Originally published in Yahoo Finance. Watch the full video here.
Former FTC Chief Technologist and Abundance Institute Head of AI Policy, Neil Chilson, joined Asking for a Trend to break down the future of AI regulation as concerns over the pace of AI development intensify.
So, uh it’s a complicated question. You know, the the discussion over the weekend talked a lot about the need to pace the frontier. And uh you know, these these companies uh who are running at the frontier, they have every right to make business decisions to slow down or speed up. Where I get worried is when they start asking the government to enforce that uh that slowdown on their competitors. That looks to me like something that harms competition, it harms innovation, and ultimately it harms our ability to stay at the front of this really important area vis-a-vis China.
Now, how difficult would a government mandated slowdown be? I mean, what’s the likelihood that it actually could happen?
So there’s lots of different ways that the government might pursue this, but all of them to be effective in the ability to, you know, make sure that everybody’s running at the same speed would essentially involve a government regulator looking over the shoulder of every innovator. And I don’t just mean the big labs, but anybody who might challenge, you know, the the labs, uh new technologies. And so, to me, I think for it to be effective in its goal, I think it would have to be quite invasive in its mechanics. And there I don’t think there’s a strong appetite for that on the hill. Um and I don’t think practically speaking that it would be good for uh the labs or their customers.
At the same time, we’re hearing about this increasing fear of Chinese AI models getting ahead. and President Trump even mentioning that within that post on Truth Social. Where are we at now? And and could that slowdown that these AI leaders are calling out for impact that competitive edge that the US wants to have against China?
So absolutely. Uh there are two different races that are being run here and the US and the and China have been emphasizing slightly different ones. So the US has been pushing the frontier models, make the the next model bigger, better, faster, more capable. China has been pushing applying the models broadly across the ecosystem in robotics and other spaces, you know, delivering products and services to customers. I think China is uh, you know, is is close to matching us on that second one. Um we are ahead on the frontier race, but we really also need to compete on delivering products and services that benefit customers and to and consumers and less focus on, you know, trying to build these big uh all- inclusive models that can do everything. I I think the calibration that’s happening in the US industry might be a good idea. Maybe we need to focus more on showing people how this is improving their lives. Let’s start solving cancer instead of, you know, spending all our time trying to build the next big model um in the promise that it might solve cancer.