Liability for AI Harms: How Ancient Law Can Govern Frontier Technology Risk, with Prof Gabriel Weil

**Nathan Labenz** (0:00)
Hello, and welcome back to The Cognitive Revolution. Today, we're continuing our short series on creative AI governance proposals with Gabriel Weil, Assistant Professor of Law at Touro University and Senior Fellow at the Institute for Law and AI, who argues that liability law may be our best tool for shaping the decisions that AI developers make. As we covered in our last episode on private regulatory markets, the pace of AI capabilities' advances and adoption, the radical uncertainty around the timing, nature, and impact of AGI and superintelligence, and the backdrop of international competition present a singularly difficult challenge for governments. For good reason, they worry that heavy-handed regulation could undermine our ability to realize the great upside of AI, while at the same time it's becoming clearer and clearer, one Mecha-Hitler episode at a time, that we can't simply trust companies to do the right thing for society while they're primarily focused on one-upping one another. So is there any way to govern AI that can keep up with technology developments, meaningfully reduce the most important risks, and still keep the dream of curing all diseases alive? Professor Weil brings another compelling idea to the table. Rather than trying to predict issues and prescribe safety standards from a distance, why not use liability law to incentivize AI developers to properly consider and account for the risk that their development and deployment decisions are imposing on the rest of society? Because I'm no lawyer, and I know that most of you aren't either, we begin this conversation with a primer on liability law, covering negligence, product liability, and the doctrine of abnormally dangerous activities, before diving in to how these frameworks might apply to frontier AI development. The key advantages to using liability law in this way are that the liability risk that a company faces scales naturally with the risks it takes. If the systems are safe, there's nothing for anyone to worry about. And unlike most other proposals, which would require new legislation, liability law is well established and has proven over centuries of evolution that it can adapt to new situations and technologies. Still, of course, important questions arise around the different types of harms that AI systems can cause and the mechanisms by which they come about. Throughout this conversation, we explore concrete scenarios that highlight the complexities, including the tragic character AI case, phone call agents that can call unsuspecting people and speak to them with increasingly lifelike cloned voices, and coding agents that might overwhelm APIs or outright hack critical systems. Considering in each case how responsibility should be shared by the model developers, both closed and open source, as well as the application developers and end-users. Notably, Professor Weil does want to make sure that society gets the benefits of AI, even as it remains imperfect. And so he's less focused on changing how AI companies serve customers with products like AI doctors or self-driving cars, and instead emphasizes the risk of harm to third parties who were not part of the commercial relationship between the AI companies and their customers. Those could be the pedestrians who share space with self-driving cars, or the public as a whole, which it seems will face at least some increased risk of pandemic and other large-scale systemic harms. Within this category, he treats misuse, where a person is intentionally trying to use an AI system to cause harm, quite distinctly from misalignment, where the AI system itself breaks bad for whatever reason. His most provocative proposal involves using punitive damages as a mechanism for addressing what would otherwise be uninsurable catastrophic risks. If an AI system causes a relatively small harm, but evidence shows that the situation could easily have gone much worse than it did, Professor Weil argues that punitive damages offer a way to hold companies accountable not just for the actual harm, but for the risk they irresponsibly ran. Considering the magnitude of harms that people worry about when it comes to bio and cybersecurity, such a judgment could in theory be existential, even for the most powerful and deep-pocketed companies. And as such, this does seem like a promising way to get companies to properly internalize the risks they're taking. Beyond that, we discussed the role of the insurance industry in making this work, what other policies would complement this evolution of liability law, and even touch on Professor Weil's hands-on work crafting state-level legislation in Rhode Island and New York, which would make clear that if an AI system does something that would be a tort if a human did it, and neither the end user nor any other intermediary intended or could have reasonably anticipated that outcome, then the developer, the model developer should be strictly liable. It's a simple and I think relatively unobjectionable idea to address model-level misalignment that at least some governments might find a natural first step toward accountability for frontier AI companies. As I said last time, all governance proposals require people to do a good job, and no governance structure can guarantee success. Whereas the private regulatory market proposal trusts governments to articulate worthy goals and private regulatory bodies to effectively implement them, this liability-based approach would rely on judges and juries to make good decisions and on companies to adjust their decision-making based on that expectation. Honestly, both of these proposals seem like major improvements, relative to traditional top-down rulemaking or to doing nothing, but I honestly can't say that I have a favorite. Perhaps the best thing to do is for society to pursue both in parallel, in different jurisdictions, and see which ones seem to be working better when the time comes for implementation at a larger scale. If you have a strong opinion on this, or if there are other proposals you think would be better than either of these, please do reach out and let me know. For now, I hope you enjoy this exploration of how centuries-old legal principles might help us navigate the emerging risks of artificial intelligence with Professor Gabriel Weil.