It’s quite gratifying to see the argument I’ve been making for years gradually start seeping into common recognition. In this case it’s that LLM AI service providers (and their stockholders) should bear strict liability. Gabriel Rauterberg and Sarath Sanga remark in an op-ed at the Wall Street Journal:
The heads of frontier labs have said their companies could be responsible for such a mass tort, or worse. They’ve made the case against limited liability.
That case, as we argue in a recent paper, is strongest when a corporation’s profits and the risks it poses rise together, and when those risks are extreme and unbounded. That’s exactly the situation AI executives describe. Customers demand the capabilities that make the product so dangerous. The more successful the product, the more risk likely lands on the public.
Building more-capable models without these risks is the engineering problem that labs say they need more time to solve. Congress isn’t about to solve it. But Congress doesn’t have to. It can establish a liability rule and let incentives do the work.
In the 19th century, locomotives threw off hot embers that set nearby fields and barns ablaze. Lawmakers didn’t engineer a technical solution. They an
That should be easy for Congress to achieve even in a divided Congress.
Building better models is only one of the engineering problems AI service providers face. They must also find ways to deploy them safely. Strict liability for harms their services cause would give them a powerful incentive to do so. And if the potential harm exceeds what the company can pay, limiting the loss to the company’s assets leaves the public bearing the risk while shareholders retain the upside. That is the part of the authors’ argument Congress should take seriously and the sooner the better.
