Scaling Laws

Melissa Hutchins, founder and CEO of Certifi AI, joins Kevin Frazier, AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to discuss the rise of deepfakes, non-consensual sexually explicit imagery, and the growing policy fight over AI-generated harms online.

Drawing from both her professional work and her personal experience as a victim of cyberstalking, Melissa explains how synthetic media is changing the threat landscape for individuals, platforms, and policymakers alike. The duo also unpack proposals like the Take It Down Act, the challenges posed by a fragmented patchwork of state AI laws, and what it’s like building an AI company from Seattle rather than Silicon Valley.
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Adeel Khan of MagicSchool AI and Ryan Trattner of StudyFetch join Kevin Frazier, AI Innovation and Law Fellow at the University of Texas School of Law and Senior Editor at Lawfare, to discuss the rapid integration of artificial intelligence into education.

The conversation explores how AI tools are being used by both teachers and students, from automating lesson planning to providing personalized tutoring and study support. The group examines claims about improved learning outcomes and time savings, while probing what counts as meaningful evidence versus early-stage or self-reported metrics.

They also discuss the regulatory and operational challenges of building AI systems in education, including constraints imposed by student data protections, limited access to high-quality training data, and the growing impact of regulations and public scrutiny on product development and deployment.
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John McAuliff, a Delegate in the Viriginia House of Delegates, joins Kevin Frazier, Director of the AI Innovation and Law Program and a Senior Fellow with the Abundance Institute, to discuss the ongoing debates around data centers at the state level.

John was one of the first candidates to recognize data centers as a key issue. He had to convince his polling team to put the issue on early surveys. Of course, they soon realized he was on to something. In his first legisatlive session as a delegate, John championed legislation to try to help counties negotiate with data center developers. He's not done working on the topic. Learn more about his plans and related issues by giving this episode a listen.
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Cathy O’Neil, CEO of ORCAA and author of Weapons of Math Destruction and The Shame Machine, joins Kevin Frazier, AI Innovation and Law Fellow at the University of Texas School of Law and Senior Editor at Lawfare, to explore the promises and limits of algorithmic auditing.

The conversation examines what audits actually do in practice, how organizations measure and mitigate bias, and why context—not just code—determines whether an AI system causes harm. O’Neil explains why auditing cannot be reduced to a checklist, where it can meaningfully improve outcomes, and where it risks creating a false sense of security.

They also discuss the need for evidence-based AI policy, the challenges of translating ethical concerns into measurable standards, and how regulators should think about auditing as part of broader governance frameworks.

Logan Le-Jeffries, a wonderful member of the AI Innovation and Law Program, provided research assistance on this episode.

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Sean Perryman, AI policy lead at Uber and lecturer on AI Governance and Ethics at Vanderbilt Law School, joins Kevin Frazier, the Director of the AI Innovation and Law Program at the University of Texas School of Law and a Senior Fellow at the Abundance Institute, to explore the rapidly evolving debate over algorithmic pricing and AI governance.

The conversation begins with the rise of state-level efforts to regulate algorithmic pricing to unpack what these systems are actually doing and why they provoke strong reactions. Perryman examines the political motivations behind these regulatory efforts, the economic tradeoffs they often overlook, and the risk of unintended consequences.

The discussion then broadens to a central theme in Perryman’s work--including his Substack, The Human Cost--not all AI systems raise the same risks. Different use cases require fundamentally different governance approaches—yet policy debates often flatten these distinctions.

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