Escaping One-Size-Fits-All AI Policy with Sean Perryman
From Scaling Laws by Lawfare & University of Texas Law School
May 15, 2026 · 41 min
About this episode
Sean Perryman discusses the complexities of AI governance and the implications of algorithmic pricing regulation.
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. Hosted on Acast. See acast.com/privacy for more information.
People in this episode
Host: Kevin Frazier
Guest: Sean Perryman
Topics covered
- AI policy
- algorithmic pricing
- AI governance
- regulation
- economic tradeoffs
- political motivations
Keywords
- AI policy
- algorithmic pricing
- governance
- regulation
- economic tradeoffs
- politics
- unintended consequences
Mentioned in this episode
Organizations: Uber, Vanderbilt Law School, University of Texas School of Law, Abundance Institute
Books & works: The Human Cost
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