Scaling Laws

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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