Scaling Laws

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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In this episode of Scaling Laws, Kate Klonick, Associate Professor of Law at St. John’s University and a fellow at the Brookings Institution, and Kevin Frazier, Director of the AI Innovation and Law Program at the University of Texas School of Law and a senior fellow at the Abundance Institute, are joined by Marietje Schaake, the International Policy Director at Stanford University’s Cyber Policy Center and author of The Tech Coup: How to Save Democracy from Silicon Valley. A former Member of the European Parliament, Schaake has long been a leading architect of digital rights and tech governance.

Their conversation explores the central thesis of her work: that a handful of tech giants have effectively staged a "coup" over democratic functions, from national security to the very infrastructure of public discourse. They examine the democratic implications of AI development, the "privatization of policy," and why Schaake believes that without urgent intervention, the "rule of law" is being replaced by the "rule of code."

To get in touch with us, email [email protected]. Logan Le-Jeffries, a member of the AI Wranglers student program at the University of Texas School of Law, provided research assistance with this episode.
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Bennett Borden, Founder and CEO of Clarion AI Partners, joins Kevin Frazier, the AI Innovation and Law Fellow at UT and a Senior Fellow at the Abundance Institute, to discuss AI adoption as well as the future of the law and legal practice. The two explore Bennett’s unique background, Clarion’s AI interdisciplinary approach, and the importance of AI adoption. They also cover innovative work underway at major AI labs to align model use with user expectations. Hosted on Acast. See acast.com/privacy for more information.

In this episode of Scaling Laws, we explore how the "black box" of global greenhouse gas emissions is being cracked open by artificial intelligence and satellite imagery.

Kevin Frazier, Director of the AI Innovation and Law Program at the University of Texas School of Law and a Senior Fellow at the Abundance Institute, talks with Gavin McCormick, the founder of ClimateTrace, a global coalition that has revolutionized the process of identifying and quantifying emissions.

For decades, climate policy has relied on self-reported data from nations and corporations—a system prone to gaps and "greenwashing." McCormick’s work leverages machine learning to monitor every major source of emissions on Earth in near real-time. We discuss the legal implications of "radical transparency," how AI-driven data can be used to enforce regulations and measure claims, and the myths and facts of AI’s environmental consequences.

To get in touch with us, email [email protected].

Logan Le-Jeffries, a member of the AI Wranglers student program at the University of Texas School of Law, provided research assistance with this episode.

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Scott Sullivan, professor of law at the U.S. Military Academy at West Point and a leading contributor to the Manual on International Law Applicable to Artificial Intelligence in Warfare, joins Kevin Frazier, AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to examine whether AI should be understood as a “normal” or “abnormal” technology.

Drawing on his recent article, Sullivan argues that while AI may diffuse slowly and unevenly in civilian contexts, military AI operates under fundamentally different conditions—where strategic competition rewards speed, costs are often externalized, and meaningful oversight is limited by secrecy and epistemic uncertainty.

The conversation explores how these dynamics challenge prevailing AI governance frameworks, what current military deployments reveal about the trajectory of AI adoption, and whether existing legal and policy tools are equipped to manage a domain where the pace of technological integration may outstrip the institutions designed to constrain it.
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