AI, JD, and other letters of the law

Ryan Donovan (0:08)

Hello, and welcome to The Stack Overflow Podcast, a place to talk all things software and technology. I'm your host, Ryan Donovan. We're coming live from the floor of the Ai4 conference. And today we're talking about not the engineering side of AI, but the law.

My guest for that is Kevin Frazier, who is a professor at the University of Texas School of Law. So welcome to the show, Kevin.

Kevin Frazier (0:29)

Thanks for having me, Ryan. And to all those folks who thought that the engineering side of AI was the most fascinating part, I'm here to tell you that the legal and policy questions are pretty fascinating too.

Ryan Donovan (0:40)

Well, I mean, in a way it's social engineering, right?

Kevin Frazier (0:43)

Yes. Very much so.

Ryan Donovan (0:45)

So let's do a quick overview of what's the major issues with the AI and the law.

Kevin Frazier (0:52)

Yeah. So there are a couple of different buckets. The bucket that is most salient for most Americans is data centers.

So even when you say AI governance, the first thing that a state lawmaker will then say is, they won't talk to you about data, they won't talk to you about how a model is going to be released and tested, so on and so forth. For them, the most salient thing that they hear from their voters is just data centers. So even though you haven't said anything about it, they'll go straight that way.

Ryan Donovan (1:20)

Right.

Kevin Frazier (1:20)

And when we're talking about data centers, there's permitting concerns, there's zoning concerns, there's the regulation of utilities, and all of those are very weighty, very difficult legal questions that involve questions of federalism, the power allocated between the states and the federal government. Right. You get municipalities involved, you get counties involved, so that can all be gnarly. Then if you press them and say, okay, I'm not talking about data centers, I'm talking about AI specifically, they will then not go directly to the tech, they'll pivot to something like workforce and concerns around the loss of jobs. There are proposals far and wide now about how to address perceived and or real consequences of AI being more ubiquitous in the economy. Today, we're talking on August 7th, 2026

Gosh, time flies. Representative Kassar in Texas introduced the idea of a tax on AI companies. We know that Senator Warner, for example, has been studying how best to try to measure the number of jobs that are being cut, specifically because of AI at major corporations. So that's another bucket.

And then you start to get into concerns related to the tech. And that's where you'll see issues with respect to deepfake content provenance. And then you can get a little bit further into the weeds, and folks will have issues around child safety and cognitive de-skilling and related questions around how AI is being used.

Ryan Donovan (2:57)

Right. So for the data centers, that is a big one. That's getting a lot of protests. You talk about the sort of permitting land use. There's social effects too, right? There's effects on utility prices, consumer hardware prices. I think there's noise issues around it. I have this conversation with another podcaster friend of mine about whether the people who are protesting are crazy. And he says, well, a little no, a little yes, a little no.

And I tend to be a little more on the protester side just because there are social effects and not much is being done about them. What is the law doing to shift to protect and or enable data sectors?

Kevin Frazier (3:42)

Yeah. So, you know, I think that if you ask anyone, hey, do you want a little bit more congestion on your roads? Do you want perhaps your view to be obstructed? And do you want perhaps an annoying hum? Very few people are going to say, just based off of those facts alone, yes, sign me up. I would love that compared to the alternative. As with most public policy issues, the question or the difficulty arises from the fact that the benefits that result are diffused and are not immediately felt by the people who instead are saying, hey, well, it takes me 15 minutes to get to work now. It used to take me 10 I used to have this great view, now I don't, so on and so forth. So how to measure those and how to quantify those is something that's been really hard because it is really easy to see when your view has been obstructed. It's a lot harder to see, hey, my county now has more tax revenue than it's ever had in the past few decades. The library is open longer, that pool project is finally going to be completed, the museum hired more staff. You don't feel that immediately, but it's really important for a community. So I don't think anyone is necessarily crazy. I think they're responding to the information that's right in front of them.