Steven Sinofsky: AI Doesn't Need New Rules Yet

**Steven Sinofsky** (0:00)
The whole topic of regulation for me just seems completely backwards, because it's starting before we even know what we're regulating. There's no reason why the AI company should be against open source, other than we just don't want our competition to exist, and we don't want to bother to compete. We'd rather just compete with each other and not worry about that crazy open source competitor. Truth is, no one knows the future. What those assumptions mean are, we should regulate this based on our own personal predictions of the future.
But the history of being right about those predictions is pretty limited. And so we should be really careful about that because those are all self-serving.

**SPEAKER_2** (0:44)
How should governments regulate AI when the technology is still evolving?
Theo Jaffee and Sofia Puccini are joined by Steven Sinofsky to discuss why he believes AI regulation is moving too fast. The case for open-source models and what previous waves of technological innovation can teach us about building policy without stifling progress.

**Theo Jaffee** (1:09)
We are live with Steven Sinofsky, amazing tech analyst, author of hardcore software, longtime Microsoft leader. And we're so glad to have you back on, Steven. Welcome back.

**Sofia Puccini** (1:20)
Hey there.

**Steven Sinofsky** (1:21)
Super fun to be here.

**Theo Jaffee** (1:22)
Yeah, so much in AI, like where do we even start?

**Steven Sinofsky** (1:27)
Well, our goal is to say stuff that we haven't said yet, so let's see if we can do that.

**Theo Jaffee** (1:32)
We will try.

**Sofia Puccini** (1:32)
Novel insights time, yeah.

**Theo Jaffee** (1:34)
Novel insights. So open-source, there's been much discussion of regulation of open-source, Chinese open-source models in particular on both sides of the pond.
China has considered export controls, but also Xi Jinping has said we're encouraging open-source, and then in America we've had Scott Besson says we're going to be looking into IP theft, and some people have considered import controls or requiring a license. So there's a lot going on right now. It's very fluid. What are your takes on regulation of open-source models?

**Steven Sinofsky** (2:07)
Well, the whole topic of regulation for me just seems completely backwards, because it's starting before we even know what we're regulating, and if you go back in history, one of the best things about the 20th century in America was that so much experimentation was happening, so much innovation. And that does have this potential downstream of like, oh gosh, this thing happened that we have to roll back. Like a super famous example was safety in cars, and that car companies spent the first 50 years making cars, making cars. And then in the 1960s, it sort of became clear that, wow, we could actually make cars much, much safer. Now, it took 60 years to understand that cars were super dangerous, and it was all that evolution, and in all fairness, like it wasn't a design criteria. You know, seat belts and airbags and these things became a very long process to get them put into the upstream of making cars. And you could go through every sort of dimension. There's the antitrust law and the whole reason why, you know, oh my God, you can't be an oil company where you sell gasoline, produce gasoline, and also pull it out of the ground, or you can't make movies, have actors and actresses under contract, and own the movie theaters and distribution. And maybe that shouldn't be right. And there are millions of examples. The challenge is the story of regulation is always told as though if they would have got in early, they would have prevented this stuff from happening. And you look back and you're like, what if they would have shown up at Henry Ford and said, we need airbags? And Henry Ford is like, okay, we can't figure out how to make engines work.
Like, let's get that done. And also these cars go 15 miles an hour, and we're just trying to make them go. And of course, air travel is like that. Every technology innovation, it took a long time for two things to happen. One, for it to just work at all. And today we're talking about AI, and it can't be that AI is both the most intelligent thing in the world, and it generates gibberish, hallucinations, and the answers are wrong, and you can't rely on it. Like those both can't be true at the same time. You can look at social networking had the same effect, where like, oh, it's a toy, it's a giant waste of time. You know, it's either that or it can topple governments. You know, it couldn't be, and they were at the same time, people were saying both of those things about social networks.