializing in regional economic development; and as a graduate research fellow for the Mercatus Center at George Mason University.
Sam received a BA in economics from Saint Mary’s University and an MA in economics from George Mason University and Carleton University.
Mentorship style
Fellows we are looking for
- Strong writing and communication ability
- Basic familiarity with core concepts in public policy and economics
Project selection
The Winter 2027 cohort offers a wide range of research streams led by experts across AI alignment, interpretability, governance, and safety. Each stream provides its own research agenda, methodology, and mentorship focus.
