Kevin T. Frazier is a legal scholar focused on AI policy, innovation policy, and regulatory design, and an editor at Lawfare who writes frequently on AI executive-branch policy. He is the AI Innovation and Law Fellow at the University of Texas School of Law, where he leads the school's AI Innovation and Law Program (Source: https://law.utexas.edu/faculty/kevin-frazier/).
Background
Frazier previously served as Assistant Professor at St. Thomas University College of Law and as the Crump Family Endowed Visiting Professor at the University of Texas at Austin School of Law. His Lawfare work has provided long-running coverage of AI executive-branch policy and frontier-AI governance.
Frazier graduated summa cum laude from the Robert D. Clark Honors College at the University of Oregon, earned his J.D. with Order of the Coif recognition at the UC Berkeley School of Law, and completed a Master of Public Administration at the Harvard Kennedy School (Source: https://law.utexas.edu/faculty/kevin-frazier/). Following a clerkship with Chief Justice Mike McGrath of the Montana Supreme Court, he taught constitutional law, administrative law, and civil procedure at St. Thomas University College of Law and conducted research with the Institute for Law and AI (Source: https://law.utexas.edu/faculty/kevin-frazier/). Before his graduate education he worked for Oregon Governor Kate Brown, lobbied the Oregon State Legislature for a nonprofit, and held roles at Google, Verily, and Cloudflare (Source: https://www.thefai.org/profile/kevin-frazier).
Roles
Frazier is the inaugural AI Innovation and Law Fellow at the University of Texas School of Law and leads its AI Innovation and Law Program, which includes teaching AI courses, connecting students with Austin's startup community, and representing the school at AI events; he has taught "The Law of Artificial Intelligence" and "AI Innovation, Law, and Policy" (Source: https://law.utexas.edu/faculty/kevin-frazier/). He is described as a Senior Editor at Lawfare and as Director of the AI Innovation and Law Program in Lawfare's own materials (Source: https://www.lawfaremedia.org/article/lawfare-presents--scaling-laws). He co-hosts the Scaling Laws podcast on AI policy (Source: https://law.utexas.edu/faculty/kevin-frazier/). The existing page records his role as a Contributing Editor at Lawfare; he has co-authored multiple Lawfare AI policy pieces with Alan Z. Rozenshtein.
Scholarship and writing
Frazier's research focuses on artificial intelligence, innovation policy, and regulatory design, including how to design regulatory ecosystems that accelerate AI adoption and diffusion (Source: https://law.utexas.edu/faculty/kevin-frazier/). He has published in law journals including the Tennessee Law Review, the Rutgers Law Review, the Chapman Law Review, and the Fordham Intellectual Property, Media & Entertainment Law Journal, and has written essays on AI policy for Lawfare, Reason, AI Frontiers, the MIT Technology Review, and the Dispatch (Source: https://www.thefai.org/profile/kevin-frazier).
Frazier has testified before Congress on AI and technology policy. He appeared before the House Judiciary Subcommittee on Courts, Intellectual Property, Artificial Intelligence, and the Internet on September 18, 2025 in a hearing titled "AI at a Crossroads: A Nationwide Strategy or Californication?", and before the House Committee on Education and the Workforce on January 14, 2026 in a hearing titled "Building an AI-Ready America" (Source: https://law.utexas.edu/faculty/kevin-frazier/). He also testified before House subcommittees on November 20, 2025 regarding foreign-adversary threats to subsea cable infrastructure (Source: https://law.utexas.edu/faculty/kevin-frazier/).
Positions and statements
With Alan Z. Rozenshtein, Frazier co-authored Dominating AI Requires Understanding AI (Lawfare, May 12 2026) (Dominating AI Requires Understanding AI (Frazier + Rozenshtein, Lawfare, May 12 2026); see Dominance by Understanding (Frazier-Rozenshtein policy frame)). The essay names a "dominance by understanding" policy frame, presented as a third-pole alternative to "doomer" predeployment-testing mandates and "accelerationist" minimal-intervention dominance. His writing engages with Responsible Scaling Policy (RSP), AI Pre-Release Vetting, Defense Production Act (DPA), and CREATE AI Act (Young).
Frazier's stated research interest is in regulatory approaches that he argues should accelerate AI adoption and diffusion rather than constrain it (Source: https://law.utexas.edu/faculty/kevin-frazier/). He has participated in Federalist Society events on AI and national security, including a panel at the 2025 AI and National Security Symposium and a session on the federal AI Action Plan (Source: https://fedsoc.org/bio/kevin-frazier).
Relationships
- affiliated-with: Lawfare (Contributing Editor; described as Senior Editor in Lawfare materials)
- co-author-with: Alan Z. Rozenshtein (multiple Lawfare AI policy pieces)
- author-of: Dominating AI Requires Understanding AI (Frazier + Rozenshtein, Lawfare, May 12 2026)
- supports: Dominance by Understanding (Frazier-Rozenshtein policy frame)
- engages-with: Responsible Scaling Policy (RSP), AI Pre-Release Vetting, Defense Production Act (DPA), CREATE AI Act (Young)
Sources
- Dominating AI Requires Understanding AI (Frazier + Rozenshtein, Lawfare, May 12 2026)
- University of Texas School of Law faculty profile: https://law.utexas.edu/faculty/kevin-frazier/
- Foundation for American Innovation profile: https://www.thefai.org/profile/kevin-frazier
- Lawfare, "Lawfare Presents: Scaling Laws": https://www.lawfaremedia.org/article/lawfare-presents--scaling-laws
- Federalist Society contributor bio: https://fedsoc.org/bio/kevin-frazier