The State of American AI Policy: From ‘Pause AI’ to ‘Build’

0:00So we've been through all of these tech waves and we've learned how to have this discussion in a way that for the United States interests bounces these two things and if we're going to make a departure from a posture that was developed from 40 years, better have a pretty damn good reason. Today a new frontier of scientific discovery lies before us. You can sometimes judge a book by its cover and I think this is a strong start. The conversation around AI regulation in the U .S. has changed dramatically. Just a year ago, the loudest voices were calling to pause or shut down open source AI. Today, the US is pushing to lead the global race.

0:33So what changed? And what does it mean for innovation, competition, and the future of open source? I'm joined by A16Z Journal Partners, Martin Casado, and Anjane Midha to unpack the new AI action plan, the politics behind it, and the implications for builders and policymakers alike. Let's get into it. As a reminder, the content here is for informational purposes only. Should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security and is not directed at any investors or potential investors in any A16z fund. Please note that A16z and its affiliates may also maintain investments in the company's discussed in this podcast.

1:12For more details, including a link to our investments, please see A16z .com forward slash Disclosures.

1:23Okay, so we're talking a week or two after the action plan has been announced. Looks like we've come a long way. Yeah. You guys have been on the front lines for years now in this discourse fighting to make this possible. Why don't we trace where we've been so that we could then understand how we got here and where we're going? I mean, under the Biden administration, we had the executive order, which was basically the opposite of what we're seeing today. It was trying to limit innovation. It was doing a bunch of fear mongering. But to me, what was even more striking was not regulators being regulators.

1:55You'd expect that. But if you remember, Orange, and this is why we got involved is you would have these politicians, you know, making recommendations, which is finding to expect that. But nobody was saying anything. You know, it was like academia was silent. Right. The startups were silent. And if anything like like the technologists were kind of supporting it. So we were in the super back where it's world, where it was like innovation is bad or dangerous, and we regulated, we should pause it. You know, there was this discourse and it was like somewhat fueled by tech as opposed, you know, and then nobody was going against it.

2:28And so I think today we should definitely talk about the act of planets great, but we should also talk about how the entire industry has kind of come around to say like this, and we need to keep these things in check. We need to be sensible to talk about it. Pause AI, that was two years ago. Remember that the big sort of, you know, all the CEOs signed this petition. Oh, yeah, I think that was the last AI action summit, right? The one before Paris. There's been so many of these. Yeah, that's right. I don't remember. Like, what was Dan Hendrix's CIS, what was California AI, the Center for AI Safety?

3:01Center for AI Safety, that's it. That's it. The nonprofit, yeah. Yeah, and then they got like all of these like people to sign this list, you know, like when you need to worry about the existential risk of AI and that was the mood. It was almost like, that can I just do something for a contrast, right? So I was, you know, there during kind of like the early days of the web and the internet. And at that time, you actually had examples of the stuff being dangerous, right? Like Robert Morris, like went out the Morris Worm, it took down critical infrastructure We had new types of attacks. We had viruses.

3:34We had worms. We had critical infrastructure. We actually had a different doctrine for the nation. We said, you know, the more we get on the internet, the more vulnerable we are. So instead of, like, mutually assured destruction, we have the notion of asymmetry. So there was all of these great examples of why should we be concerned? And what did everybody else do? Pedal to the metal. Invest more technology. This is great. And so, like, we were still at the time. Like, we wanted the internet. We wanted to be the best. We wanted to build it out. you know, the startups were all over it. And coming into this AI stuff two years ago, it was the opposite, which is like, there were the concerns with new technology which you always have, but like there are very few voices that were like, actually it's really important we invest in this stuff.

4:13And things so that's kind of, to me the bigger changes, this more cultural change. I think that's right. There was a moment in, I think it was last summer, where somebody sent you and me a link to the SB 1047 bill. And I remember, Martin, I was reacting like, there's no way there's gonna get any steam. What was absurd to us, I think, was that it made it through the House and the Senate. And it was on its way to a final vote and would have become law, one signature from the governor later. And I think there was this escalation where I realized, I think my views that technologists like to technology and politicians like to policy and pretend like these two things are in different worlds.

4:52And as long as these two worlds don't collide and the engineers get to build interesting tech And there's no sort of like self -own to early. We generally trust in our policymakers. And that changed completely, I think, last summer, which is really weird cultural shift, which is, no, no, a lot of the policymakers who actually, I think, were quite open about the fact that they didn't know much about the technology because it was moving so fast, still felt like something had to be done. Therefore, this is something, therefore, it must be good. And that this was this, I think the most egregious example of this being adversarial was SB 1047.

5:25But that culture shift was one from, let's let the tech mature and then decide how to regulate it later. To like, before, let's try to regulate it in its infancy was like a massive, I think, shift in my head. But let's just talk about how bad it was. You had VCs. Their entire job is investing in tech, talking against open source. You know, like, for no founders funder, like open source AI is dangerous. it gives China the advantage. Right. And there was this some sort of prognostication that if we didn't do open AI, I think the Chinese would somehow forget math and not be able to create models.

6:04And then you forward by a year and they've got the best models by far and we're way behind. So it was like the people that are supposed to be protecting the US innovation brain trust were somehow on the side of the let's slow it down. And I think that now there's this realization of, I should turn it really good at creating models and they've done a great job. We've kind of hamstringed ourselves from whatever discussion we were having. And I think you're right. I think we're just, like, it's good to be concerned about the dangers and job risks, but it has to be a fulsome discussion. You need both sides.

6:37And when you and I jumped in, it just didn't feel fulsome at all. It was like one side was dominant and there was almost no one on kind of the protect, pro -innovation, pro -innovation, pro -innovation source side. I just think it didn't feel grounded in Amperics. No, but certainly not that. It came from, you know, what is the steel man of the critique of open source that they were making a couple years ago? That you know, this is like a nuclear weapon. Would you open source your nuclear weapon plans? Would you open source your F -16 plan? So the idea was that somehow like this was like, you know, nuclear weapons are not dual use.

7:06Nuclear energy is dual use, right? And F -16 is not dual use like a jet engine is dual use, but a lot of the analogies that were used at the time were something that you know, if you squint one way parts of it are dual use. they could be used for good or for bad, but like the examples were clearly the weapons. And that's what they would say. They would say, listen, these things are incredibly dangerous, which you open source like whatever, the plan is for an F -16. And then, you know, the other side which slowly decided like this conversation is ridiculous, we gotta go ahead and set up. It says, you know, no, you would not do this for an F -16 because that is a fighter, you know, jet.

7:42However, like a lot of the technologies used to build it, Yes, this is fundamental. It's not like people aren't gonna figure out anyways, and we need to be the leader, just like we were the leader in nuclear. And we were, then by the way, in nuclear, like if you go historically, when that came out, we invested incredibly heavily in it. The things that we thought were proximal to weapons. Of course, we made sensitive. But this, all the universities were involved, like the entire country had the discourse, and that just wasn't what was happening. I think that's true. they were basically like there was a substantive argument against open source and there was an atmospheric one.

8:18And the substantive one was like the one Martin mentioned that the technology was being confused for the applications. And all the worst case outcomes of the applications are misuses, where then being confused. But they were also theoretical too. It's just seeming the worst of that. It was like you're right on what you're saying, but it was like this could potentially create bio -appans. It was funny. We got a bio -appan expert and he's like, I don't know really. I mean like the difference between like a model in Google is almost nothing. But you know, like that was used as this, you know, strawberry argument and then it could hack into a whole bunch of stuff like nobody had done it before, but it was theoretical.

8:50So it was like these theoretical arguments that were very specific right versus a broad tech. That was one. And then the Atmosphirics, where there was a famous former CEO who went up in front of Congress and literally in a testimony said, the US is yours ahead of China. And so since these are nuclear weapons and the misuses were being confused with the technology and we're so far ahead, let's lock it down so we can maintain that lead and therefore our adversaries will never get their hands on it. Which we're both just fundamentally wrong. For the reason Martin said like, substantively, he was not introducing new marginal risks.

9:21So if you did an e -vow on how much easier this... Well, he's not identified at the time. I mean, you would go to Don Song, who is like a safety researcher, McCarthy Genius fellow at Berkeley, and you'd say, what are the marchals of AI? She'd say, great question. We should research that stuff. That's a really good research fellow, yeah. The world expert on this question was like this is a very important, but it's an open research statement. Yeah, so no empirical evidence of the time that AI was creating net new marginal risks and just factual inaccuracies that we were ahead of China, because if you just paid attention, what was happening deep seek had already started to publish a fantastic set of papers, including deep seek maths, V2, which came out last summer.

10:00And you're like, okay, obviously these guys are clearly close to the frontier. They're not yours behind. And so in R1, and Deepseek R1 came out earlier this year. You know, a lot of Washington was like shocked. Oh my God, they're like, how did these folks catch or they must have stolen our weights? No, actually, it's not that hard to distill on the outputs of our labs. Have you actually looked at the author list of any paper in AI? Like, when you think these people come from? Right. So, so I think those two things were, it felt like we were being gaslit constantly because both the content and the atmosphere were just wrong.

10:29Yeah, yeah, yeah. Maybe one question for the smartest people or the most sober people who were against it is like, maybe they were asking, where should the burden of proof be? because it's hard to prove that there is risk, but it's also hard to prove that there isn't risk. And so this question of what's risky, is your risk year to just go full seam ahead, or is it risk year to kind of slow down until we better understand these models, you know, interpretability, et cetera? I mean, I think it's really important to ground these hypothetical discussions on what we've learned as an industry. I mean, the discourse around tech safety has been around for 40 years.

10:57We went through it with compute, like remember when we're like, okay, Saddam Hussein shouldn't have play stations because you can use GPUs to simulate naked weapons. That was actually a pretty robust and real discussion, but that did not stop, you know, us from having other people create chips or video games, right? I mean, we went through the internet, we went through the cloud, we went through mobile. And so we've been through all of these tech waves and we've learned how to have this discussion in a way that for the United States interests balances these two things. And, you know, listen, we've had kind of areas that were very sensitive to national governments.

11:26Think about like Huawei and Cisco, for example, and we as a nation did start to put in kind of important export restrictions as a result. And so I just feel these almost platonic, you know, polemic questions like the one that you just posed aren't rooted in 40 years of learning. So all I ask is if we're gonna make a departure from a posture that was developed from 40 years, we better have a pretty damn good reason. And if we don't have a good reason, then I think we should probably learn from that experience. Yeah, I think extraordinary claims. Require extraordinary evidence. And so the burden of proof should be on the party making the extraordinary claims.

12:05And if there's a party who's going to show up and say, you know, AI models are like nukes and California should start imposing downstream liability on open -source developers for open -sourcing the weights, that's a pretty high claim to make. And so you should have like exceptional proof if you want to change the status quo. And the status quo is you do not hold scientists liable for downstream uses of their technology. That's absurd. That's a great way to shut down the entire innovation ecosystem and start throwing literally like researchers in jail We don't want that we want them to be trying to push the frontier forward And I just don't think that the tall claims were not being right followed up by tall proof When we're talking about open source are we all talking about the same thing meaning are there degrees of open source Erzer kind of just like a binary open weights I think was the primary contention which is that if somebody put out and open the weights of a model and a bad guy Took those weights fine tuned it did something really terrible two years later or the SB 1047 regime proposed that the original developer of the weights and that they put out basically as free information should be held liable, which was absurd.

13:06Right, so I think, oh, wait a minute. I just wanna make sure we're very clear because people jump on top of these things. Right, what are you saying, Chris? So basically if the weights were over a certain size and there was a mass casualty event, I think. And catastrophic harm was the word used, but there were no real, no, mass casualty. There are so many versions that they don't know Of course, you don't like it. Yes, yes. But I remember we actually looked it up. The legal definition was three or more people were killed or the medical system was overwhelmed, which there was actually precedence of this, including like a car crash.

13:38Right. Right. And there was actually precedence of this happening in rural area, which basically doesn't have any sort of capacity. And so, you know, basically it would move the conversation to the courts and outside of policy, which is, again, historically, we've taken a policy position on these things, which follows precedence that we understand, you know, to make sure that we don't introduce externalities, like, for example, allowing, you know, China to race ahead with the resource, which is, you know, which has happened. And the key thing is by moving it to the court, even if you don't, you could, you could argue, oh, orange, but like, sure, it's moving to the course.

14:15That means it's open for debate. It's not clear that open weights are going to be regulated with liability, the point is that creates a chilling effect. The chilling effect is the idea that when our best talent is considered... I could be sued. I'm a random kid in Arkansas developing something. I don't want to be in a world where it can be resolved in the cars. I can't even afford whatever. And in a situation where you have an entire nation -state -backed entity, like China, actually doing the opposite of a chilling effect, encouraging a race to the frontier. why on earth would we want? You know that there's this meme of a guy on a bike and they pick up a stick and put an intern's front wheel and dobbles forward.

14:54That's the effect of a chill. That is what chilling effect is. Right. At a time when your primary adversary is racing. So let's trace how the conversation has changed because we don't see Vinod tweeting about open source anymore. Obviously open. It's a change of tune, especially right now. What is it really just deep seek? Is that or how do you trace kind of how how the sentiment shifted on open source. Let's go through a few theories. I'm not really sure what happened. I almost felt like it was almost culturally invoked to be a thought leader on the negative externalities of tech. And it kind of started with both Trump but it was picked up by Elon, it was picked up by

15:37muskowitz, I mean a bunch of like these intellectuals that we all respect and still do. I mean, they're just really the titans of our industry and our era. They were asking these very interesting intellectual questions around like, do we live in a simulation? What happens if AI can recursively self -improve? And then actually, they created whole kind of cultures and online social discourse around this stuff. And so I think to no small part, that became a bit of a runaway train. And it's just catnip to policymakers. makers. You know, and so I think part of it is like people didn't really realize that this becomes so real because of course, GPC 2 comes out and then 3 comes out and all the stuff is amazing and somehow it got completed.

16:18So I think part of it is just a path dependency on where we came from, which is kind of the legacy of both of them. I think that was part of it. I think the on -genres approach would be that there was a lot of discourses awesome, but a lot of the people pushing the discourse were first order thinkers. They weren't doing the math on, wait a minute, if policymakers who have no background in Frontieria, which by the way nobody does because this space is only three four years old, start to take discourse as canon, which is a big difference. Then what happens, what are the second and third order effects and the second and third order effects that are that you start making laws that are really hard to undo and start mistaking interesting thought experiments as the basis for policy.

17:03And once that happens, those of us who've, look, law is basically code. Code is hard to refactor. Law is like impossible to refactor. And so I think the second and third order effects were that were a lot of well -intentioned folks, for example, in the existential risk community saying, look, if you're intellectually honest about the rate of progress of AI, it's not crazy to say that there are some existential risks on the technology. It's non -zero. Sure. Yes, that is true. But then to then say that that threshold is high enough to start introducing Nash sweeping changes in regulation to the way we create technology.

17:33That leap, I don't think a lot of the early proponents of that technology realized they would do that. In fact, I think Jack Clark, who runs policy for Anthropic, literally tweeted towards the end of the SB 1047 saga, he was like, I guess we didn't realize the impact of how far this could have gone. And I think to those of us who had interacted with DC before and regulation before, like The second and third -order effects were much more discernible, illegible. And then I think what DeepSeek did was just made it super legible to everybody else. So I think they were already, like I think DeepSeek was the catalyst.

18:09But it wasn't like there was a step, it didn't change the reality that the second and third -order effects of policymakers confusing sort of like discourse for fact were always gonna be terrible. I just think it brought to light something a lot of us were already saying, which is we're in a race with adversaries. And that should be the calculus. we do Calcas, we should be working backwards from. Yeah, there was, there was also prevailing view, which is turned out to be so wrong, from really well -intentioned people, which was like, it's gonna be regulated anyways, if it looks like we're self -policing, we can dictate, you know, how it happens, right?

18:43And unfortunately, that just turned out not to be true, because you know, whatever self -policing we seem to be doing, scared the shit out of people. And I'm like, and then of course, I would say very opportunistic elements in tech, decided to use that for whatever agenda that they had. And so kind of it got away from us. Yeah. So Mark had this sort of the Baptist bootleg. Yes. I was just going to say exactly true believers and then sort of people who use the sort of that thinking for to support their own names. And it seems like that's changed even as on the company. But the reality is I think it was driven.

19:12I think the majority of people are neither. Yeah. The majority of people are pragmatists that are not trying to take advantage of the system that think, well, maybe if we have this discourse, it's an on -diss discourse, and then we'll self -police. And then I just feel like the silent majority was not part of the discussion. Maybe the biggest change now is like, those people are there. Like the founders are there. Academia is there. VCs are there. Now now the people that are not either Baptist or Bute -Leaders are driving the disguise. Which is independent of the action plan itself. I feel much into better position now.

19:45Like for example, there's still a bunch of stupid regulation that's popping up, but I'm not calling on at night and think we have to do something now because I feel like, okay, there's actually representation that's sensible. At the time, there was not. And I think to move to the action plan, I think this is a great, like, if you read the first page, what a marked shift, the fact that the co -authors include technologists, right? And I think that was the core problem, is DC is a system, like a self -contained system, and the values is self -contained system. And I think a lot of the people here were assuming best intentions over here in vice versa.

20:17And what happened is a few bad actors, essentially use that arbitrage opportunity to represent Silicon Valley's views incorrectly in DC. And when we saw some of the legislation, we had policymakers calling us up and saying, wait, you guys aren't happy with 1047, but the guys, the other tech people were calling us and saying you'd love more of this kind of regulation. We said, what other tech people? And it turns out we are not one homogenous group. Little tech is extraordinarily different from Big Tech, which is extraordinarily different from the academic communities. And I think one of the things we had to contend with was like, we used to be one shared culture.

20:52And then when tech grew, we actually, there are some major differences in the valley at least, between party, we're not one tech ecosystem anymore. We have different interests. And DC had an update at that. And I think what's amazing about the action plan is, it's written by people who've bridged both, with enough representation across the four or five different sub -cultures within tech who have different interests. I think that's new. Yeah, yeah. Going back to open source, why don't you talk a little bit about how different companies, how does it make sense of how different companies have thought about it or from a business strategy perspective?

21:26Maybe we saw Meadow, maybe the first big open source push, Open AI has evolved their tune. I've seen even, and the topic seems to be evolving their dialogue a little bit. How should we think about open source as a business strategy in terms of what's changed year and why? Oh, look, I don't think this is, this part is actually, is playing out beautifully along the same trend lines of all previous computing infrastructure, databases, analytics, operating systems, like Linux. The way it works is the closed source pioneers, the frontier of capabilities. It introduces new use cases. And then the enterprises never know how to consume that technology.

22:01And when they do figure out eventually that they want cheaper, faster, more control, they need somebody like a red hat to then introduce them and provide solutions and services and packaging and forward deployed engineering and all of that around it. And this is why the ARC generally in enterprise infrastructure has been close source wins applications. And open source tends to do really well in infrastructure, especially in large government customers, regulator industries where there's a bunch of security requirements, things need to run on -prem. The customer needs control over it. Broadly, you could call that the sovereignty I market right now.

22:31Lots of governments and lots of and legacy industries are going, wait, this open source thing is really critical to us. So I think whereas two, three years ago, it was open sources viewed as like this like largely philosophical endeavor, which it is. Open sources have always been political and philosophical by definition. But now there's an extraordinary business case for it, which is why I think you're seeing a lot of startups and companies also changing their posture because they're going, wait a minute, some of the largest customers in the world. Enterprise customers happen to be governments and happen to be legacy industries, and fortune 50 companies, and they want stuff on -prem.