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Liam Epstein

Liam Epstein

AI policy researcher focused on compute governance and transformative AI

Washington, District of Columbia, United States
cnas
Joined July 2026
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Summary

Focus on AI policy and compute governance: Epstein's recent work centers on the economics and governance of AI compute, including analysis of chip supply constraints and proposals for state investment mechanisms to shape AI trajectories. cnas+1
Interdisciplinary academic training in AI ethics and public health: He holds an MPhil in Ethics of AI, Data, and Algorithms from Cambridge and dual BS degrees from Leiden University College The Hague, giving him a cross-cutting perspective on technical, ethical, and societal aspects of AI. cnas+1
Experience across think tanks, fellowships, and government: Epstein has held roles at CNAS and IFP, participated in research fellowships (Convergence / SPAR), and interned with the U.S. Delegation to the OPCW, reflecting both policy research and practical government exposure. cnas+2
Proposes institutional tools for steering AI outcomes: Through his Convergence Analysis work, Epstein has explored concrete institutional levers—such as sovereign wealth funds and mechanisms for sharing AI rents—indicating a focus on actionable governance proposals. convergenceanalysis+1

Work

Education

Projects

Writing

American AI Companies Can't Get Enough Chips

May 1, 2026

Report analyzing constraints on AI chip production, implications for U.S. AI leadership and policy recommendations to address supply bottlenecks and strategic allocation of compute.

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Lead, Own, Share: Sovereign Wealth Funds for Transformative AI

July 1, 2025

A paper proposing sovereign wealth funds as an institutional tool for states to invest in upstream AI infrastructure, acquire strategic equity in frontier AI firms, and share AI-derived returns with citizens; evaluates ownership models, governance risks, and policy tradeoffs.

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