Scaling Laws

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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