Explore every episode of the podcast Scaling Laws

Kevin Frazier, Director of the AI Innovation and Law Program at the University of Texas School of Law and a senior editor at Lawfare, speaks with Roberto Tallarita, assistant professor at Harvard Law School, about Anthropic's recently filed s-1 and its experiment in corporate governance. They discuss its current status as a public benefit corporation, its decision to create and empower a body of financially disinterested trustees, and its current unique class structure. Drawing on Tallarita’s research on stakeholder governance and unequal voting rights, the two also discuss what would make a commitment to safety precautions durable even when in stark tension with profit.

Tallarita lays out some of his thoughts on what could come next for Anthropic in his recent article “Profit and Mission in Anthropic’s IPO.” Frazier also has recently written an analysis of Anthropic’s post-IPO governance.

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One week before Election Day, the Scaling Laws Roadshow visited Emory Law for a conversation with Stacey Abrams, former Minority Leader of the Georgia House of Representatives, bestselling author, entrepreneur, and producer. She joined Kevin Frazier, Director of the AI Innovation and Law Program at the University of Texas School of Law and Senior Editor at Lawfare, and Alex Bores, New York Assemblymember and co-founder of Who Decides.

The three explored Abrams’s frameworks for rebuilding democratic power, her efforts to connect people with opportunities to participate, and the role AI might play in those efforts. Leader Abrams also provided an overview of the Ten Steps Campaign, which you can check out here; https://10stepscampaign.org/

Big thanks to Dean Freer, Professor Sag, Matt Winston, and Nadia Hedayat for making the visit possible.

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What should a state government have to demonstrate before it asks residents to trust an AI system?

In this episode of Scaling Laws, Nik Blosser, Oregon’s Chief AI Officer, 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, to discuss Oregon’s approach to adopting and governing AI.

They explore Blosser’s role, Oregon’s Medicaid information chatbot and its public disclosure card, and Governor Tina Kotek’s recent executive order on frontier-model procurement. The conversation also considers the limits of state expertise and purchasing power, and the AI issues likely to shape Oregon’s 2027 legislative session.

Big thanks to Ellie Lewis and Maggie Byrne of the AI Student Association for hosting Scaling Laws in Eugene!

Check out the Oregon AI System Disclosure Card.

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Live from Grand Forks, North Dakota!

Should the public be upset that courts aren’t using more AI? Justice Jerod Tufte of the North Dakota Supreme Court 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, to take up that question. Drawing on his background in computer engineering and his own experience testing and applying new tools, Tufte considers what the public should expect from courts as AI’s capabilities grow.

The conversation builds on Kevin’s study of how AI may alter government and the operation of our constitutional system. How should judges weigh the risks of adopting new tools against the costs of delay? What might those choices mean for the judiciary’s ability to fulfill its constitutional role? Together, Kevin and Justice Tufte examine how decisions about AI could shape the capacity of public institutions to serve the people who depend on them.

Big thanks to the University of North Dakota School of Law for hosting!

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What happens to society, law and privacy when artificial intelligence makes it possible for police to detect nearly every observable crime? Matthew Tokson, Director of the Criminal Law Program and Associate Dean for Research and Faculty Development at the University of Utah S.J. Quinney College of Law, joins Kevin Frazier, director of the AI Innovation and Law Program at the University of Texas School of Law and a Lawfare Senior Fellow, to discuss this question. They recorded this conversation at the University of Nebraska College of Law as part of the Scaling Laws Roadshow.

For more, read Tokson's article, "Artificial Intelligence and Near-Total Law Enforcement," in the Nebraska Law Review.

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Hélène Landemore, Professor of Political Science at Yale University and a fellow at Oxford’s Institute for Ethics in AI, 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, to examine who should decide what AI is for. Starting with Landemore’s recent Noema essay, the pair discuss why decisions about AI’s purpose, limits, and governance should not be left solely to elected officials, technical experts, and the companies building the systems.

Landemore explains some key ideas--covering the fundamentals of deliberative democracy, sortition, and citizens’ assemblies. They then explore her proposal for global public consultation and deliberation. The duo conclude with hard questions about representation, expertise, and platform power.

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Dave Willner, co-founder of Zentropi, and Vaishnavi J., founder and principal of Vys, join 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 examine how AI is affecting younger users and why existing child-safety responses often default to age gates, parental consent, and outright bans.

The conversation then turns to their open-source teen self-harm and suicidal ideation policies, which use age-banded rules and a four-zone framework: remove, suppress with a warning, suppress from recommendations, and allow. Dave and Vaishnavi explain how the policies were developed using more than 1,200 hand-labeled examples, how Zentropi’s CoPE classifier translates written policy into enforcement, and how platforms should evaluate false positives, false negatives, over-refusal, under-refusal, human review, and appeals.

Dave's Tech Policy Press piece.

More on their classifer and research.

Explainer blog - Overall: https://quire.substack.com/p/what-it-takes-for-llms-to-make-age

Explainer blog - Part 1: https://quire.substack.com/p/f4b99ab0-0127-4992-a31d-67b989f2cf58

Explainer blog - Part 2: https://quire.substack.com/p/ae6a5436-21e5-4fec-81fe-8025004f3b16

Full set of policies: https://zentropi.ai/u/vys

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Chloé Bakalar, ASI Ethics Lead at Responsible Superintelligence Institute (RESI) and a Senior Research Associate at University College London, 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, for a Scaling Laws Roadshow conversation recorded at Columbia Law School. Big thanks to Eliza Steffen for organizing a fantastic visit.

Recorded on the eve of Constitution Day, Chloé and Kevin explore the purposes of political constitutions, the American experience with constitutional change, and debate the extent to which the U.S. Constitution constrains private power. They then turn to AI constitutions: who writes them, whose values they reflect, how those principles are interpreted and revised, and how we can tell whether they meaningfully constrain an AI system.

The conversation closes by testing a broader proposal: whether governing advanced AI may require a dual constitutional structure—one governing the model itself and another governing the companies that develop and deploy it.

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Kenji Yoshino, Chief Justice Earl Warren Professor of Constitutional Law at New York University School of Law and a member of Meta’s Oversight Board, joins Kevin Frazier, director of the AI Innovation and Law Program at the University of Texas School of Law, and guest co-host Kate Klonick to discuss what frontier AI companies can learn from the Oversight Board. Yoshino recently co-authored a Tech Policy Press piece with fellow Board member Ronaldo Lemos arguing that meaningful AI oversight should feature independent and representative overseers, external standards, and transparent, reasoned decisions.

The trio tests that proposal against some of the hardest questions raised by the Oversight Board’s own experience. Can a selective, precedent-setting institution provide meaningful oversight at AI scale? What gives a privately created board legitimacy to constrain decisions with global consequences? What powers would an AI oversight body actually need? And when does private oversight complement democratic regulation—and when might it merely give corporate power a new source of legitimacy?

Here’s the Tech Policy Press piece.

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Christina Lee, Visiting Associate Professor of Law and Privacy and Technology Law Fellow at George Washington University Law School, 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, from the Institute of Law and AI’s Workshop on Law-Following AI in Cambridge, UK.

They discuss her forthcoming article, Beyond Algorithmic Disgorgement: Remedying Algorithmic Harms. 

The conversation begins with the basics: what is algorithmic disgorgement, why did the FTC first use it in the Cambridge Analytica case, and how has the remedy evolved from data-deletion-plus-model-deletion orders into a much broader candidate remedy for AI harms? Christina explains why the remedy’s expansion matters, especially after the FTC’s Rite Aid settlement, where the alleged wrong was not unlawful data collection but the allegedly unfair use of facial recognition technology.

They also discuss alternative remedies, including injunctions, post-processing, fine-tuning, machine unlearning, and training-data attribution. Finally, they wrap up with Christina’s professional journey and the future of legal education in the age of AI.

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Bri Treece, Executive Director of PACT AI, and Dr. Rob Slone, Chief Scientist & Innovation Officer at UL Solutions, join Kevin Frazier, Director of the AI Innovation and Law Program at Texas Law and a Senior Editor at Lawfare, to discuss a neglected layer of AI governance: the organizations that deploy AI in real-world products, services, and operations.

They discuss why PACT AI was formed, what AI assurance can learn from other industries, and why evaluating AI cannot be a one-time exercise. The conversation also covers PACT AI’s 90-day formation process and UL Solutions’ pre-existing work on AI-enabled products. Finally, Kevin asks Bri and Rob to pin down the major barriers facing the broader AI assurance ecosystem.

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Brandon Mitchell, founder of WriteSea, joins Kevin Frazier, the AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to discuss the growing role of artificial intelligence in workforce development. WriteSea’s platform provides AI-driven career guidance, helping job seekers refine resumes, practice interviews, and navigate modern hiring systems that increasingly rely on automated screening tools.

As policymakers and the public writ large assess the extent to which AI will disrupt the labor market, Brandon's efforts warrant particular attention. New tools such as WriteSea may play a key role in helping entry-level workers find jobs that align with their skillset. 

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Anil Seth, Professor of Cognitive and Computational Neuroscience and Director of the Sussex Centre for Consciousness Science at the University of Sussex, 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, to examine whether artificial intelligence could ever be conscious.

Drawing on Seth’s essay, “The Mythology of Conscious AI,” the pair attempt to define consciousness, develop the strongest arguments for and against machine consciousness, and assess what the current evidence can—and cannot—tell us. They also discuss the risks posed by AI systems that are perceived to be conscious and what AI labs, policymakers, and users should do amid profound uncertainty.

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Matt Abrams, technologist, investor, and co-founder of $1 Billion for Trust, 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 collapse of institutional trust and how AI may accelerate — or potentially help reverse — that trend.

The conversation explores Matt’s work to rebuild trust in information ecosystems, interpersonal relationships, and major institutions. Along the way, the duo examine the relationship between AI, information integrity, labor disruption, institutional legitimacy, and democratic resilience.

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Matthew Schwartz, founder of Virgo, joins Kevin Frazier, the AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to discuss how AI is beginning to reshape gastroenterology. Virgo’s model is trained on one of the largest collections of endoscopy procedure videos ever assembled, opening new possibilities for earlier diagnosis, personalized treatment of diseases like inflammatory bowel disease, and faster clinical research.

The duo also examine how medical imaging data can generate new “digital biomarkers,” what role AI might play in shortening clinical trials, and how regulators and healthcare institutions are grappling with the promise—and risks—of deploying AI in clinical environments.

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Daniel Kokotajlo, former OpenAI researcher and executive director of the AI Futures Project, joins Kevin Frazier, Director of the AI Innovation and Law Program at Texas Law and Senior Editor at Lawfare, to detail his policy recommendation–AI 2040: Plan A. It’s a thorough analysis of a policy pathway to delaying superintelligence, which Daniel and his co-authors think is necessary to ensure that the disruptive effects of highly-capable AI systems do not outweigh the benefits. 

Kevin asks Daniel to explain scenario scrutiny, address feedback from other AI policy stakeholder such as Tom Davidson, and detail what led him to already alter his estimation of how likely it is that policymakers adopt Plan A.

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DZ Kalman, fellow at the Berkman Klein Center, research fellow at the Shalom Hartman Institute, senior advisor at Sinai & Synapses, and host of Belief in the Future, joins Kevin Frazier, AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to explore what religious traditions can teach AI governance.

DZ and Kevin discuss religious responses to AI, Jewish technoculture, kosher supervision as a model for AI certification, and the limits of AI use in faith contexts. They also connect these traditions to contemporary debates about alignment, institutional trust, human dignity.

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Laura Davis, founder of USLege, joins Kevin Frazier, the AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to dive into how USLege is leveraging AI to transform the way professionals monitor and respond to government activity.

USLege’s platform aims to be the answer to the prayers of many policy stakeholders. It captures and analyzes legislative hearings, regulatory discussions, and committee proceedings as they happen, surfacing policy signals that often emerge long before a bill is formally introduced. Kevin and Laura talk about the fragmented information systems that shape American policymaking, how AI tools are transforming the practice of government affairs, and whether technologies like “live government listening” could make legislative activity more transparent and responsive to public demands.

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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

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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

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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.”

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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. 

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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.

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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.

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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.

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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.

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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.

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Dhruv Diddi, founder of Solo Tech, joins Kevin Frazier, the AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to discuss the emerging frontier of Physical AI. Solo Tech builds infrastructure that allows developers to deploy AI models directly onto robots and edge devices rather than relying on cloud-based computation. In other words, think about allowing AI systems to operate in remote areas that have traditionally struggled to leverage the latest and greatest tech.

Kevin and Dhruv look into what it takes to move AI systems out of digital environments and into the physical world. They also chat about the idea of "gyms" for AI and policy challenges associated with highly-sophisticated robots becoming more ubiquitious. 

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Alan Rozenshtein, Research Director at Lawfare, spoke with Robert Wright—author of Nonzero, The Moral Animal, The Evolution of God, and Why Buddhism Is True, and the writer behind the NonZero Newsletter and podcast—about his new book, The God Test: Artificial Intelligence and Our Coming Cosmic Reckoning, which argues that AI is an evolutionary threshold on the scale of the entire history of life, that we are collectively failing to grasp its magnitude, and that rising to the challenge will require both new forms of international governance and an expansion of human moral and cognitive perspective.

The conversation covered the multiple meanings of the book's title and what it means to view AI from a "cosmic" perspective; whether the public is finally starting to "feel the AGI" and where skepticism about AI's capabilities now comes from; how large language models are trained and Wright's claim that we have built "machines that create machines that think"; whether these systems genuinely understand, what Searle's Chinese Room and Nagel's "what is it like to be a bat?" have to do with it, and the open question of AI moral patienthood; the two families of AI risk—bad actors empowered by AI versus AI itself going rogue—and why the near-term disruption to jobs, relationships, and security may matter most; the "But China!" argument against AI regulation, China hawkishness, and why Wright thinks racing toward superintelligence is dangerously destabilizing; the case for "global governance" over "world government" and the perils of concentrating AI power at home; and why a book about AI and geopolitics closes with a call for mindfulness, cognitive empathy, and transcending the psychology of tribalism.

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In this cross-pod episode, Alan and Kevin join Seth Benzell and Andrey Fradkin of Justified Posteriors to explore a big question: what should AI be for?

The conversation begins with Pope Leo XIV’s recent encyclical. The group discusses how economists should think about the Church’s role in AI debates, what counts as an AI-related market failure, whether moral and religious institutions can help address social harms, and whether such interventions risk crowding out private action or local experimentation.

The episode then turns to the emerging idea of positive alignment. A recent paper, Positive Alignment: Artificial Intelligence for Human Flourishing, argues that AI alignment has focused too heavily on negative alignment—preventing harms such as manipulation, bias, dangerous outputs, and misuse—and should also ask how AI systems can actively support autonomy, wisdom, truth-seeking, pluralism, and human flourishing.

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Shane Tews, host of Explain to Shane and nonresident senior fellow at AEI, 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, for a cross-post conversation about the AI and cyber executive order, workforce disruption, and the future of education. They also share their respective research agendas for the summer.

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Janel Thamkul, former frontier counsel team member at Anthropic, joins Kevin Frazier to discuss what it means to practice law at the frontier of AI.

This episode starts with a review of Janel’s fascinating and varied background. Next, she walks through her initial exploration of a career in art before eventually pivoting to the law based on some very formative experiences. Kevin and Janel then investigate some of the most pressing and open questions related to transformative AI.

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Alan Rozenshtein, Research Director at Lawfare and Visiting Senior Fellow at the Institute for Law & AI (LawAI), spoke with Christoph Winter, LawAI Founding Director and Assistant Professor of Law and AI at the University of Cambridge, and LawAI Senior Research Fellow Charlie Bullock, about their new paper "Radical Optionality: Governing Transformative AI Under Uncertainty," which argues that, given the possibility of transformative AI within the next decade and deep uncertainty about its capabilities and risks, governments should aggressively build the institutional capacity to regulate competently when needed, rather than either deferring to the market or locking in premature substantive rules.

The conversation covered the four foundational assumptions underlying the paper and what makes the optionality "radical"; the difficulty of regulating an exponentially improving and poorly understood technology and what it means to "feel the AGI"; why a pure permissionless-innovation approach breaks down once the national-security implications of transformative AI come into view; why the European precautionary approach risks regulating without the expertise to enforce; the centrality of hiring and talent and what an adequately funded U.S. counterpart to the UK AI Security Institute would look like; the concrete work that such an agency would do, including evaluations, standard-setting, and procurement-side cybersecurity requirements modeled on CMMC; the importance of building international information-sharing channels among liberal democracies before they are urgently needed; and the case against broad federal preemption of state AI laws before any federal regulatory framework exists.

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Tom Davidson joins Kevin Frazier, AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to discuss AI timelines, explosive economic growth, and the increasingly urgent debate over “AI character” — the behavioral traits and decision-making tendencies embedded into advanced AI systems.

Drawing on Davidson’s recent paper, “The Importance of AI Character,” which he co-authored with Will MacAskill, their conversation explores how the character of future AI systems may influence democratic governance, military conflict, institutional trust, and even the long-run trajectory of civilization. The discussion also examines the key influences on character development and which actors should ultimately play a part in dictating the default values and behaviors of AI models. 

You may also enjoy Tom's article on AI as advisors.

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Owen Larter, Senior Director and Head of Frontier Policy and Public Affairs at Google DeepMind, joins Kevin Frazier, AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to provide an inside look at how DeepMind approaches frontier governance. 

The conversation moves beyond the familiar U.S.-EU-China framing of AI policy to examine international coordination after the recent U.S.-China summit, Google DeepMind’s national AI partnerships, the role of the Frontier Model Forum, and the challenge of expanding AI adoption. Kevin and Owen also discuss policy formation inside frontier AI companies. They close with an examination of the need to build a deeper AI policy talent pipeline.

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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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Deger Turan, CEO of Metaculus, joins Kevin Frazier to unpack new forecasts on how AI could reshape the labor market over the next decade.

The conversation centers on a striking divergence between Metaculus forecasts and projections from institutions like the Bureau of Labor Statistics—raising fundamental questions about whether existing tools for understanding the economy can keep pace with rapid technological change.

Deger walks through key findings from the Labor Automation Forecasting Hub, including:

• A potential decline in overall employment by 2035
• Increased pressure on entry-level workers and early-career pipelines
• The emergence of “lean” firms generating more value with fewer employees
• A counterintuitive “wage paradox,” where fewer jobs may coincide with higher wages
• The growing role of political power, regulation, and licensing in shaping labor outcomes

The discussion also explores second-order effects, including how contraction in high-paying sectors could ripple through local economies, and what a shift away from traditional four-year degrees might mean for students and policymakers.

Finally, Deger situates these forecasts within a broader vision: forecasting as a form of epistemic infrastructure. As AI accelerates change, the ability to form accurate beliefs about the future—and update them quickly—may become a core component of effective governance.

*** - This episode was recorded on April 23, 2026. Metaculus is a live platform. It's likely that forecasts mentioned have subsequently changed.

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Alan Rozenshtein, Associate Professor of Law at the University of Minnesota and Research Director at Lawfare, and Kevin Frazier, AI Innovation and Law Fellow at the University of Texas School of Law and Senior Editor at Lawfare, spoke with Dean Ball, Senior Fellow at the Foundation for American Innovation and former Senior Policy Advisor for AI at the White House Office of Science and Technology Policy, about the Trump administration's reported plans to vet frontier AI models before public release.

They discussed how Anthropic's Mythos model reshaped the administration's posture on AI risk; why the executive branch lacks clear legal authority for a mandatory pre-deployment vetting regime; the voluntary "kick the tires" framework Frazier and Ball have proposed using CAISI and the Cyber Resilience Fund; whether an FDA-style licensing regime is ultimately inevitable for frontier AI; and the institutional design challenges of building AI oversight that can scale with rapidly improving model capabilities.

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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 scalinglaws@lawfaremedia.org. 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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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 scalinglaws@lawfaremedia.org.

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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Senior Editor Kate Klonick interviews reporters Ronan Farrow and Andrew Marantz on their recent article in the New Yorker, titled “Sam Altman May Control Our Future—Can He Be Trusted?” In their 16,000-word piece, Farrow and Marantz create a cohesive narrative with receipts around Sam Altman, the products he's building at OpenAI, and how he's selling them not just to investors and the public, but also to regulators and world leaders.

Klonick unpacks three key areas that are discussed in the piece: potential concerns of fraud, ongoing trust and safety and alignment issues at OpenAI, and the national security concerns that the article exposes in the "country plan" and Altman's entanglements in the Gulf. The discussion ends with a basic question: Are any of these legal issues enough to stop or correct the course of OpenAI, with its estimated $1T IPO in the coming weeks?

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Alan Rozenshtein, research director at Lawfare, spoke with Miles Brundage, founding executive director of the AI Verification and Evaluation Research Institute (AVERI) and former senior advisor for AGI readiness at OpenAI, about the state of AI safety and accountability and AVERI's vision for independent third-party auditing of frontier AI companies.

The conversation covered the weaknesses of current AI regulations, including California's SB 53 and New York's RAISE Act; why Brundage left OpenAI to build an independent nonprofit; AVERI's case for shifting the unit of analysis from individual AI models to the organizations that build them; the "Volkswagen problem" of deception-proofing safety evaluations; a framework of AI Assurance Levels ranging from baseline transparency to treaty-grade verification; the limitations of safety benchmarks and the BenchRisk project's findings; market-based mechanisms for driving audit adoption, including insurance, procurement, and investor pressure; and how AVERI navigates the tension between proximity to industry and independence from it.

Mentioned in this episode:

• Frontier AI Auditing: Toward Rigorous Third-Party Assessment of Safety and Security Practices at Leading AI Companies, Averi 2026
• Risk Management for Mitigating Benchmark Failure Modes: BenchRisk, NeurIPS 2025
• Why I'm Leaving OpenAI and What I'm Doing Next, Miles Brundage, Substack, October 2024

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