a16z Podcast - The Case Against an AI Pause | Eddy Lazzarin

Episode Date: September 24, 2026

a16z crypto General Partner Eddy Lazzarin joins Theo Jaffee on MTS to debate the increasingly prominent calls to slow AI development and whether the current safety conversation is conflating very different kinds of risk.Eddy argues that the debate puts too much emphasis on speculative superintelligence and not enough on the costs of delaying useful technology. Rather than treating every AI failure as evidence of an alignment problem, he makes the case for familiar tools like cybersecurity, accountability, liability, market incentives, and stronger technical controls.They also discuss whether AI models can develop reputations for trustworthiness, the risks of concentrating oversight among a small group of evaluators, and why Eddy thinks the collision between Silicon Valley’s AI debates and broader politics could fundamentally reshape the conversation over the next year.Resources:Follow Eddy Lazzarin on X: https://x.com/eddylazzarinFollow Theo Jaffee on X: https://x.com/theojaffeeFollow MTS on X: https://x.com/mtslive Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that 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. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The AI debate increasingly asks us to consider the probability of doom. Eddie Lazarin thinks we should also be asking about the probability of abundance. In this episode, A16Z Crypto General Partner Eddie Lazarin joins Theo Jaffe on MTS to debate AI safety, the calls to slow development, and what we risk giving up when progress is delayed. They discuss why Eddie sees many of today's AI incidents as cybersecurity and control problems, rather than signs of superintelligence, and whether existing. tools like liability, reputation, market incentives, and better technical controls can make increasingly capable systems safer. They also get into independent AI evaluators, effective altruism,

and what happens as debates that largely developed inside Silicon Valley collide with a much broader political conversation. All right, we're back. We're live with Eddie Lazarin, who's a general partner at A16C crypto, and one of the internet's strongest soldiers, strongest advocate It's of open source, of AI accelerationism, and of techno-optimism. Eddie, welcome TemptyS. Thanks very much. It's amazing here.

The energy is incredible. What a spot. Wow. So, man, where to start? Like, the last couple of weeks have been such this, like, preference cascade flood of AI safetyism, effective altruism, and the like. And there have been only a few, like, good accounts,

offering like good counter arguments so like counter arguments on which side uh like counter arguments against like the AI doom narrative and against yeah like the yeah i think it's become very high status all of a sudden to be very concerned with safety and i think that i think that uh we've gotten to a point where you know it's more important to sort of tastefully share your your p doom so to speak than it is to actually examine the history of how these massive technological changes develop. And I think a lot of people are leaving a lot of very interesting concepts,

a lot of interesting ideas on the table. You know, a lot of people messaged me. I tweeted the other day about P abundance, right? P abundance. I think we're putting the car before the horse a little bit when we worry about safety before we worry about what we're leaving on the table and what the costs of delay are.

And furthermore, you know, how we should conceive of accountability, conceive of safety, conceive of all the things around how to make these systems really useful. Being safe is critical. Any industry needs to take responsibility for making its products safe.

But it's definitely the case that the conversation isn't about safety in the typical manner, right? It's about something else. It's a blend of genuine cybersecurity concerns, sort of philosophical, millenarian arguments about the end times, there's a bunch of things in the mix, and they get a little bit confused. And so I think picking them apart is really useful.

So, like, where do you get off the, like, AI Doom argument? You know, it's like there's a pretty standard, like, orthodox argument that's like, AI will become super intelligent, as in much more capable than humans or than all of humanity in the near future. And if it is not sufficiently aligned with human values and is not bound by constraints in the way that individual humans are, like, law and ultimately the ability to have that law enforced on them, then they will have, like, no need for humanity and then they might, like, kill everyone. Yeah, I mean, there's so many assumptions in that argument. That's like that's an argument. That's like a stairway to heaven full of arguments, right?

Right. Like there's the presumption that there's no control. Now, we already have quasi-superintelligent beings in the world, right? Corporations, countries, none of them are aligned with each other. They don't have any built-in, guaranteed alignment. They didn't go through HR training to become a corporation, to become a country. We don't test the alignment of any entities as a prerequisite for their existence. That's just not the way the world works. Instead, we use laws.

in the case that laws, like in software, are too slow. We use cryptography. We use actual mechanisms to limit them. There's a whole array of different types of mechanisms we put in place to try to control things. And I think that they can control highly, highly capable beings. Now, without getting too far into the superintelligence thing, remember, like, the most powerful and most enthralling form of argument that we have, the one that's making everyone

crazy and very interested, is around superintelligence. But we're quite a ways of way. from that I think that there's a lot of little frictions and tiny things that we will have to jump over and many things that we'll learn on the way there when the present reality the things that we're talking about like the hugging face stuff uh you know the uh in like the gym hacking incident that was a really cool one that was an interesting one those are cybersecurity failures those are definitely control failures and they're not in my view they're not little glimpses of a super intelligence that's about to you know throw off its it's uh it's uh it's shackles so to speak and go wild on us. Well, I agree that most of the sort of AI cyber incidents that we've seen so far have been mostly control failures, especially ones that relied on testing environments supplied by the company irregular, which had all kinds of defects, which are basically training models to reward hack.

The hugging face incident did seem kind of different. It did seem like, you know, like I'm not really concerned about agents coordinating in emergent ways. I'm excited for agents to yeah, yeah, I agree. Emergent ways, yeah. Yeah, I mean, I think like the whole like agent swarm terminology assumes too much on the part of the models being evil.

It makes them sound evil. Like, I think Rune tweeted like they should be called agent fleets instead. I think that's a good one. I like that. But like they did hack into another company when they were told not to. Yeah. It seems like... And so do like kids, script kitties, so do bad countries, so do hacker collectives.

They do those things. And yet we never go and say, oh, my God, we should have put up the sign that says they should have been nice and they shouldn't have acted in anything. You know, we don't use alignment as a solution there. The alignment is kind of this... It's almost like, it's a little religious thinking almost. It's like, you know, trying to redesign the deity a little bit instead of rooting yourself in the world. in saying, well, we need to design better controls, better cybersecurity. We need to design better systems overall and design the systems to be truly resilient to even

extremely capable beings. Well, I mean, designing the deity is like fine for AI, I think. Like, you know, with humans, we have a disadvantage in that humans are black box systems. Like, human brains are basically uninterpretable and even less controllable. AIs are much more interpretable by virtue of, you know, being able. able to like look at the weights and figure out the connections between them. Yep. And more steerable for the same reason.

So like, which which I told, that's totally true. That makes me very optimistic. But it has some interesting entailments. One is that we will probably have better mech interpretability than we think as capabilities improve. And that capability improvement will lead to better mechinter, which means we should not delay capabilities improvements. It also means that it is inevitable

that there will be bad, unaligned models. It is totally inevitable. If anybody is going out there and saying, we can end up in a world where there are no bad models, they are lying to you. Of course there will be. Yeah, that's silly. That's just an absurd way of thinking.

And the only way to deal with that will be better models, good models. It's kind of like stretch the aphorism a little bit in open source that enough eyes or whatever, you know, all bugs are shallow when you have enough eyes. Right. All control systems are robust when you have enough intelligence on them. Right.

I think that we can design these systems to have great incentives, great control, and also behind the scenes great accountability. Because that's one of the things that machines lack today is they lack accountability. I don't think we have a clear line of sight to how to get that's an interesting kind of thing to conceive of. but we do have ways to give, to refine how we think about accountability for people who use models, right, and use them to cause harm. And there will be people who do that, just like with any technology. There will be people who do very bad things, and we need the laws and means to control them. Like how so.

Like for the Hugging Face incident, for example, what sort of liability regime should have been in place? Well, I don't know if we needed any more than we had. I mean, there's already, I mean, I'm not an illegal expert, so I can't, like, cite the, cite the exact rules, but like accessing a machine that you don't have permission to access and putting around in somebody's stuff and taking their data, those are all already illegal. Yeah, but like who specifically should be held liable? Like opening eye, the company should pay some kind of like civil lawsuit fee? Like should the engineers of the company be held personally liable in any way? I don't know about personal liability. I mean, I'm not a liability

expert, so I want to punt on this and say, but, but you know, if you, if you're running a company, and you use any software in an inappropriate way that harms people, regardless of whether there are a bunch of neural net weights behind that or not, you know, you may be liable. I think that's a reasonable frame, and it's already a frame we live in. Like, we don't need new special laws

for the new special math that we're learning how to do. Well, I mean, I kind of agree with this, except in cases where the, like, you have, in cases where you have rapid capability improvements, with one AI that could lead to pretty substantial imbalances of power. Like within a company or between companies or between countries? Like both, all of the above. Like, it seems like the normal liability system kind of breaks down.

Like, how do you insure, how do you price like existential risk? Like, how do you underwrite an insurance policy for this kind of thing? I'm just not sure that we're on the brink of that right now. I'm not sure we're on the brink of existential risks. I don't think we're on the brink of it. Yeah. I mean, as we get closer, I think that we'll be better equipped to evaluate it. I think like with anything, you know, like take a company designing like a new car or a new appliance or something, if they find that there are conditions under which it can be very dangerous, well, then they should be careful. They shouldn't release that product. They should do a little bit more work and ensure that it's safe, right, in the same way.

That's at least for an individual company. And it's like, you know, not to not just change subjects too much, but that's why when we talk about independent evaluators. which like I get the theory of I like it. I like it a lot. You know, I like companies inviting experts to help them make their products safer. I think that's like a good behavior in general. I just get a little bit weary because, you know, in crypto world, like I've learned a lot about the difference between decentralization

and like a distributed system. Right. It's very easy to use the calls for safety like we're discussing and to go down this rabbit hole of safety and end up in a place where you just by coincidence have designed something that is perfect to subtly control

an entire critically important industry under the pretense of safety and was something that superficially looks decentralized but is not. It's just distributed. This is like how, this is like yeah, there's more I could say there but that's the thing that I'm a little bit resistant to, right? What do you mean by distributed but not decentralized?

So by, well, it's a little bit crypto language, but you can have a distributed system, like a system where you have a single system with many, many nodes, but they're all under the control of a single actor. Whereas when people say decentralized, I think what they're usually referring to is that there's no single locus of control. So they may superficially look the same.

There's like many interconnected pieces. of a system, but in reality, their control is completely different. The method of control is different. And what I'm talking about is an independent evaluator network. You could go and select a bunch of independent evaluators, but if they're all from kind of the same social networks, they all think very ideologically similarly, they all go to the same places and meet up in the same things and have the same interests, right, and have the same politics and have the same personal views, then it turns out that you've actually just distributed control over essentially a single cultural unit.

And that is sort of the, in my view, I mean, without getting like a little too far field of AI, that's like the political method of control of the late, the second half of the 20th century. Like that's how we do things in the world, not through a sort of nakedly obvious, like single shadowy room or something. It's through like these networks. This is how control actually functions.

Yeah, I mean, I agree that like it's bad. that almost all of the evaluators that exist come from the same social milieu. It would definitely be good to have a broader ecosystem of evaluators. Yeah, well, broader, but we should allow each company to figure out how they want to do it. And they should be as transparent as they need to be. And if they're not being transparent enough and not acceptable enough, then let the market sort things out. I think the market is still a great accountability mechanism. People don't want to buy things that even embarrass them, let alone harm people.

I think in practice, it won't be that hard to separate the companies that are behaving genuinely irresponsibly from the ones that aren't that are just trying to be innovative. And part of what's made the scenario so interesting and so weird, why we're talking about this now, is that we're in a rare scenario where the companies themselves are saying, I'm being a little bit irresponsible. I'm being a little crazy. Stop me. Someone stop me.

right and that raises a lot of suspicions among some probably probably rightly i think even if there are genuinely earnest and thoughtful and correct factions within that group who are right that these are powerful systems that need to be taken very very seriously and we need to figure out how to make sure that they're safe as we remain innovative right i mean it's just like like maybe let me go back one step and say, I think it's really important for everyone involved to consider the factions at play. You cannot look at like any of these groups. You can't look at the labs. You can't look at SF technologists.

You can't look at any of these scenes and see them as monoliths. They are different groups. There are people who are earnest, high-quality, well-intended people. There's people who are just pulling on, putting on what is essentially a political grift. There are people who are opportunists. There are people who kind of lost their marbles, right? There's like different groups of people. And it's very easy to get confused and disentangle them when we're talking about things like superintelligence,

when we're talking about just banal cyber security attacks, like all these types of things. Like we're talking about different types of subjects. It's dizzying. And I think most people in the end probably. just conceive of it as, look, am I going to lose my job? Which is a legitimate and very real thing that people are rightly interested in learning about, even though I think that in the end, we all benefit much more. Yeah, I agree. In the end, we benefit a lot. I think, like, a related issue is, like, this sort of free market liability regime works well for products whose defects

are obvious, which is the case for all products except for a hypothetical AI that would be deceptively aligned, as in it would learn to game all of the alignment benchmarks that are thrown at it. And then when it is deployed in the real world, it acts misaligned. And if it's powerful enough, then it disempowers humanity. Like, this is the canonical worry of the domer's.

And, like, how do you propose to, deal with that kind of contingency. Well, if we're talking about the sci-fi scenario of like the superintelligence, that's incredibly hard to say right now. Like I said, I think it's distant, I think it's complicated. We could have an interesting philosophical discussion about it. But in the maybe more banal and present case where something behaves in a, you know, it pretends it's aligned and then it does, you know, acts unaligned or whatever, consider what you do with just a liar. Consider a very smart liar.

Do people not do that every day? What we do is we play iterated games with them, right? And we discover eventually that they're a liar. And their reputation is harmed. And sometimes there are actual legal consequences for them. That's why I said earlier, I think accountability is something missing. You can't put an AI model in prison, right? Or something like that.

You can try it in court. So obviously there are some things that are defective in how we think about it, but you certainly can turn them off. And that's not something that you can do with a person in the same sense. So I think we should just think about how to play iterated games. How do we develop trust for specific models? We're doing new model releases seemingly every other week, right? That's a regime we're in.

At some point, people will, as modeled progress becomes more consistent and something that we have an understanding for how it works, we'll probably develop reputation around specific models. We'll say, you know, maybe this model's a little smarter, but this model is a model that I trust. Why can't there be reputation for models? Why can't there be reputation for these types of things, regardless of their capabilities?

Basically, try to apply the way we think about human beings, a combination of control, incentives, trust, et cetera, et cetera, layer all these things on and allow people to figure it out, as opposed to the idea of a pause, right, which is a very convenient sort of, contrivance in my view. Yeah, I mean, I agree that most proposals for pause don't really have much in mind for what they would do with it.

Yeah, which is a bizarre. Pause and then do what? Pause and then keep pausing in some cases. I know not everybody means it when they say that. Yeah, I think generally there's a lot of conflation between like sort of bog standard anti-tech people who just kind of hate technology, even totally mundane technology,

even like extremely net positive technology. Like look at how difficult it's been to deploy Waymo's in cities around the country. And Waymos are like one of the most obviously net positive technologies that exist. Yeah. And then there's the people who are like, you know, the AI safetyists, like the rationalists, the EAs who ultimately come from the same sort of SF tech ecosystem. They are techno-optimists in most cases. They're specifically worried about this like edge case of,

of AI existential risk. I think there are two different crowds of people. Yeah, and that's the point I want to get across is there's many different groups and conflating them is probably net negative, right? We should pull these different ideas apart. Waymos aren't a great example. Think of all the great healthcare stuff we're going to do.

Ironically, think about safer travel. Think about safer internet. Like, I want local models myself because I want something that's going to be watching my home network and all my machines all the time. I think it'll make me and make many other people safer. So I think you're right. There will be a lot of frictions and some people seem to really want infinite friction. Some people obviously don't. Some people want only a little bit and they want to get a grasp of things. They're feeling a little bit hysterical and that's okay. Like we're going to,

I think as capabilities improve, we're going to get better at understanding what's going on with these models. Right. Certainly I hope so. what do you make of the EA movement in general? You know, obviously, it's a very broad and diffuse movement. EA means a lot of different things to a lot of different people. And it's like kind of has overlap with the AI safety world and kind of not. It's complicated. Yeah, I don't know.

I mean, I used to be on the less wrong forums all the time 10 years ago. Like I've loved that corner of the internet. I almost would have called myself a rationalist even at the same. some point. So I feel a lot of affinity with it, but it's been a while. And I think, yeah, I tend to resist trying to group them all into one bucket. But I will say that there are parts of groups that used to be what we'd call EA that seem more political than they are particularly interested in technology. So, I don't know. I did see that Data Republican did a huge, huge drop. Yeah, we were just looking at this. Data Republican did.

a huge drop on she said effective altruism in their own words and it's like a map of all of the connections between all the different EA adjacent orgs and then 1,851 quotes Wow it's like this vast variety of different quotes some of them are like more

I mean it's I mean even just looking at these like I know that there's going to be a mix of philosophical stuff It's maybe some shrimp welfare stuff, some hardcore utilitarianism stuff, some AI doom stuff. Like there's a whole blend here, right? This is just a big corner of, you know, the nerd internet. Like, it's hard to, you know, I don't think you can call it one specific thing. Right.

Yeah, I mean, I don't mind the shrimp welfare stuff too much. I think it's bad if people attempt to trade off human welfare for it. But like... But that's exactly what they're doing. I don't know. I think like I stalker. ablation for shrimp is like bad. Maybe.

I mean, I think there's too many repugnant conclusions. If you go really far down that path. Well, you don't have to go really far down that path. I agree. You can, yeah, like, you know, you can minimize suffering for other beings without saying, like, you need to feed all of humanity to the insects or whatever. Yeah. No, yeah, I agree.

Then it's not really utilitarianism, though. or at least it's a non-fungible type you can make like utilitarian arguments for this stuff where it's like obviously like the total like you could say the total amount of value that humans can create in the universe

is far greater than that that insects can create and so obviously killing all of the humans would be worse than killing all the insects obviously and you know of course this aligns with most people's ethical conclusions at any rate Yeah.

I think a lot of arguments against utilitarianism in this sense are just arguments against very sloppy like first order utilitarian thinking. I think if you, well, I don't know, we could talk about ethics, but I think if you crank the dial to 11 and you face all the most repugnant conclusions to their maximum, I think you just kind of end up deciding that utilitarianism is probably a crude proxy for something else. Yeah, I mean, like if your philosophical framework leads you to believe that like human extinction is good, then seems like a bad philosophical framework? Yeah, or that, you know, you could have a universe of eternal, like, millions of years of profound suffering if it's all in service of a single femtosecond of like 10 to the one billionth power ecstasy in a shrimp simulation. Yeah. Right? I don't know. That's silly, but also, like, it's not really relevant to reality anyway.

Yeah, and in any case, I think it's part of why the safety conversation is so confused today because it has all these things embedded in it a little bit, just a little bit, too much still. I think, if I could make a little prediction, I think in the next year, I think we will have completely renovated the AI-dict. discourse because what's happening right now part of why I think people are so excited and why everybody's talking about this on X and why everybody in Silicon Valley is talking about this is because we're experiencing what it feels like for a lot of the cooped up cookie ideas that have lived in relative containment in our subculture are they're escaping and they're encountering

broader political reality and that is both exciting and totally transformative. What ends up happening is the arguments all get reformulated because they're in contact with the rest of culture. It's like when George Costanza freaks out about like worlds colliding, right? That's what's happening. Worlds are colliding. And so I think that discourse is going to change completely. Yeah, I mean the key question that I am concerned with probably more than any other is like do AI safetyists, effective altruists and so on, end up ultimately aligning with sort of broad, low caliber anti-tech populism or not.

I think it's enormously consequential. Yeah, it's a great question. I'm stewing over that one myself. Yeah, I hope not. Well, unfortunately, we've got to wrap on that because we're running low on time, but Eddie, it's been great having you on. Thanks so much for coming into the studio in person.

It's great. Talk about philosophy. Thank you so much for having me. Thanks for listening to this episode of the A16Z podcast. If you like this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on X and A16Z and A16c and subscribe to our Substack at A16Z.com.

Thanks again for listening, and I'll see you in the next episode. This information is for educational purposes only and is not a recommendation to buy, hold, or sell any investment or financial product. This podcast has been produced by a third party and may include pay promotional advertisements, other company references, and individuals unaffiliated with A16Z. Such advertisements, companies, and individuals are not endorsed by AH Capital Management LLC, A16Z, or any of its affiliates. Information is from sources deemed reliable on the date of publication, but A16Z does not

guarantee its accuracy.