Cybersecurity & Tech

Lawfare Daily: Why AI Won't Revolutionize Law (At Least Not Yet), with Arvind Narayanan and Justin Curl

Alan Z. Rozenshtein, Justin Curl, Arvind Narayanan, Jen Patja
Thursday, February 12, 2026, 7:00 AM
What are the bottlenecks preventing AI from reducing legal costs?

Alan Rozenshtein, research director at Lawfare, speaks with Justin Curl, a third-year J.D. candidate at Harvard Law School, and Arvind Narayanan, professor of computer science at Princeton University and director of the Center for Information Technology Policy, about their new Lawfare research report, “AI Won't Automatically Make Legal Services Cheaper,” co-authored with Princeton Ph.D. candidate Sayash Kapoor.

The report argues that despite AI's impressive capabilities, structural features of the legal profession will prevent the technology from delivering dramatic cost savings anytime soon. The conversation covered the "AI as normal technology" framework and why technological diffusion takes longer than capability gains suggest; why legal services are expensive due to their nature as credence goods, adversarial dynamics, and professional regulations; three bottlenecks preventing AI from reducing legal costs, including unauthorized practice of law rules, arms-race dynamics in litigation, and the need for human oversight; proposed reforms such as regulatory sandboxes and regulatory markets; and the normative case for keeping human decision-makers in the judicial system.

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Alan Z. Rozenshtein is an Associate Professor of Law at the University of Minnesota Law School, Research Director and Senior Editor at Lawfare, a Nonresident Senior Fellow at the Brookings Institution, and a Term Member of the Council on Foreign Relations. Previously, he served as an Attorney Advisor with the Office of Law and Policy in the National Security Division of the U.S. Department of Justice and a Special Assistant United States Attorney in the U.S. Attorney's Office for the District of Maryland. He also speaks and consults on technology policy matters.
Justin Curl is a J.D. candidate at Harvard Law School currently serving as the Technology Law & Policy Advisor to the New Mexico Attorney General. He's interested in technology and public law, with a research agenda focused on algorithmic bias (14th Amendment), binary searches (4th Amendment), and judicial use of AI. Previously, he was a Schwarzman Scholar at Tsinghua University and earned a B.S.E. in Computer Science magna cum laude from Princeton University.
Arvind Narayanan is a professor of computer science at Princeton University and the director of the Center for Information Technology Policy. He is a co-author of the book AI Snake Oil, the essay AI as Normal Technology, and a newsletter of the same name which is read by over 60,000 researchers, policy makers, journalists, and AI enthusiasts. He previously co-authored two widely used computer science textbooks: Bitcoin and Cryptocurrency Technologies and Fairness in Machine Learning. Narayanan led the Princeton Web Transparency and Accountability Project to uncover how companies collect and use our personal information. His work was among the first to show how machine learning reflects cultural stereotypes. Narayanan was one of TIME's inaugural list of 100 most influential people in AI. He is a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE).
Jen Patja is the editor of the Lawfare Podcast and Rational Security, and serves as Lawfare’s Director of Audience Engagement. Previously, she was Co-Executive Director of Virginia Civics and Deputy Director of the Center for the Constitution at James Madison's Montpelier, where she worked to deepen public understanding of constitutional democracy and inspire meaningful civic participation.
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