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At a time when our nation is becoming increasingly polarized, media often ignore viewpoints and stories that are worthy of attention. American Thought Leaders, hosted by The Epoch Times Senior Editor Jan Jekielek and his reporting team, features in-depth discussions with important thought leaders on key issues facing America—and Canada, the world—today.

American Thought Leaders

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Jan Jekielek is a senior editor with The Epoch Times, host of the show “American Thought Leaders” and co-host of “FALLOUT” with Dr. Robert Malone and “Kash’s Corner” with Kash Patel. Jan’s career has spanned academia, international human rights work, and now for almost two decades, media. He has interviewed nearly a thousand thought leaders on camera, and specializes in long-form discussions challenging the grand narratives of our time. He’s also an award-winning documentary filmmaker, producing “The Unseen Crisis: Vaccine Stories You Were Never Told,” “DeSantis: Florida vs. Lockdowns,” and “Finding Manny.”

Jan Jekielek

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How Cartel Mega-Tunnels Move Hundreds of Millions in Narcotics Into America | Sara Carter

Why Women Can’t Find Good Husbands | Timothy Goeglein

The Machinery Behind Modern Mass Manipulation | Jacob Siegel

What the End of the Orban Era Means for Hungary and Its Constitution | Marton Sulyok

One Key Fact About America’s Founding That Isn’t Taught Anymore | Eric Metaxas

Is Canada Becoming the CCP’s Backdoor into America? | Former Canadian Intel Analyst Scott McGregor

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News you can trust from the U.S. and around the world. Critical information and insight. We cover the stories that others don’t. NTD News Today airs Monday–Friday at 11 a.m. ET.

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News with integrity, from the United States and around the world. Focused reports and analyses that shed light on major issues the world deserves to know. NTD Evening News airs daily at 6 p.m. ET.

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Andrew Thomas is a reporter for NTD News primarily covering business, the economy, and technology. 

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Daniel Monaghan is a reporter for NTD News covering culture, social issues, and education. He holds a BA in Political Science and Government.

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Why 28- and 29-Year-Olds Are Disappearing From China’s Uyghur Concentration Camps | Ethan Gutmann

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The Failures of Multiculturalism in the United Kingdom | Peter McIlvenna

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Robert Kiyosaki: Why America’s Middle Class Keeps Getting Poorer

The CCP’s Gloves Are Off in Trade War—What’s Next? | Lee Smith

How Tariffs Once Paid America’s Bills–And Why They Could Again | John Gardner

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[RUSH TRANSCRIPT BELOW] Few people understand artificial intelligence and machine learning as well as MIT physics professor Max Tegmark. Founder of the Future of Life Institute, he is the author of “Life 3.0: Being Human in the Age of Artificial Intelligence.”

“The painful truth that’s really beginning to sink in is that we’re much closer to figuring out how to build this stuff than we are figuring out how to control it,” he says.

Where is the U.S.–China AI race headed? How close are we to science fiction-type scenarios where an uncontrollable superintelligent AI can wreak major havoc on humanity? Are concerns overblown? How do we prevent such scenarios?

Views expressed in this video are opinions of the host and the guest, and do not necessarily reflect the views of NTD.

RUSH TRANSCRIPT
Jan Jekielek:

Max Tegmark, such a pleasure to have you on American Thought Leaders.

Thank you.

We’ve been seeing incredible growth in AI, especially through these chatbots. That’s what all the fuss is about. Maybe some also in robotics and some other areas, some very interesting applications. But I have this sense, I have this intuition that what’s really happening is much, much greater than that, at a level that perhaps I can’t even grasp at this point. So why don’t you tell me what’s really going on here?

It is indeed hard to see the forest for all the trees because there’s so much buzz in AI every day. There’s some new thing. So if we zoom out and actually look at the forest, you know, we humans have spent a lot of time over the millennia wondering about what we are, how our bodies work, etc. And hundreds of years ago, we figured out more about muscles and built machines that were stronger and faster.

More recently, there was a quest to try to understand how our brains process information and accomplish tasks. The name artificial intelligence was coined in the 50s. People started making some progress. Since then, it’s mostly been chronically overhyped. The people who started working on this said they were going to do a summer workshop at Dartmouth and kind of figure it out. It didn’t happen.

But for the last four years, it’s switched to being under-hyped, where progress has actually been much faster than people expected. So to give you an example, I’ve been doing AI research at MIT as a professor there for many years. And as recently as six years ago, almost all my colleagues thought that building a machine that could master language and knowledge, kind of at the level of ChatGPT-4, was decades away. Maybe it will happen in 2050. And they were obviously all wrong. It already happened.

Since then, AI has gone from kind of high school level to college level, to PhD level, to professor level and beyond in some areas, which leads us close to the point where the godfather of the whole field, Alan Turing, talked about in 1951. He said, look, folks, if you ever make machines that are just better, can out-think us in every way, they’re going to take control. That’s the default outcome. But he said, chill out. It’s far away. Don’t worry. I’ll give you a test, though, a canary in the coal mine, when you need to pay attention.

It’s called the Turing test. That’s when machines can master language and knowledge, which is what’s now happening with ChatGPT-4 and so on. And so basically, after a lot of hype and failed promises, we’re now at the point where we’re very close to probably the most important fork in the road in human history, where we have to ask ourselves, are we going to somehow build inspiring tools that help us do everything better and cure diseases and make us prosperous and strong, or are we going to just sort of throw away the keys to the planet by building some alien, amoral machine species that just sort of replaces us?

I really want to touch on this. I’m very fascinated by how you talk about the AIs that we’re creating as alien, and that’s very interesting. But just very briefly, what is the Turing test, and how has it been passed now?

The Turing test, the way Alan Turing defined it, is an imitation game. You basically get to interact with a machine, maybe by typing. And the question is, can you tell the difference between the machine and the human? There was actually a nerd paper that was written by a bunch of scientists recently, where they’ve now found that machines pass this test more often than humans, even. They’re even better at convincing people they’re human than humans are.

But in practice, passing the Turing Test means that you really master language and basic knowledge and so on in the way that today’s chatbots can clearly do. And the reason this test is so important is because if you ask yourself, why is it that when you go down to the zoo here in Washington, it’s the tigers that are in the cages, not the humans? Why is that? Is it because we are stronger than the tigers or have sharper teeth? Of course not. It’s because we’re smarter, right? And it’s kind of natural that the smarter species will dominate the planet. And that was the basic point Turing made, and it still stands.

People who don’t see this, I think, make the mistake of thinking of AI as just another technology, like the steam engine or the internet, whereas Turing himself was clearly thinking about it as a new species. That might sound very weird because your laptop isn’t a species, of course, but if you think of a species as something that can make copies of itself and have its own goals and do things, we’re not there now with AI.

But if you imagine in the not distant future, we have robots that can just outthink us in every way and outplan us and outstrategize us. Of course, they can also build robot factories and build new robots, they can build better robots, they can build still better robots, et cetera, and then gradually get more and more advanced than us. That checks every box of being a new species.

And at that point, before that point, we have to ask ourselves, is that really what we want to do? We have this incredible gift. We’re placed here as stewards of this Earth, with an ability to use technology for all sorts of wonderful stuff. And I love tech as much as anyone. Don’t we want to aim for something more ambitious than just replacing ourselves?

Again, before I start talking about this, you know, this sort of alien foreign thing, which we seem to be creating ourselves, I’ve been thinking a lot about how these AIs learn with all sorts of information. And, you know, information has become increasingly politicized, especially over the last decade. It’s always been a bit politicized, but in the last decade, it’s been sort of taken to a whole different level. You know, this is something we used to have as a huge challenge for us at The Epoch Times to cut through that. That’s part of the reason I think we’ve had a lot of growth is because I think we have.

You have, you know, Verity News now it’s called, and a kind of an attempt to do the same sort of thing. But it’s also been demonstrated that many of these chatbots, even at this, you know, what you, I guess you would call it still a primitive level of AI development, there are huge holes in their knowledge and really biased ways of thinking. It’s like the values of the programmers have basically gone into them. And there’s even ratings on what kind of values the different chatbots have. We’re not even talking about creating this AGI or anything like that. That itself seems a huge problem at this primitive level. Your thoughts?

For sure. I mean, George Orwell pointed that out. If someone can control the truth, in quotes, that’s pushed onto people, then they can control the world, of course. And living in some sort of AI-fueled 1984 is not what I want for my children, you know. Basically, the same thing as being a good journalist, which means that you pursue the truth, you follow the truth, whatever it is, even if it’s not what you had hoped you were going to find. And I sometimes get asked what I mean by being a scientist.

My definition would be that a scientist is someone who would rather have questions they can’t answer than answers they can’t question. And you’re laughing here, but think about Galileo. He asked some questions that the authorities didn’t want him to ask. Look at people more recently who asked questions that were deemed inconvenient, all sorts of stuff that got them blocked on Facebook or whatever, and then later turned out to be true. And what we see is this is a quite timeless thing. You know, George Orwell was onto something. The first thing that people who want to manipulate the truth will do is accuse their critics of spreading disinformation.

So as a scientist, I get really annoyed when people say, oh, just follow the science. Being a scientist is not like being a sheep and following what you’re supposed to follow. It’s asking all the tough questions, whether people get pissed or not about that. And that’s why I created the very new site where it’s just like in science, you know, it’s hard to figure out the truth. Let’s be honest.

Very hard.

Very hard. We had the world’s smartest physicists for hundreds of years believing in the wrong theory of gravity. And that wasn’t even political. They believed in Newton, and then Einstein came along 300 years later and said, oops, we were all wrong. So the idea that you can just figure out the truth by having some government-appointed or Facebook-appointed committee that’s going to decide it for you is ridiculously naive, right? If it was so easy to figure out the truth, you could shut down the universities, shut down all the news organizations. I think science has the best track record historically of ultimately getting to the truth, closer to the truth. And so the idea with Verity was just to sort of emulate that a little bit in the media.

Rule number one is you don’t censor anybody, even if they’re dressed badly or don’t have a fancy degree. If they have a good argument, you’ve got to listen to them. I’m pretty sure that someone back at MIT is going to criticize me, saying, hey, Max, why are you talking to people at The Epoch Times? You know, I’m a scientist. I will talk with anybody. I will listen to anybody, also. And that’s the scientific method, you know.

If you go to Verity News, all the different perspectives are in there. And we actually use machine learning to figure out what people from the different sides of a controversy all agree on. We call those facts. And then we also separate out where they disagree. So people can just go in if they’re busy, you know, oh, this seems to have happened because Fox News and CNN agree on it. And here is what these people say. Here’s what these people say. Now I can make my own mind up. That’s how I want to have it as science, as scientists, too. If someone is arguing about a vaccine or anything controversial, I want to see, okay, these ones say this, these say this. Now I can decide for myself.

One of the big challenges is that we have something that I kind of call, I call the megaphone. But it’s like when you have, you know, an information ecosystem where there’s, for some reason, consensus on an issue, no matter how crazy it turns out to be years later, right? And then that kind of dominates the information ecosystem, right? So according to your algorithms, you might think because of that, well, that’s the truth, because like all these different media agree on this point.

You know, one example was this idea of Russiagate. There was this false narrative that the president was a Russian agent. Everybody was writing it. You would think you would have believed it almost, right? But except that we were asking the difficult questions that got us in huge trouble. And of course, you know, you’re vindicated later, but you suffer along the way, and the question is just like Galileo, but which is just very newsable to distinguish between that. I’m just fascinated by what you’re trying to do here.

We actually did an interesting experiment. This was with a student, one of my thesis students, Samantha D’Alonzo, where we gave AI a million news articles to read and asked if it could automatically figure out which newspaper wrote the article just by reading the words. And it was remarkably good. And it put all of the newspapers on a two-dimensional plane. The obvious Left to Right, like if it’s an article about abortion, it was pretty easy to tell. The AI discovered that if it talks about fetuses or unborn babies, it could make some guesses as to what views the journalist had about that matter.

But it was a whole separate axis also that the AI just found by itself, which is what we call the establishment bias. Are you basically saying the same thing that everybody else is saying? Or are you being the Galileo here with saying the unpopular thing? It’s often newspapers that are a little bit farther away from power that don’t always echo the big talking points of the corporations and so on. So there is an objective way of ultimately noticing this.

And what Verity News tries to do is just make sure we sample from all the corners of this for every article. And in particular, whenever there’s a topic, you know what the controversy is going to be about it. So you make sure you look at newspapers on both sides of it and see what they agree on. So that the viewer can come in very quickly and say, okay, this is what happened. Here’s what they say. Here’s what they say. And make their own mind up. Say here’s what they say and make their own mind up. It’s incredibly important to me that we never tell people what to think, that we make it easy for them to make up their own mind.

But what you just said is really super interesting, right? Because what if the AI is injecting inherent bias? I mean, this dovetails perfectly, right?

Of course it is, and in two ways. I mean, one is just from its training data and so on. But also, if you have a country and all the media is owned by one guy, right, the media will start writing nicer things about that guy. There was a study about what happened to the views of the Washington Post after Jeff Bezos bought it. You will not be so surprised that you will fall off your chair if I tell you that he found that it started criticizing Amazon less, you know.

And now we’re in a situation where OpenAI, Google, and these companies are controlling an ever larger fraction of the news that people get through their algorithms, which gives them an outsized power. It’s only the beginning of an ever more extreme power concentration that I think we’ll see if we keep giving corporate handouts to these AI companies, let them do whatever they want, that they will define the truth. And the truth will always include, oh, and we tech companies are great and should be allowed to do whatever you want.

One of the things that shocks me is that there are actually in the literature of some of these AI companies, some of them appear to be wanting to create artificial general intelligence. So I’m going to get you to tell me what that is for the benefit of our audience. And also that is astonishing and almost like some sort of odd quasi-religious commitment, right, which scares the living daylights out of me.

First of all, artificial intelligence is just non-biological intelligence, the idea being that it has to do with information processing. You don’t need to do the information processing in carbon atoms and neurons and brains; we found you can also do it with silicon atoms and computers, right? Intelligence itself in computer science is defined simply as the ability to accomplish goals. It doesn’t matter whether the thing has any kind of subjective experience or emotions or anything like that.

We just measure it. Can it beat you at chess? Can it drive a car better than you? Can it make more money than you at the stock market? That’s how we operationally define intelligence. So what’s artificial general intelligence then? Well, the AI we have so far is still pretty stupid in many ways. In many cases, it’s quite narrow, also, that it can do some things and not others.

For example, most AI systems today are very passive. What you have there in your iPad is, it can answer questions, but it’s not outdoing anything in the world. It’s not making plans for what it’s going to do next year, right? Artificial general intelligence is defined simply as AI that can do everything we can do, basically, as well as we can or better. And some of these companies have put on their website that their goal is to basically automate all economically valuable work.

People who say there will always be jobs that humans can do better than machines are simply predicting that there will never be AGI, artificial general intelligence. They’re betting against these companies. For many years, people thought that AGI was science fiction and it was impossible. We already talked about how people predicted that ChatGPT was impossible, or at least until 2050. So we should eat humble pie.

And I think it’s increasingly obvious to people who work in the field that it’s absolutely possible. If we get to where machines can do all our jobs, that also includes doing the job of making better AI. So very quickly, the R&D timescale for making still better AI will shorten from months to years for human researchers to maybe weeks or months or days. And machines will keep just improving themselves until they bump up against the next bottleneck, which is the law of physics.

But there is no law of physics saying you can’t have something processing information vastly better than us. You’re a very smart guy, but your brain is limited by the size of your mom’s birth canal, right? And moreover, when your brain runs on 20 watts of electricity, like a light bulb, you know, and you can easily put millions of watts into your computer. My laptop runs about one billion times faster than my brain also. So once machines start improving themselves, they can get as much smarter than us, I think it’s obvious, as we are smarter than snails. And if you had the idea that somehow snails were going to control us, or they were going to build us and then control us, you should laugh at this because it’s pretty obviously a tall order.

So what I describe now is what’s known as superintelligence, which is what probably will come not long after artificial general intelligence. And this is exactly what Alan Turing warned about. He was not worried that some sort of calculator was going to take over the world. He was worried that we were going to make self-improving machines that would eventually sort of take over.

There’s a really interesting historical analogy here. Enrico Fermi, the famous physicist, in 1942, he built the first ever nuclear reactor, actually under a football stadium in Chicago. It totally freaked out the world’s top physicists when they learned about this. Not because the reactor was dangerous in any way. It wasn’t, you know. But because they realized, oh my, this was the last big hurdle to building the nuclear bomb. That was like the Turing test for nuclear bombs. So now they know maybe it’ll take three years, four years.

But it’s not going to happen.

It’s going to happen. It’s just a matter of engineering now. In fact, it took three years there. The Trinity test was in July of 1945, the first bomb. It’s exactly the same with the Turing test when that was passed now with things like GPT-4; it became clear that from here on out to buildings, things we could actually lose control over, it’s just engineering. There’s no fundamental obstacle anymore. And instead, it’s all going to come down to political will. Are we going to want to do this or not?

Can I inject some optimism in this because I’m just feeling a little gloomy in the direction we’re going here? We still have not actually had a nuclear war between the superpowers because there was a political will not to have one, so we didn’t have one, you know, even though there were some close calls. And it’s absolutely not a foregone conclusion either that we’re just going to hand over the keys to our future to some stupid alien machine because, frankly, almost nobody wants it. There are actually a very small number of tech people who want, who have actually gone on YouTube and places like that and said that they want humanity to be replaced by machines because they’re smarter somehow and that’s better. I think of that as digital eugenics.

It’s a deeply nihilistic thought. I can’t even imagine what these people are actually thinking. It’s insane. Isn’t it by definition maybe? I don’t know.

Yes, I think they’re sort of salivating over some sort of digital master race. I’m not a psychologist. I’m not the one who can get into their minds exactly. I believe in free speech. I believe they should have the right to want what they want. But I’m on team human. I’m not on their team. I want our children to have the same rights to a long and meaningful life that we have. And frankly, I think you’re on my side on this.

I’m deeply on your side, but my concern, I mean, we’re talking about this, right, is that I think the people who are actually working on this are above average more predisposed to the view that you described. And that’s the concern, right? And the other part is that with the nuclear bomb, there’s this mass physical devastation that happens when you launch one. This is somehow different. This is ethereal. The mass physical devastation doesn’t happen until you’ve already sort of… you know, ChatGPT doesn’t feel like it can pose an existential risk the way that a proto-nuclear bomb does.

The biggest difference of all is we have all seen videos of nuclear explosions. And nobody has seen a video of or anything about AGI or superintelligence because it’s in the future. So the uphill battle you and I have here, if we want to make other people pay attention to this, is to imagine we were warned about a nuclear winter in 1942. People would be like, what are you even talking about? You know, and if we do get there, oh, there can be plenty of devastation. I mean, the most likely outcome is that it just causes human extinction.

And we talked about the suppression of memory-holding of inconvenient truths. One of the most memory-holed stories of 2023 was that the CEOs of all of these companies, Sam Altman, Demis Hassabis, and Ilya Sutskever, signed a statement saying, hey, this could cause human extinction. Let’s be careful. They said it. It’s kind of like if Oppenheimer and Einstein had written a letter warning that nuclear weapons could kill people, and then everybody just sort of forgot about it. So there could be devastation.

But it feels so abstract now because it’s not today’s AI we’re afraid of. Today’s AI can, of course, brainwash people, manipulate people, cause power concentration, and do censorship. But it’s not today’s AI that we could simply take; we could lose control over. It’s the AI that we will get in the future if we let it happen. The huge shift that’s happened after we passed the Turing test, though, this future is no longer decades away, right?

Dario Amodei, who leads Anthropic, one of the top American companies, predicts that by 2027, two years from now, AGI will have what he calls a country of geniuses in a data center, where these geniuses in the data center, these AIs, are better than Nobel laureates in physics, chemistry, and math at their various tasks. And so most likely, we’ll get to the point where this could happen during Trump’s presidency.

Trump is the AI president. It’s going to be what he does during his watch that determines how this goes. I promised you some optimism. So here’s the optimism. This dystopian future, almost nobody wants it except for some fringe nerds. And that’s the main… you know, there have been a lot of polls in the U.S. The vast majority of Americans absolutely don’t want this future. There’s not even any partisan divide on that.

Moreover, I think what’s beginning to happen is people in the NatSec community are beginning to also realize that this is a national security threat. You know, if you’re working in the U.S. NatSec community and your job is to keep tabs on other countries that could pose a NatSec threat, and then you hear some guy talking about a country of geniuses in a data center, you’ll think, well, maybe I should put his country on my list to pay attention to also. Do I really want some San Francisco-based nerd who’s had too much Red Bull to drink, you know, to make decisions about something that could overthrow the U.S. government? The truth, the painful truth that’s really beginning to sink in is that we’re much closer to figuring out how to build this stuff than we are to figuring out how to control it.

But that’s also the good news because nobody in the NatSec community wants us to build something uncontrollable. Even if you start talking about weapons, you want controllable weapons. We don’t want uncontrollable weapons. And this is the way the NatSec community will think in every country. You know, take China for example; you know, I’m pretty sure Xi Jinping would like to not lose his control. So if some Chinese tech company could overthrow him, what do you think he’s gonna do about that tech company?

One of the things that drives innovation is technological competition. I think that’s obvious, right? I think it’s a major driver, like once you’re trying to get ahead of the others. And this is driving, I’m sure, this whole chatbot mass evolution, quick evolution that’s happening right now. The difference is that the moment you let the genie out of the bottle, the moment that thing can start building itself. I don’t know at what point. We’re rushing right now. We’re in an arms race. You mentioned communist China, Xi Jinping, a completely amoral governing regime.

There’s no moral boundary to be crossed. You’re right. The moral boundary is control. Absolutely, the Chinese Communist Party wants to not relinquish an iota of control. That’s true. However, any technology that’s outlawed or problematic—CRISPR babies would be a great example—though technically the guy didn’t go to jail for that. But you know all that stuff is happening. Okay. Why? Because there is no moral boundary and there’s an arms race, a technological arms race in all these areas that we can get ahead. And, you know, all these American companies have built AI centers, you know, notably Microsoft and so forth.

So, you know that all that information has been siphoned and used. And I’m convinced that the NatSec people or the military people are going to be like, hey, we got to keep pushing the envelope here because otherwise those other guys are going to be ahead. And then the genie comes out of the bottle, and now it’s doing its own thing. How does that not happen?

The key thing is to think about this envelope that you talk about, to think about what is the edge of this envelope actually. It’s not so simple that AI is just either you have less of it or you have more of it. Think if there’s a space of different kinds of AI systems with different properties. For example, you have a lot of intelligence in your iPad there, but it’s narrow intelligence, not very general. And it’s, for example, it can’t drive. And it doesn’t have agency. It doesn’t have goals that it’s out pursuing with a robotic body in the world.

At least I hope.

Yes. And the thing that we clearly don’t know how to control is actually only when you combine three separate capabilities: when you have not just very strong domain intelligence at what you’re good at, like AlphaFold for curing cancer or whatever, and very strong generality, so it knows how to manipulate people and produce new pandemics or whatever, and also agency, autonomy. It’s only when you put those three together that we don’t know how to control it. It’s also only when you put those three all together that it can do all the human jobs and cause a lot of negative upheavals in our society.

But if you have only one or two of those traits, it’s perfectly possible to both control it and also make sure that it just complements people rather than replaces them. You have autonomy and generality in your intelligence, etc., so you’re not going to be replaced by something that lacks one of those. So if you think of the Venn diagram—I’m being a nerd now—you know there’s like a donut shape where you just pick one or two of those traits but not all three. That lets you kind of have the cake and eat it, and I think that that’s where we’re going to end up in the donut, so to speak.

If you want to make a lot of money on AI, suppose you want to build the world’s best self-driving car that can drive better than any human driver. We don’t have it now. What do you need from this? Yes, you need, of course, autonomy and you need domain intelligence. You better be really good at driving. But do you really need to know how to make bioweapons? Do you need to have so much generality in it that your car can persuade you to vote for your least favorite politician? You probably wouldn’t even want that. You just, hey car, can you just stick to driving, please? And similarly, if you want to cure cancer, there’s no reason to teach a cancer-curing AI how to manipulate people or how to drive cars.

So I think what we’re going to—this is my optimism—where the race is going to shift is towards tool AI, the kind of AI here in the donut where we know how to control it. To me, a tool is what I can control. I like to drive a powerful car, not an uncontrollable car, right? Similarly, what military commander in any country is going to want an uncontrollable drone swarm? I think they would prefer the controllable kind, right? So they’re not going to put all this extra AGI stuff in it so it can persuade the commander of something else. And we will see a competition of who can build the best tools between companies and between countries.

But there will be, at some point, a hard line drawn by the Nazi community saying no one can make stuff that we don’t know how to control. And you’re right that people in different companies and different countries have very different views of things. But the Soviet Union-U.S. dynamic shows that you don’t need to necessarily agree on everything to agree not to have a nuclear winter. It’s not like there wasn’t a great trust between Ronald Reagan and Brezhnev, right? But they still never nuked each other because they both realized that this was just suicide. And they never even signed a treaty to that effect. There was no treaty where Reagan hugged Brezhnev on a stage and said, I promise not to nuke you. Because the U.S. knew that the Russians viewed it as suicide trying to nuke the U.S. And the Russians knew that the converse was also true. And so you had this red line that nobody crossed.

And I think building uncontrollable, smarter-than-human machines is exactly the same kind of red line. Once it becomes clear to everybody that that’s just suicide and no one is going to do it. Instead, what people will do is race with tools, and then they’ll come up with some basic safety standards just to protect their own people. Like, do you know that AI is currently the only industry in the U.S. that makes powerful stuff that has less regulation than sandwiches? If someone has a sandwich shop in San Francisco, before they can sell their first sandwich, some health inspector checks out the kitchen.

And a great many other things. Yes, correct.

Yeah. If someone in OpenAI has this crazy uncontrollable superintelligence and wants to release it tomorrow, they can legally do so. It used to be that way also, for example, for medicines. Have you heard of thalidomide?

Yes.

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