Strategic steering
Open AI's backing of state-level safety legislation is likely an attempt to set the ceiling where the floor should be
What does AI regulation at the state level accomplish, how does it work, and why might AI companies support it?
A recent Politico article covers OpenAI’s backing of a Massachusetts safety bill that would require AI companies “to publish safety frameworks and catastrophic risk assessments.” OpenAI is actually attempting to strengthen this bill, encouraging the state to add a third-party audit requirement. But even with this addition, the bill would still be weaker than the one Anthropic is backing, which would “require top AI companies to submit to independent safety evaluations.”
The difference? A third-party audit basically asks: did the company do what it said it did? It doesn’t probe whether the company’s process was sufficient, just whether or not the process happened. Independent safety evaluations attempt instead to answer the question: is this model safe enough to release? (I’ve written previously about the unfortunate limits of such evaluations, though they’re certainly a step in the right direction.)
What does it mean when a state requires measures like this, but they aren’t mandated at the federal level? It means the measures apply to companies who have customers in that state. Since the top AI companies have customers nationwide, state-level restrictions often result in de facto nationwide compliance, and may be a way to get around the absence of federal legislation. While Congress fails to act, states can step in to help fill some gaps.
But importantly, the safety measures that AI companies are backing are relatively weak. This, in my view, may be the reason OpenAI is supporting the Massachusetts bill. Safety measures that have real teeth would go beyond audits, and even beyond independent safety evaluations. They might include an explicit cap on model capabilities, to prevent companies from training more and more powerful models that are more and more likely to escape containment. They might limit the amount of computing power companies can use to train a model, in order to prevent them from creating something smarter than humans. And they might make companies legally liable when bad actors misuse their models, causing widespread harm.
So we can think of industry support for state-level safety bills as an attempt to steer legislation towards a precedent that doesn’t get in the way of business as usual. (This is my take, not Politico’s, and it’s not the only plausible reason for AI companies supporting state laws.) But I do think my colleague Joe was onto something when he wrote in May:
The industry failed to lock in favorable rules at the federal level, so now they’re trying the same thing in the states. If they can get some nice-sounding but ultimately toothless policies in place and then cement them as the standard to beat, perhaps they can forestall further unwanted interference. It’s a transparent attempt by industry to set the ceiling where the floor should be.
The analyses and opinions expressed on AI StopWatch reflect the views of the individual contributors and the sources they cover, and should not be taken as official positions of the Machine Intelligence Research Institute.