Tal Feldman writes about AI and national security. His work has appeared in the New York Times, Foreign Affairs, the Washington Post, Foreign Policy, MIT Technology Review, Lawfare and Science.

Before law school he built AI systems for the government. He led an 18-person AI engineering team at the State Department and also worked at the Federal Reserve Board and the Department of Defense. He was a Schwarzman Scholar at Tsinghua University and is a Truman Scholar and a Paul & Daisy Soros Fellow. He is a J.D. candidate at Yale Law School and an editor of the Yale Law Journal.

Ibrahim Dagher writes about how machine learning works and what that means for AI policy. His writing has appeared in the Wall Street Journal, the Washington Post, Lawfare and Just Security.

His background is in formal methods and philosophy. He has published in Synthese, Philosophia and other philosophy journals. The Yale Law School faculty awarded him the Cohen Prize for legal philosophy. He was most recently a summer fellow at the Foundation for American Innovation and the Institute for Law & AI. He is pursuing a J.D. and a Ph.D. in philosophy at Yale, where he is a Paul & Daisy Soros Fellow.

Kevin Xiao works on structural constitutional law, administrative law and the separation of powers. His writing on AI governance and cybersecurity has appeared in the Wall Street Journal and Just Security.

He was president of the William F. Buckley, Jr. Program at Yale and worked on data privacy at the Federal Election Commission. He earned his B.A. and M.A. in political science at Yale and is a J.D. candidate at Yale Law School.