Scaling Laws

Kent Walker, President of Global Affairs at Google and Alphabet, joins Kevin to discuss Google's proposal for a two-pronged approach to AI governance: a Frontier AI Regulatory Organization, which like FINRA, would operate as an independent, industry-based governance body overseen by a federal agency and the application of existing laws to widely-deployed, less capable systems.The two also discuss the timing behind this proposal and its relevance in light of the recent Hugging Face / OpenAI incident.Follow Kent: @kent_walker

Assemblymember Alex Bores ran for Congress on a platform that in many ways centered on AI policy. He therefore drew considerable support as well as substantial opposition from interest groups across the country. Though Bores lost in the Democratic primary, his experience is worth exploring in detail.Alan and Kevin dive in with some key questions:what did he hear from voters on AI? are everyday New Yorkers worried about benchmarks being saturated?how did the millions of dollars coming into the race change its dynamics?what does this early episode in the political aspects of AI signal for the future of AI governance?what's the proper allocation of AI regulatory authority between states and the federal government?Follow Alex at @alexbores And, as always, get in touch with Kevin via @scaling_laws and @kevintfrazier

Courtney Cox, Associate Professor of Law at Fordham Law School, joins Kevin Frazier, AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to discuss her forthcoming article, Hardwiring Hercules?.It’s a great read that builds on Dworkin’s idea of a perfect adjudicator, Hercules. Courtney argues that the debate over a “right to a human decision” has missed a central problem: normative uncertainty. Machines may struggle to explain their decisions, but humans often struggle too—especially when judges are uncertain about what they ought to do. At the same time, the common response that people merely have a right to a “better decision,” whether by human or machine, assumes we know what “better” means. Courtney’s paper challenges both sides of the debate and asks what AI governance should look like when regulators, engineers, and judges cannot simply “hardwire Hercules.”

Nils Tracy, founder of Authorship, joins Kevin Frazier, the AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to detail the challenges and solutions to deploying AI in highly sensitive contexts.Authorship enables users to map their AI policies to myriad use cases--from on-device AI tools to those connected to the cloud. It's a direct effort to tackle concerns that as AI use cases become more frequent and varied deployers may struggle to ensure compliance with key policies and laws. 

Joe Seddon, Founder and CEO of Zero Gravity, joins 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, to discuss AI, social mobility, higher education, and the future of opportunity. Zero Gravity is a UK-based platform that helps launch students from low-opportunity backgrounds into leading universities and prosperous careers. The conversation explores whether AI can scale the kinds of mentorship, admissions advice, tutoring, and career guidance that have historically been available only to students with strong networks. The two also examine the future of elite credentials, the role of universities in preparing students for an AI-transformed labor market, and whether AI will disrupt entry-level white-collar work in ways that require new approaches to retraining, apprenticeships, and lifelong learning.

Adi Tantravahi, founder of Cofactor, joins Kevin Frazier, the AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to talk about how AI can help cut through the administrative red tape that underlies and, in many ways, undermines the modern healthcare system.Cofactor’s AI platform focuses on denial management—an area where hospitals routinely lose revenue because insurance claims go unchallenged due to staffing constraints. Kevin and Adi unpack the economics of healthcare billing, why administrative overhead has grown so dramatically in American medicine, and how AI systems capable of autonomously managing appeals and reimbursement workflows might reshape the financial infrastructure of hospitals.

Andy Masley joins Kevin Frazier, director of the AI Innovation and Law Program at the University of Texas School of Law and a senior editor at Lawfare, and Alan Rozenshtein, research director at Lawfare and associate professor at Minnesota Law, to unpack the increasingly contentious issues related to data centers.They discuss Andy’s efforts to challenge what he sees as misleading claims about data center water use, land use, electricity rates, and local community impacts. Be sure to check out Andy’s substack here.

Kal Clark, co-founder of Zauron Labs, joins Kevin Frazier, the AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to explain how AI is already reducing diagnostic errors in radiology.Kal details how Zauron’s AI system functions as a second-look safety layer, reviewing imaging exams for high-impact missed findings before those results translate into patient outcomes.Kal and Kevin then discuss the scale of diagnostic error in modern healthcare, the institutional barriers that have prevented systematic second reviews, and how open-source AI models combined with on-premise deployment might allow hospitals to build their own diagnostic intelligence while protecting patient data.

Alan Rozenshtein, associate professor of law at the University of Minnesota and research director at Lawfare, and Kate Klonick, associate professor of law at St. John's University School of Law and a senior editor at Lawfare, spoke with science fiction novelist and technology journalist Cory Doctorow about about his new book, The Reverse Centaur's Guide to Life After AI, which argues that AI is being deployed to turn workers into "reverse centaurs" who serve machines rather than direct them, and that the economics of the AI industry add up to an unsustainable bubble. The conversation covered the distinction between centaurs and reverse centaurs in automation theory; why Doctorow thinks the AI business loses money on every customer and can't pencil out; whether the AI boom is a "productive residue" bubble like the dot-com fiber glut or a pure value-destroyer like crypto; how AI has fused with the state and the stock market, raising the prospect of a slow deflation rather than a clean crash; whether statistical inference can ever amount to genuine understanding; AI's effect on labor, from warehouse injury rates to the burden of "marking the AI's homework"; AI art and the problem of intention; security risks like "slop squatting"; and the threat of knowledge collapse and what it means for the future of education.