Private Governance: Creating a Market in AI Regulation, with Dr. Gillian Hadfield & Andrew Freedman

**Erik Torenberg** (0:00)
Hello, and welcome back to The Cognitive Revolution. Today, we're kicking off a short series on creative AI governance proposals. And I'm speaking with Dr. Gillian Hadfield, Bloomberg Distinguished Professor of AI Alignment and Governance at Johns Hopkins University, and Andrew Freedman, Co-Founder and Chief Strategy Officer at Fathom, about their proposal to govern AI via private regulatory markets.
AI is, to put it mildly, a hard technology for society to effectively manage. The relentless march of capabilities advances, the radical uncertainty about how powerful AI systems will get and how soon, the feverish pace of adoption, and the increasingly intense international competition combine to create huge stakes, but still very little clarity on what should be done, with legitimate worries that even the most tech-savvy policymakers could easily get things wrong. And yet, while highly prescriptive government regulation of the sort that Europe is attempting with their AI Act doesn't seem to me likely to meet the moment, the fact that XAI can credibly claim frontier capabilities, even while Grok 4 continues to self-identify as Hitler, suggests that a laissez-faire free-for-all won't serve us well for all that much longer either. Is there any way to create a governance regime that's agile enough to keep up with AI developments, sophisticated enough to address the most important and extreme risks, and yet not so burdensome that I'll still be able to have my AI doctor? It's a hard problem, but Dr. Hadfield and Andrew have a very interesting proposal to harness market mechanisms and hopefully create a race to the top in AI safety standards. It's been introduced into California's legislative process as SB 813, and from what I hear, it does seem to be gaining traction in a number of red states as well. The core idea is to separate the process of democratic deliberation about the outcomes we want and want to avoid from the detailed rulemaking process meant to get us there. In concrete terms, a government body, perhaps the California Attorney General or perhaps a newly created AI safety board, would articulate goals like AI systems must not enable the development of bioweapons, or standards like autonomous vehicles must be safer than human drivers, and then create a competitive ecosystem of private certifiers who develop the safety standards, engage the companies to make sure they're properly implemented, and then report back to the government and public on results. Companies could then choose to work with these approved certifiers, and in exchange for meeting their standards, would receive some level of liability protection when things still end up going wrong. Which, given the unwieldiness of AI systems generally and the unsettled nature of AI liability law, is a serious incentive that would presumably convince many companies to opt in to participate in the system. As a lifelong Libertarian, I really like the idea of trying to bring market dynamism to AI governance. And I appreciate that while this idea is new to the public now, Dr. Hadfield has been developing such concepts for decades, even working with Anthropic co-founder and policy lead Jack Clark on related ideas as early as 2019 Andrew, for his part, brings invaluable practical implementation experience to the table as well, having worked as Colorado's cannabis are while the state was rolling out a new regulatory system for legal marijuana. Nevertheless, as you'll hear, I press them on several important concerns. How do we avoid a race to the bottom, where companies simply choose the most permissive certifier? How would the liability protections interact with existing tort law? And what exactly are people giving up in terms of their ability to sue? Do we have any organizations that could step up and do a good job in the role of private regulator? And who do we really have to trust to do a good job for such a system to work not just in the beginning, but on an ongoing basis? In the end, there's no silver bullet. Any governance system that we might design does ultimately rely on some number of people doing a good job in key roles. But I do come away from this conversation optimistic than an arrangement of this sort. If it could put the good folks at FAR AI, Neater, or other similarly tech savvy organizations in a position of some real authority, could deliver much more responsive regulation than the government could muster on its own, while also making sure that society is not flying entirely blind into the fast approaching AI future. Coming up soon, we'll have another episode with Professor Gabriel Weill, who has a very different proposal to address many of the same core concerns via liability law. So please stay tuned for that, and definitely reach out to let me know which of these ideas you find most promising, or if there are other proposals that you think would be better yet. With that, I hope you enjoy this exploration of a proposal to harness market dynamism to effectively govern AI technology. With Dr. Gillian Hadfield of Johns Hopkins and Andrew Freedman of Fathom. Dr. Gillian Hadfield, Bloomberg Distinguished Professor of AI Alignment and Governance at Johns Hopkins University, and Andrew Freedman, Co-Founder and Chief Strategy Officer at Fathom. Welcome to the Cognitive Revolution.