[0:00:01] So I would love if you could, you touched on this, but just describe in a little bit more detail how and why you felt like you had to move from a non-profit structure to a for-profit structure. Was that like a light bulb going off? The simple thing was we just needed vastly more capital than we thought we could attract, not that we thought, we tried that we were able to attract as a non-profit. We knew that scaling computers was going to be important, but we still really underestimated
[0:00:31] How much we need to scale them. Yeah. So does that suggest that nobody can do AI as a nonprofit in any kind of a meaningful way? No. There are other things that you can do for sure. But to be at the front of scaling research, I think you probably can't do that as a nonprofit. What about as government? Government could do anything they wanted, right? Right. Well, but yes and no. So again, one of the things we try and pick at is that there's some things that firms are much better at than government.
[0:00:57] I mean, do you think the Department of Energy or the Department of Defense could do OpenAI as well as you guys do? The Apollo program was pretty impressive. So do you think that could possibly be another route? I think, you know, in some sense, in a well-functioning society, I think this would be a government project. Yeah. But that seems to be a big if. But given that that's not happening, I think it's better that it happens this way and happens, you know, like as an American project. Okay.
[0:01:28] You also then said a couple of times that there's a role for the government, or I think you used the word society to play, in setting some of the guardrails or in directing things so that equity is built in. More than a role. Maybe that's like society should play the role there. But how does that happen? Like society is not like a thing. No, it's a complex negotiation of a lot of different stakeholders.
[0:01:58] But we kind of do, you know, we do this. We get this right over time. Give me an example. How do we get it right? Airplanes are really safe. Boeing, problems aside, in general, airplanes have been remarkably safe. That happened largely as a result of kind of old-fashioned regulation. I would say it happened because people want to get on an airplane and know that they're not going to die. And society responds to that.
[0:02:26] Well, specifically government response. Airplane manufacturers also, if they want to keep selling airplanes that people want to get on, definitely governments have a role. The scientists and engineers working on it feel a sense of obligation. I think it is a multi-party thing. But there's a huge role for regulation, for sure. And are you, how are you, you're clearly going to be a player in this game as it unfolds. I hope so. A big player. I'd put money on it.
[0:02:53] So how are you thinking about it? And I compare it a little bit having been at HBS when the internet happened. Sort of the folks who were you when social media and the internet were happening were saying no government, cyberspace wants to be free, keep the black helicopters out of our business. How are you thinking about sort of your position vis-a-vis the government? I mean, I hope it's like a real partnership. It's been fairly constructive so far. Too much...
[0:03:25] Regulation clearly slows innovation. Not enough clearly leads to a whole set of other problems. Everyone agrees, I think, on those two statements. And then there's just a question of where you should be on that spectrum. And do you think there's particular parts of the government that, I know you're working with DHS, but DOE, DOD, I mean, where would you most like to build bridges? I mean, I look at it easy to be too optimistic and drink the Kool-Aid too much in this, but I think this is going to touch like all parts of,
[0:03:56] Society and thus all parts of government. But those are hard things to build. For sure. But, you know, like the Internet touched all parts of society pretty much. Right. But arguably we got some parts of that really wrong. I was going to say we got a lot of that wrong. We got some parts right. And I don't think most people would say undo the Internet, even with all of the problems. Yeah. That is kind of interesting watching my students, a lot of them having grown up on social media.
[0:04:26] Would like that part of the internet to go away. For sure. And there will be parts of AI that you would like to go away. But how many of your students would push a button and destroy all computers and the entire internet? Oh, none. None. So there will be parts you don't like. There'll be parts your students 10 years from now don't like either. Yeah. But on the whole, I think it'll be a huge net win. And some of the students asked you this, but maybe I'll ask you to go a little deeper in it.
[0:04:54] If you think about from either the societal perspective or the commercial perspective, what are the pieces of AI that you're most excited about? Personally, I think greatly increasing the rate of scientific discovery is what I'm most excited about. I believe that that is, if you zoom all the way out, that is how the world gets sustainably better. And I think doing more of that is awesome. A lot of other areas too, I think there'll be incredible AI tutors.
[0:05:23] Incredible AI medical advisors. But personally speaking, I'm so excited for AI for science. Yeah. Any particular parts of science? I mean, I guess if I had one personal thing to pick, I would say like, you know, go solve all of physics. But no, I'm excited for it everywhere. So why all of physics? I have incredible personal curiosity. And I also believe that, you know, the more we can understand about physics, the more we can manipulate the universe.
[0:05:54] I don't know what will come of that, but it seems probably important to find out. So then the obvious question, what happens to the physicists? I was being a little facetious there. If there's truly no problems left in physics at all, then I don't know. What I suspect is that we answer the current questions and find more and harder and more interesting problems. So have you read this piece by John Maynard Keynes, Economic Prospects for Our Grandchildren? No.
[0:06:25] Okay, we have to, I have to send it to you. Okay. It's brilliant. So Keynes wrote it in 1930. And he's talking about what the world is going to look like 100 years ahead. Oh, I know about it. You must have known. Yeah, yeah. Because he, you know, it's a similar set of issues that once you solve all the problems. And he comes up with sort of a weird answer to it. That we're just going to make art.
[0:06:51] And not care about money. I mean, do you think about those kinds of existential questions? What happens to the physicists? What happens? You know, everybody has been debating this for a long time. And he was, I think, sort of right and sort of wrong. There is some sense in which you could go back to the 1930s and look at a lot of people today. You would say they are just making art and they don't care about money. They're all fine. But that's not.
[0:07:21] Their experience of it. If you could look at the people today and go forward another 100 years and ask them what they think about those people of the future's jobs, we'll say, you know, it's a weird definition of art, but okay, they're making art and none of them care about money. They have unbelievable material abundance. And you'd think a little bit harder and say, well, they seem busy and stressed and they seem to be getting a great deal of satisfaction out of the work they're doing and they don't quite call it art.
[0:07:47] You know, they still feel like they don't have enough and they want more and they're still finding new ways to compare each other, compare with each other. And, you know, maybe they're now, instead of like looking at whether their house is bigger or smaller than their neighbors, they're looking at whether they own a nicer galaxy or less of a nice one than their neighbors. But I think the human drives are just going to keep going. Human nature doesn't seem to change.
[0:08:12] So one of the things I write about in my weird books is the prediction that we're going to fall in love with robots, which is an exaggerated version of what I actually do think is true, that we are going to embrace AI entities as emotional companions. What's your sense? I mean, are you a fan of the kind of singularity type vision where there is this merging and we start to build emotional connections with?
[0:08:42] With things that are created rather than born. Yeah, I suspect that entertainment in the future will look quite different. And maybe it does. You know, maybe a lot of the time spent watching TV or playing video games today is replaced with an interactive experience with AIs. And we probably do derive some version of companionship from that. But for most of us, I think...
[0:09:13] The premium on the real human authentic version of it goes up not down in that kind of a world. So I'm sure we'll be talking to AIs a lot and I'm sure it'll be a fantastically entertaining world. But I would bet that there's something deep about human nature where just the knowledge that it's another real person or not really matters. Although sometimes.
[0:09:42] You know, I talk to some of the people I care about the most entirely through text because we're in the same city. So I might not know if they were being replaced. I might be fine with that if they were dead. Well, that's the question. If you knew it was not a real person behind it, would you feel any different? And I would posit that you would. Yeah. We're going to find out. Right. We're going to find out. But I think you will. Okay. All right. So we should make a bet on it and, you know. I would be happy to bet on it. See you 100 years from now. I'd give you nice odds. Okay. So.
[0:10:12] I want to go back to one other piece that you raised in your talk earlier. One of the kids asked the question about equity. And you had a very nice answer that, which I agree with, that the technology is probably going to drive to equity, but it's going to need some nudging. What kind of nudging do you have in mind? Well, first of all, I think it may not need any nudging at all. Sometimes technology doesn't.
[0:10:42] And I also think that knowing the right kind of nudging academically is hard to do. You kind of have to do it experientially. Like I'm sure all of my ideas right now are totally wrong. I think a tight feedback loop and watching where the problems are being created, fixing those, finding new problems, that's kind of how I believe we'll have to do the nudging.
[0:11:06] Although it's hard, right? I mean, I just came back from Denmark. You can see doing that in a country like Denmark, small, they have really good data. Like the US, wait, you know, the US takes 30 years to pass any kind of regulation. So how do you think about that nudging? I mean, I hope the companies will do it. Okay, okay. I think, yeah, if you're relying on US regulation, that would be. But you have, I actually taught your piece last night, two nights ago, the Moore's Law for Everything. I haven't read that in a while.
[0:11:36] How did it hold up? I think it's very interesting, because you're talking about changes in the taxation system, which are not particularly far-fetched. I mean, they're doable. Whether or not they're doable in the current political situation is a different question. But basically talking about a tax on land and market cap. And technology, basically. Yeah, companies. I mean, I like it. Would you still stick with that? Oh, I still think that's right, for sure.
[0:12:06] Of AI, taxing income and corporate profits primarily is not quite right. We do need to switch to a tax on capital somehow, it seems to me. I think that's a really interesting idea that hasn't gotten sufficient track, because it's different than a UBI. I mean, it's connected in some ways, but it's different. If you had one wish for AI, what would it be?
[0:12:38] Love humanity. Can you build that in? I think so. Like, how do you try? One of the things that has worked surprisingly well is the ability to align an AI system to behave in a particular way. And so if we can articulate what that means in a bunch of different cases, then yeah, I think we can get the system to act that way. Do you think OpenAI can and should
[0:13:09] Have the power to make its own rules. Why should we trust you? I don't think you should. I don't think we do. I don't think we will. I don't think we should. By the way, that does not necessarily mean that the right thing to do is to hand it over to a government bureaucrat either. The directional kind of thing that I think is interesting is you could imagine one of these systems chatting with all of its users.
[0:13:38] Saying, explain to me your value system. And then I'm going to collectively align across that. I am a believer that the users of technology, the people impacted by it the most, deserve a lot of say in its governance. So you could do something like that. I mean, is that feasible? Especially, again, given the vast sums of money. Totally feasible. Again, I think that's really a new thing that is enabled by this technology that just wasn't possible before. Okay. So is that something like what Anthropic is?
[0:14:08] What are they pushing towards? I don't know what they're doing. I'm not sure. No, because, I mean, they had this sort of, it seemed a little naive, the idea of, you know, we're going to put our design principles out there for kind of crowdsourcing. What I was thinking, I mean, I think it's very good to say here's how we're making these trade-offs of what a system will do and not do. But what I was saying, what I meant more is...
[0:14:35] I'm interested in the thought experiment of an AI chats with you for a couple of hours about your value system and does that with me and with everybody else and then says, okay, I can't make everybody happy all the time. So it's essentially sort of using AI to come up with a consensus. Well, using AI to talk to everybody to understand the consensus at a deep level of billions of people, which we can't do without AI probably. Okay.
[0:15:05] But it would just be interesting to line up something like that against kind of the founding documents of this country, which are explicitly, for better or worse, against majority rule. Now, what you're describing is different, but it gets foundational pretty quickly. Well, but it is fundamentally about democracy with some power checks on it. Yeah. Yeah, you'd have to think about what those look like. For sure. Yeah, so if the consensus is that it's bad AI, you know, that it's evil.
[0:15:36] How do you come up with the checks? Well, I think that should be part of what people should vote on for the governance structure. Yeah. Awesome. Thank you. Thank you. You've got to go be pitched. All right. Thank you so much.