#155 – Max Tegmark: AI and Physics

Max Tegmark is a physicist and AI researcher at MIT. Please support this podcast by checking out our sponsors: – The Jordan Harbinger Show: https://www.jordanharbinger.com/lex/ – Four Sigmatic: https://foursigmatic.com/lex and use code LexPod to get up to 60% off – BetterHelp: https://betterhelp.com/lex to get 10% off – ExpressVPN: https://expressvpn.com/lexpod and use code LexPod to get 3 months free EPISODE LINKS: News Project Explainer Video: https://www.youtube.com/watch?v=PRLF17Pb6vo News Project Website: https://www.improvethenews.org/ Max’s Twitter: https://twitter.com/tegmark Max’s Website: https://space.mit.edu/home/tegmark/ Future of Life Institute: https://futureoflife.org/ Lex Fridman Podcast #1: https://www.youtube.com/watch?v=Gi8LUnhP5yU PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ YouTube Full Episodes: https://youtube.com/lexfridman YouTube Clips: https://youtube.com/lexclips SUPPORT & CONNECT: – Check out the sponsors above, it’s the best way to support this podcast – Support on Patreon: https://www.patreon.com/lexfridman – Twitter: https://twitter.com/lexfridman – Instagram: https://www.instagram.com/lexfridman – LinkedIn: https://www.linkedin.com/in/lexfridman – Facebook: https://www.facebook.com/LexFridmanPage – Medium: https://medium.com/@lexfridman OUTLINE: Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time. (00:00) – Introduction (08:15) – AI and physics (21:32) – Can AI discover new laws of physics? (30:22) – AI safety (47:59) – Extinction of human species (58:57) – How to fix fake news and misinformation (1:20:30) – Autonomous weapons (1:35:54) – The man who prevented nuclear war (1:46:02) – Elon Musk and AI (1:59:39) – AI alignment (2:05:42) – Consciousness (2:14:45) – Richard Feynman (2:18:56) – Machine learning and computational physics (2:29:53) – AI and creativity (2:41:08) – Aliens (2:56:51) – Mortality

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Lex Fridman?

  The following is a conversation with Max Tegmark, his second time on the podcast. In fact, the previous conversation was episode number one of this very podcast. He is a physicist and artificial intelligence researcher at MIT, co-founder of the Future of Life Institute and author of Life 3.0, Being Human in the Age of Artificial Intelligence. He's also the head of a bunch of other huge fascinating projects and has written a lot of different things that you should definitely check out. He has been one of the key humans who has been outspoken about long-term existential risks of AI and also its exciting possibilities and solutions to real-world problems.

• 0:42Lex Fridman?

  Most recently, at the intersection of AI and physics and also in re-engineering the algorithms that divide us by controlling the information we see and thereby creating bubbles and all other kinds of complex social phenomena that we see today. In general, he's one of the most passionate and brilliant people I have the fortune of knowing. I hope to talk to him many more times on this podcast in the future. Quick mention of our sponsors: The Jordan Harbinger Show, Four Sigmatic Mushroom Coffee, BetterHelp Online Therapy, and ExpressVPN. So the choice is wisdom, caffeine, sanity, or privacy. Choose wisely, my friends, and if you wish,

• 1:25Lex Fridman?

  click the sponsor links below to get a discount to support this podcast. As a side note, let me say that much of the researchers in the machine learning and artificial intelligence communities do not spend much time thinking deeply about existential risks of AI. Because our current algorithms are seen as useful but dumb, it's difficult to imagine how they may become destructive to the fabric of human civilization in the foreseeable future. I understand this mindset, but it's very troublesome. To me, this is both a dangerous and uninspiring perspective, reminiscent of a lobster sitting in a pot of lukewarm water that a minute ago was cold. I feel a kinship with this lobster. I believe that already the

• 2:10Lex Fridman?

  The algorithms that drive our interaction on social media have an intelligence and power that far outstrip the intelligence and power of any one human being. Now really is the time to think about this, to define the trajectory of the interplay of technology and human beings in our society. I think that the future of human civilization very well may be at stake over this very question of the role of artificial intelligence in our society. If you enjoy this thing, subscribe on YouTube, review it on Apple Podcasts, follow us on Spotify, support it on Patreon, or connect with me on Twitter at Lex Fridman. As usual, I'll do a few minutes of ads now and no ads in the middle. I tried to make these interesting, but I give you timestamps, so if you skip, please

• 2:53Lex Fridman?

  still check out the sponsors by clicking the links in the description. It is in fact the best way to support this podcast. This episode is sponsored by The Jordan Harbinger Show. Go to jordanharbinger.com/lex, subscribe to it, listen, you won't regret it. I've been binging on this podcast for the entirety of 2020. Jordan is a great interviewer. He gets the best out of his guests, dives deep, calls them out when it's needed, and makes the whole thing fun to listen to. He has interviewed Kobe Bryant, Mark Cuban, Neil deGrasse Tyson, Garry Kasparov, and many more. Perhaps more importantly, he is unafraid of addressing challenging, even controversial

• 3:36Lex Fridman?

  topics with thought and grace. I especially like his Feedback Fridays episodes, where his combination of fearlessness and thoughtfulness is especially on display, touching topics of sex, corruption, mental disorders, hate, love, and everything in between. Again, go to jordanharbinger.com/lex is how he knows I sent you. On that page, there's links to subscribe to the show on everywhere you listen to podcasts, including Apple Podcasts, Spotify. If you're listening to this, I'm sure you know how this works. Oh, and if you like it, probably go give five stars to the show, leave a nice review, tell them I sent you. This show is also sponsored by the thing I currently really need, which is coffee.

• 4:19Lex Fridman?

  Four Sigmatic, the maker of delicious mushroom coffee and plant-based protein. I enjoy both. The coffee has lion's mane mushroom for productivity and chago mushroom for immune support. The plant-based protein has immune support as well and tastes delicious, which I think honestly, at least for me, is the most important quality of both protein and coffee. Supporting your immune system is one of the best things you can do now to stay healthy in this difficult time for the human species. Not only does 4Sigmatic always have 100% money-back guarantee, but right now, you can try their amazing products for up to 50% off.

• 5:00Lex Fridman?

  And on top of that, you get extra discounts for just the listeners of this podcast if you go to 4sigmatic.com/lex. That's 4sigmatic.com/lex. This episode is sponsored by BetterHelp, spelled H-E-L-P. Help. I always think about the movie Cast Away when I spell out the word help. Okay, they figured out what you need and match you with a licensed professional therapist in under 48 hours. I chat with a person on there and enjoy it. Of course, I also have been talking to, over the stretch of 2020 and looks like 2021 as well, to David Goggins, who is definitely not a licensed professional,

• 5:44Lex Fridman?

  or some would say sane, but he does help me meet his and my demons and become comfortable to exist in their presence. This is just my view, but I think mental struggle is essential for creation. But I think you can struggle in a way that's controlled and done beautifully, as opposed to in a way that destroys you. I think therapy can help in this and BetterHelp is a good option for that. They're easy, private, affordable, available worldwide. You can communicate by text anytime and schedule a weekly audio and video session. To give a shout out to the two OGs, my two favorite psychiatrists, Sigmund Freud and Carl Jung. When I was younger, their work was important in my intellectual development.

• 6:28Lex Fridman?

  Anyway, check out betterhelp.com/lex. That's betterhelp.com/lex.

• 6:34Lex Fridman?

  This show is also sponsored by ExpressVPN. It provides privacy in your digital life. Without VPN, your internet service provider can see every site you've ever visited, keeping a log of every single thing you did online. So your internet provider like AT&T or Comcast is allowed to store those logs and sell this data to anyone. That's why you should use ExpressVPN as much as possible. I do it, you should consider doing it as well. They don't keep any logs. They audit their tech by external companies. These guys are legit. I think this topic and VPNs certainly are especially relevant now when the power of social media firms and ISPs was made apparent

• 7:18Lex Fridman?

  with a wave of deplatforming actions. We need to use tools that lessen the power of these centralized entities. I use ExpressVPN as just one example of such a tool. Go to expressvpn.com/lexpod to get an extra three months free on a one-year package. It's a big red button if you enjoy those kinds of things. I certainly do. Okay. That's expressvpn.com/lexpod. Sign up for the privacy and the big red button. That's expressvpn.com/lexpod. And now here's my conversation with Max Tagmark.

• 8:15Lex Fridman?

  So people might not know this, but you were actually episode number one of this podcast just a couple of years ago. And now we're back. And it so happens that a lot of exciting things happened in both physics and artificial intelligence, both fields that you're super passionate about. Can we try to catch up to some of the exciting things happening in artificial intelligence, especially in the context of the way it's cracking open the different problems of the sciences?

• 8:46Max Tegmark?

  Yeah, I'd love to, especially now as we start 2021 here. It's a really fun time to think about what were the biggest breakthroughs in AI. Not the ones necessarily that media wrote about, but that really matter. And what does that mean for our ability to do better science? What does it mean for our ability to help people around the world? And what does it mean for new problems that they could cause if we're not smart enough to avoid them? So, you know, what do we learn basically from this?

• 9:18Lex Fridman?

  Yes, absolutely. So one of the amazing things you're part of is the AI Institute for Artificial Intelligence and Fundamental Interactions. What's up with this institute? What are you working on? What are you thinking about?

• 9:31Max Tegmark?

  The idea is something I'm very on fire with, which is basically AI meets physics. And, you know, it's been almost five years now since I shifted my own MIT research from physics to machine learning. And in the beginning, I noticed a lot of my colleagues, even though they were polite about it, well, I kind of, what is Max doing? What is this weird stuff?

• 9:55Lex Fridman?

  He's lost his mind.

• 9:57Max Tegmark?

  Then, but then gradually, I, together with some colleagues, were able to persuade more and more of the other professors in our physics department to get interested in this. And now we got this amazing NSF center, so 20 million bucks for the next five years, MIT and a bunch of neighboring universities here also. And I noticed now those colleagues who were looking at me funny have stopped asking why I'm, what the point is of this, because it's becoming more clear. And I really believe that, of course, AI can help physics a lot, to do better physics.

• 10:36Max Tegmark?

  But physics can also help AI a lot, both by building better hardware. My colleague Marin Soljajic, for example, is working on an optical chip for much faster machine learning, where the computation is done not by moving electrons around, but by moving photons around, dramatically less energy use, faster, better. We can also help AI a lot, I think, by having a

• 11:07Max Tegmark?

  A different set of tools and a different, maybe more audacious attitude. You know, AI has to significant extent been an engineering discipline where you're just trying to make things that work. And being less, more interested in maybe selling them than in figuring out exactly how they work and proving theorems about that they will always work, right? Contrast that with physics, you know, when Elon Musk sends a rocket to the International Space Station, they didn't just train with machine learning, oh, let's fire it a little bit left, more to the left, a bit more to the right, that also missed, let's try here. No, you know, we figured out Newton's laws of gravitation and other, and got other things, and got a really deep fundamental understanding.

• 11:52Max Tegmark?

  And that's what gives us such confidence in, in rockets. And my vision is that in the future, all machine learning systems that actually have impact on, on people's lives will be understood at a really, really deep level, right? So we trust them not because some sales rep told us to, but because they've earned our trust. We can, and really safety critical things even prove that they will always do, you know, what we expect them to do. That's very much the physics mindset. So it's interesting, if you look at big breakthroughs that have happened in machine learning this year, you know, from dancing robots, you know, it's pretty fantastic, not

• 12:34Max Tegmark?

  just because it's cool, but if you just think about not that many years ago, this YouTube video at this DARPA challenge where the MIT robot comes out of the car and face plants.

• 12:45Lex Fridman?

  Yeah.

• 12:46Max Tegmark?

  How far we've come in, in just a few years. Similarly, AlphaFold 2, you know, crushing the protein folding problem. We can talk more about implications for medical research and stuff, but hey, you know, that's huge progress. You, you can look at GPT-3, that can spout off English texts, which sometimes really, really blows you away. You can look at the Google, at DeepMind's MuZero, which doesn't just kick her butt in Go and Chess and Shogi, but also in all these Atari games, and you don't even have to teach it the rules now.

• 13:28Max Tegmark?

  You know, what all of those have in common is, besides being powerful, is we don't fully understand how they work. And that's fine if it's just some dancing robots and the worst thing that can happen is they face plant, right? Or if they're playing Go and the worst thing that can happen is that they make a bad move and lose the game, right? It's less fine if that's what's controlling your self-driving car or your nuclear power plant. And we've seen already that even though Hollywood had all these movies where they try to make us worry about the wrong things, like machines turning evil, the actual bad things that have happened with automation have not been machines turning evil.

• 14:11Max Tegmark?

  They've been caused by overtrust in things we didn't understand as well as we thought we did, right? Even very simple automated systems like what Boeing put into the 737 MAX, right? Yes. Killed a lot of people. Was it that that little simple system was evil? Of course not. But we didn't understand it as well as we should have, right? And we trusted without understanding. Exactly. And overtrust. We didn't even understand that we didn't understand, right? The humility is really at the core of being a scientist. I think step one, if you want to be a scientist, is don't ever fool yourself into thinking you understand things when you actually don't. Yes. Right? That's probably good advice for humans in general.

• 14:55Max Tegmark?

  I think humility in general can do us good, but in science, it's so spectacular. Like, why did we have the wrong theory of gravity ever from Aristotle onward and close until like Galileo's time? Like, why would we believe something so dumb as that if I throw this water bottle, it's gonna go up with constant speed until it realizes that its natural motion is down? Changes its mind. You know, because we, people just kind of assumed Aristotle was right, he's an authority, we understand that. Why did we believe things like that the sun is going around the earth? Why did we believe that time flows at the same rate for everyone until Einstein? Same exact mistake over and over again. We just weren't humble enough to acknowledge

• 15:37Max Tegmark?

  that we actually didn't know for sure. We assumed we knew, so we didn't discover the truth because we assumed there was nothing there to be discovered, right? There was something to be discovered about the 737 Max. And if you had been a bit more suspicious and tested it better, we would have found it. And it's the same thing with most harm that's been done by automation so far, I would say. So I don't know if you, did you hear of a company called Knight Capital? No. So good. That means you didn't invest in them earlier.

• 16:07Max Tegmark?

  They deployed this automated rating system. Yes. All nice and shiny. They didn't understand it as well as they thought, and it went about losing 10 million bucks per minute. Yeah. For 44 minutes straight. No. Until someone presumably was like, oh, no, shut this off, you know? Was it evil? No, it was, again, misplaced trust, something they didn't fully understand, right? And there have been so many, even when people have been killed by robots, it's just quite rare still, but in factory accidents, it's in every single case been not malice, just that the robot didn't understand that a human is different from an auto part or

• 16:47Max Tegmark?

  whatever. And we, so this is where I think there's so, so much opportunity for physics approach, where you just aim for a higher level of understanding. And if you look at the, all these systems that we talked about, from the, from reinforcement learning systems and dancing robots, to all these neural networks that power GPT-3 and, and GoPlaying software and stuff, they're all basically black boxes.

• 17:18Max Tegmark?

  Much like, not so different from if you teach a human something, you have no idea how their brain works, right? Except the human brain at least has been error corrected during many, many centuries of evolution in a way that these, some of these systems have not, right? And my, my MIT research is entirely focused on demystifying this black box. Intelligible intelligence is my slogan. That's a good line. Intelligible intelligence. Yeah, that we shouldn't settle for something that seems intelligent, but we should, it should be intelligible so that we actually trust it because we understand it, right? Like, again, Elon trusts his rockets because he understands Newton's laws and thrust and how everything works. And let me tell you what, can I tell you why I'm optimistic about this? Yes.

• 18:03Max Tegmark?

  I think, I think there is, we've made a bit of a mistake where we, some people still think that somehow we're never going to understand neural networks. And we're just going to have to learn to live with this. It's this very powerful black box. Basically, for those, you know, who haven't spent time building their own, it's super simple what happens inside. You send in a long list of numbers and then you do a bunch of operations on them, multiply by matrices, et cetera, et cetera. And some other numbers come out, that's the output of it. And then there are a bunch of knobs you can tune. And when you change them, you know, it affects the computation, the input output relation. And then you just give the computer some definition of good and it keeps optimizing

• 18:47Max Tegmark?

  these knobs until it performs as good as possible. And often you go like, wow, that's really good. This robot can dance or this machine is beating me at chess now. And in the end, you have something which even though you can look inside it, you have very little idea of how it works. You know, you can print out tables of all the millions of parameters in there. Is it crystal clear now how it's working? No, of course not, right? Many of my colleagues seem willing to settle for that. And I'm like, no, that's like the halfway point.

• 19:19Max Tegmark?

  Some have even gone as far as sort of guessing that the mystery, the inscrutability of this is where the, some of the power comes from and sort of, some sort of mysticism. I think that's total nonsense. I, I think the real power of neural networks comes not from inscrutability, but from differentiability. And what I mean by that is simply that the output depends, changes only smoothly if you tweak your knobs. And then you can use all these powerful methods we have for optimization in science. We can just tweak them a little bit and see, did that get better or worse? That's the fundamental idea of machine learning,

• 19:59Max Tegmark?

  that the machine itself can keep optimizing until it gets better. Suppose you wrote this algorithm instead in Python or some other programming language. And then what, what the knobs did was they just changed random letters in your, in your code. Now we're just epically failing, right? You change one thing and instead of saying print, it says synt, syntax error. You don't even know, was that for the better or for the worse, right? This to me is, this is what I believe is the fundamental power of neural networks.

• 20:30Lex Fridman?

  And just to clarify, the changing of the different letters in a program would not be a differentiable process.

• 20:35Max Tegmark?

  It would make it an invalid program typically. And then you wouldn't even know if, if you changed more letters, if it would make it work again, right?

• 20:43Lex Fridman?

  So that's the magic of neural networks, the inscrutability.

• 20:48Max Tegmark?

  Differentiability, that, that every, every setting of the parameters is a program and you can tell is it better or worse, right? And so.

• 20:55Lex Fridman?

  So you don't like the poetry of the mystery of neural networks as the source of its power?

• 21:00Max Tegmark?

  I genuinely like poetry, but.

• 21:02Lex Fridman?

  Not in this case.

• 21:04Max Tegmark?

  It's so misleading. And it's, above all, it, it shortens changes us. It fails, it, it makes us underestimate what we can, the good things we can accomplish. Because, so what we've been doing in my group is basically step one, train the mysterious neural network to do something well. And then step two, do some additional AI techniques to see if we can now transform this black box into something equally intelligent that you can actually understand. So for example, I'll give you one example, this AI Feynman project that we just published, right? So. We took the one hundred most famous or complicated equations from one of my favorite physics textbooks, in fact, the one that got me into physics in the first place, Feynman

• 21:49Max Tegmark?

  lectures on physics. And so you have a formula, you know, maybe it has, what goes into the formula is six different variables and then what comes out is one. So then you can make like a giant Excel spreadsheet with seven columns. You put in just random numbers for the six columns for those six input variables and then you calculate with a formula the seventh column, the output. So maybe it's like the force equals in the last column, some function of the other. And now the task is, okay, if I don't tell you what the formula was, can you figure that out from looking at my spreadsheet I gave you? Yes. This problem is called symbolic regression. If I tell you that the formula is what we call a linear formula, so it's just that

• 22:33Max Tegmark?

  the output is some sum of all the things input that the time some constants, that's the famous easy problem we can solve. We do it all the time in science and engineering. But the general one, if it's more complicated functions with logarithms or cosines or other math, it's a very, very hard one and probably impossible to do fast in general just because the number of formulas with N symbols now just grows exponentially, just like the number of passwords you can make grow dramatically with length. So but we had this idea that if you first have a neural network that can actually approximate the formula, you just trained it, even if you don't understand how it works,

• 23:17Max Tegmark?

  that can be a first step towards actually understanding how it works. So that's what we do first. And then we study that neural network now and put in all sorts of other data that wasn't in the original training data and use that to discover simplifying properties of the formula. And that lets us break it apart often into many simpler pieces in a kind of divide and conquer approach. So we were able to solve all of those hundred formulas, discover them automatically, plus a whole bunch of other ones. And it's a, it's actually kind of humbling to see that this code, which anyone who wants now who's listening to this can type pip install AI Feynman on their computer and run it, you know, it can actually do.

• 24:01Max Tegmark?

  What Johannes Kepler spent four years doing when he stared at Mars data? Until he's like, finally, eureka, this is an ellipse.

• 24:08Lex Fridman?

  Yeah.

• 24:10Max Tegmark?

  This will do it automatically for you in one hour, right? Or Max Planck, he was looking at at how much radiation comes out from at different wavelengths from a hot object and discovered the famous black body formula. This discovers it automatically. I'm I'm actually excited about

• 24:30Max Tegmark?

  seeing if we can discover not just old formulas again, but new formulas that no one has seen before.

• 24:37Lex Fridman?

  And do you like this process of using kind of a neural network to find some basic insights and then dissecting the neural network to then gain the final? So that's in that way, you've

• 24:52Lex Fridman?

  forcing the explainability issue. You know, really trying to analyze a neural network for the things it knows, you know, to come up with the final beautiful, simple theory, underlying the whole, the initial, the initial system that you were looking at.

• 25:08Max Tegmark?

  I I love that. And and the reason I'm so optimistic that it can be generalized to so much more is because that's exactly what we do as human scientists. Think think of Galileo, whom we mentioned, right? I bet when he was a little kid, if his dad threw him an apple, he would catch it. Why? Because he had a neural network in his brain that he had trained to predict the parabolic orbit of apples that are thrown under gravity. If you throw a tennis ball to a dog, it also has this same ability of deep learning to figure out how the ball is going to move and catch it. But Galileo went one step further. When he got older, he went back and was like, wait a minute.

• 25:51Max Tegmark?

  I can write down a formula.

• 25:53Lex Fridman?

  Yes.

• 25:53Max Tegmark?

  Y equals X squared, a parabola. You know, and he helped revolutionize physics as we know it, right?

• 26:02Lex Fridman?

  So there was a basic neural network in there from childhood that captured like the base, the experiences of observing different kinds of trajectories. And then he was able to go back in with another extra little neural network and analyze all those experiences and be like, wait a minute, there's a deeper rule here.

• 26:21Max Tegmark?

  Exactly. He was able to distill out in symbolic form what that complicated black box neural network was doing, right? Not only did he, the formula he got ultimately become more accurate, you know, and similarly, this is how we, how Newton got Newton's laws, which is why Elon can send rockets to the space station now, right? So it's not only more accurate, but it's also simpler, much simpler. And it's so simple that we can actually describe it to our friends and each other, right? We've talked about it just in the context of physics now, but hey, you know, isn't this what we're doing when we're talking to each other also? We go around with our neural networks, just like dogs and cats and chipmunks and blue

• 27:03Max Tegmark?

  jays, and we experience things in the world. But then we humans do this additional step on top of that, where we then distill out certain high level knowledge that we've extracted from this in a way that we can communicate it to each other in a symbolic form, in English in this case, right? So if we can do it, and we believe that we are information processing entities, then we should be able to make machine learning that does it also.

• 27:32Lex Fridman?

  Well, do you think the entire thing could be learning? Because there, this dissection process, like for AI refinement, the secondary stage feels like something like reasoning. And the initial step feels like more like the, the more basic kind of differentiable learning. Do you think the whole thing could be differentiable learning? Do you think the whole thing could be basically neural networks on top of each other? It's like turtles all the way down, could it be neural networks all the way down?

• 28:01Max Tegmark?

  I mean, that's a really interesting question. We know that in, in your case, it is neural networks all the way down, because that's all you have in your skull, is a bunch of neurons doing their thing, right? But if you ask the question more generally, what, what algorithms are your brain, is your brain, are being used in your brain? I think it's super interesting to compare. I think we've gotten a little bit backwards historically, because we humans first discovered Good old fashioned AI, the logic based AI that we often called GoFi for good old fashioned AI. And then more recently, we did machine learning because it required bigger computers. So we had to discover it later.

• 28:41Max Tegmark?

  So we think of machine learning with neural networks as the modern thing and the logic based AI as the old fashioned thing. But if you look at evolution on Earth, right, it's actually been the other way around. I would, I would say that, for example, an eagle has a better vision system than I have using. And dogs are just as good at casting tennis balls as I am. All this stuff which is done by training in neural network and not interpreting it in words, you know, is something so many of our animal friends can do, at least as well as us, right? What is it that we humans can do that the chipmunks and the eagles cannot?

• 29:24Max Tegmark?

  It's more to do with this logic based stuff, right, where we can extract out information in symbols in language and now even with equations, if you're a scientist, right? So basically what happened was first we built these computers that could multiply numbers real fast and manipulate symbols. And we felt they were pretty dumb. And that, and then we made neural networks that can see as well as a cat can and do a lot of this inscrutable black box neural networks. What we humans can do also is put the two together in a useful way. Yes. So artificial. In our own brain. Yes, in our own brain. So if we ever want to get artificial general intelligence that can do all jobs as well as humans can, right?

• 30:10Max Tegmark?

  Then that's what's going to be required to be able to combine the neural networks with, with symbolic.

• 30:18Max Tegmark?

  Combine the old AI with the new AI in a good way. We do it in our brains. And there seems to be basically two strategies I see in industry now. One scares the heebie jeebies out of me and the other one I find much more encouraging.

• 30:31Lex Fridman?

  Okay, which one? Can we break them apart? Which of the two?

• 30:35Max Tegmark?

  The one that scares the heebie jeebies out of me is this attitude that we're just gonna make ever bigger systems that we still don't understand until they can be as smart as humans. What could possibly go wrong? I think it's just such a reckless thing to do. And unfortunately, and if we actually succeed as a species to build artificial general intelligence and we still have no clue how it works, I think at least 50% chance we're gonna be extinct before too long. It's just gonna be an utter epic own goal.

• 31:06Lex Fridman?

  It's that 44 minute losing money problem or like the paperclip problem like where we don't understand how it works and it's just in a matter of seconds runs away in some kind of direction that's going to be very problematic.

• 31:20Max Tegmark?

  Even long before you have to worry about the machines themselves somehow deciding to do things and to us that we have to worry about people using machines that are short of AI, AGI and power to do bad things. I mean, just take a moment. And if anyone who's not worried particularly about advanced AI, just take 10 seconds and just think about your least favorite leader on the planet right now. Don't tell me who it is. I want to keep this apolitical, but just see the face in front of you, that person for 10 seconds. Now imagine that that person has this incredibly powerful AI under their control and can use it to impose their will on the whole planet. How does that make you feel?

• 32:08Lex Fridman?

  Yeah. So the, can we break that apart just briefly? For the 50% chance that we'll run into trouble with this approach, do you see the bigger worry in that leader or humans using the system to do damage? Or are you more worried? And I think I'm in this camp, more worried about like accidental unintentional destruction of everything. So like humans trying to do good and like. In a way where everyone agrees it's kind of good. It's just they're trying to do good without understanding. Because I think every evil leader in history thought they're, to some degree, thought they're trying to do good.

• 32:51Max Tegmark?

  Oh, yeah, I'm sure Hitler thought he was doing.

• 32:52Lex Fridman?

  Doing good, yeah.

• 32:54Max Tegmark?

  He was trying to do good, too.

• 32:55Lex Fridman?

  I've been reading a lot about Stalin. I'm sure Stalin is from, he legitimately thought that communism was good for the world and that he was doing good.

• 33:03Max Tegmark?

  I think Mao Zedong thought what he was doing with the Great Leap Forward was good, too. Yeah. I'm actually concerned about both of those. Before, I promised to answer this in detail, but before we do that, let me finish answering the first question. Because I told you that there were two different routes. We could get to artificial general intelligence and one scares the hippies out of me. Which is this one where we build something, we just say bigger neural networks, ever more hardware and just train the heck out of more data. And poof, now it's very powerful. That, I think, is the most unsafe and reckless approach. The alternative to that is the intelligent, intelligible intelligence approach instead.

• 33:43Max Tegmark?

  Where we say neural networks is just a tool to this, like for the first step to get the intuition. But then we're going to spend also serious researches, sources on other AI techniques for demystifying this black box and figuring out what's it actually doing. So we can convert it into something that's equally intelligent, but that we actually understand what it's doing. Maybe we can even prove theorems about it, that this car here will never be hacked when it's driving. Because here is the proof.

• 34:19Max Tegmark?

  There is a whole science of this. It doesn't work for neural networks that are big black boxes, but it works well in certain other kinds of codes, right?

• 34:28Max Tegmark?

  That approach, I think, is much more promising. That's exactly why I'm working on it, frankly. Not just because I think it's cool for science, but because I think the more we understand these systems, the better the chances that we can make them do the things that are good for us, that are actually intended, not unintended.

• 34:47Lex Fridman?

  So you think it's possible to prove things about something as complicated as a neural network? That's the hope?

• 34:54Max Tegmark?

  Well, ideally, there's no reason it has to be a neural network in the end either, right? We discovered Newton's laws of gravity with neural network in Newton's head.

• 35:04Lex Fridman?

  Yes.

• 35:05Max Tegmark?

  But that's not the way it's programmed into the navigation system of Elon Musk's rocket anymore.

• 35:11Lex Fridman?

  Right.

• 35:12Max Tegmark?

  It's written in C++ or I don't know what language he uses exactly.

• 35:16Lex Fridman?

  Yeah.

• 35:17Max Tegmark?

  And then there are software tools called symbolic verification. DARPA and the US military has done a lot of really great research on this because they really want to understand that when they build weapon systems, they don't just go fire at random or malfunction, right? And there's even a whole operating system called Cell 3 that's been developed by a DARPA grant where you can actually mathematically prove that this thing can never be hacked.

• 35:43Lex Fridman?

  Wow.

• 35:44Max Tegmark?

  One day, I hope, that will be something you can say about the OS that's running on our laptops too. As you know, we're not there, but I think we should be ambitious, frankly.

• 35:55Lex Fridman?

  Yeah.

• 35:56Max Tegmark?

  And if we can use machine learning to help do the proofs and so on as well, right, then it's much easier to verify that a proof is correct than to come up with a proof in the first place. That's really the core idea here. If someone comes on your podcast and says they proved the Riemann hypothesis or some new sensational new theorem, it's much easier for someone else, take some smart grad math grad students to check, oh, there's an error here on equation five, or this really checks out than it was to discover the proof.

• 36:31Lex Fridman?

  Yeah, although some of those proofs are pretty complicated, but yes, it's still nevertheless much easier to verify the proof. I love the optimism. You know, we kind of, even with the security of systems, there's a kind of cynicism. That pervades people who think about this, which is like, oh, it's hopeless. I mean, in the same sense, exactly like you're saying when you're in networks, oh, it's hopeless to understand what's happening. With security, people are just like, well, it's always going, there's always going to be attack vectors, like ways, ways to attack the system. But you're right, we're just very new with these computational systems. We're new with these intelligent systems.

• 37:11Lex Fridman?

  And it's not out of the realm of possibility, just like people didn't understand the movement of the stars and the planets and so on.

• 37:19Max Tegmark?

  Yeah.

• 37:19Lex Fridman?

  It's entirely possible that like, within, hopefully soon, but it could be within a hundred years.

• 37:25Max Tegmark?

  Yeah.

• 37:25Lex Fridman?

  We start to have an obvious like laws of gravity about intelligence.

• 37:30Max Tegmark?

  Yeah.

• 37:31Lex Fridman?

  And God forbid about consciousness too, that that one is.

• 37:36Max Tegmark?

  Agreed, you know, I think, of course, if you're selling computers that get hacked a lot, that's in your interest as a company that people think it's impossible to make it safe. So, you know, but he's going to get the idea of suing you, but I want to really inject optimism here. It, there, it's, it's absolutely possible to do much better than we're doing now. And, you know, your laptop does so much stuff. You don't need the music player to be super safe in your, in your future self-driving car, right? If someone hacks it and starts playing music you don't like, the world won't end. But what you can do is you can break out and say, the drive computer that controls your safety

• 38:18Max Tegmark?

  must be completely physically decoupled entirely from the entertainment system. And it must physically be such that it can't take on over the air updates while you're driving. And it can be, it can have, it's not that, it can have ultimately a sort of some operating system on it, which is symbolically verified and proven. That, that it's always going to do what it's going to, what it's supposed to do, right? We can basically have, and companies should take that attitude too. They should look at everything they do and say, what are the few systems in our, in our company? The threat in the whole life of the company if they get hacked, you know, and have the highest standards for them. And then they can save money by going for the El Chepo poorly understood stuff for the rest, you know?

• 39:02Max Tegmark?

  This, this is very feasible, I think. And coming back to. The bigger question that you worried about that that there'll be unintentional failures, I think there are two quite separate risks here, right? We talked a lot about one of them, which is that the goals are noble of the human. The human says, I want this airplane to not crash because this is not Mohammed Atta now flying the airplane, right? And now there's this technical challenge of making sure that the autopilot is actually going to behave as the pilot wants. If you set that aside, there's also the separate question. How do you make sure that the goals of the pilot are actually aligned with the goals of the passenger?

• 39:45Max Tegmark?

  How do you make sure very much more broadly that if we can all agree as a species that we would like things to kind of go well for humanity as a whole, that the goals are aligned here? The alignment problem. And yeah, there's been a lot of progress in the sense that there's suddenly huge amounts of research going on about it. I'm very grateful to Elon Musk for giving us that money five years ago so we could launch the first research program on technical AI safety and alignment. There's a lot of stuff happening. But I think we need to do more than just make sure little machines do always what their owners do. You know, that wouldn't have prevented September 11.

• 40:25Max Tegmark?

  If Mohammed Atta said, okay, okay, autopilot, please fly into World Trade Center, you know, and it's like, okay. That even happened. In a different situation, there was this depressed pilot named Andreas Lubitz, right? He told his German Wings passenger jet to fly into the Alps. He just told the computer to change the altitude to 100 meters or something like that. And you know what the computer said? Right. Okay. Okay. And it had the frigging topographical map of the Alps in there. It had GPS, everything. No one had bothered teaching it even the basic kindergarten ethics of like, no, we never want airplanes to fly into mountains under any circumstances. And so we have to think beyond just the

• 41:13Max Tegmark?

  The technical issues, I'm thinking about how do we align in general incentives on this planet for the greater good. So, starting with simple stuff like that, every airplane that has a computer in it should be taught whatever kindergarten ethics it's smart enough to understand, like, no, don't fly into fixed objects if the pilot tells you to do so, then go on autopilot mode, send an email to the cops and land at the latest airport, nearest airport, you know. Any car with a forward-facing camera should just be programmed by the manufacturer so that it will never accelerate into a human ever. That would avoid things like the Nice attack and many horrible terrorist vehicle attacks where

• 41:58Max Tegmark?

  they deliberately did that, right? This was not some sort of thing, oh, you know, US and China, different views on, no, there was not a single car manufacturer in the world, right, who wanted the cars to do this. They just hadn't thought to do the alignment. And if you look at more broadly, problems that happen on this planet, the vast majority have to do a poor alignment. I mean, think about, let's go back really big, because I know you're so good at that. Let's go big, yeah. Yeah. So, long ago in evolution, we had these genes, and they wanted to make copies of themselves. That's really all they cared about. So, some genes said, hey, I'm gonna

• 42:39Max Tegmark?

  build a brain on this body I'm in so that I can get better at making copies of myself. And then they decided, for their benefit, to get copied more, to align your brain's incentives with their incentives. So, it didn't want you to starve to death, so it gave you an incentive to eat. And it wanted you to make copies of the genes. So, it gave you incentive to fall in love and do also naughty things to make copies of itself, right? So, that was successful value alignment done on the genes. They created something more intelligent than themselves, but they made sure to try to align the values. But then

• 43:19Max Tegmark?

  something went a little bit wrong, against the idea of what the genes wanted, because a lot of humans discovered, hey, you know, yeah, we really like this business about sex that the genes have made us enjoy, but we don't want to have babies right now. So, we're gonna hack the genes and use birth control. And I really feel

• 43:42Max Tegmark?

  Like drinking Coca-Cola right now, but I don't wanna get a potbelly, so I'm gonna drink Diet Coke. Yeah. We have all these things, we've figured out, because we're smarter than the genes, how we can actually subvert their intentions. So it's not surprising that we humans now, when we're in the role of these genes, creating other non-human entities with a lot of power, have to face the same exact challenge. How do we make other powerful entities have incentives that are aligned with ours? And that so they won't hack them. Corporations, for example, right? We humans decided to create corporations because it can benefit us greatly. Now, all of a sudden, there's a supermarket, I can go buy food there, I don't have to hunt. Awesome.

• 44:25Max Tegmark?

  And then to make sure that this corporation would do things that were good for us and not bad for us, we created institutions to keep them in check. Like, if the local supermarket sells poisonous food, then those, some, the owners of a supermarket have to spend some years reflecting behind bars, right? So we created incentives to align them. But of course, just like we were able to see through this thing, you, the birth control, if you're a powerful corporation, you also have an incentive to try to hack the institutions that are supposed to govern you. Because you ultimately, as a corporation, have an incentive to maximize your profits. It's like you have an incentive to maximize the enjoyment your brain has, not your genes.

• 45:11Max Tegmark?

  So if they can figure out a way of bribing regulators, then they're gonna do that. In the US, we kind of caught on to that and made laws against corruption and bribery.

• 45:24Max Tegmark?

  Then, in the late 1800s, Teddy Roosevelt realized that, no, we were still being kind of hacked because the Massachusetts railroad companies had like a bigger budget than the state of Massachusetts, and they were doing a lot of very corrupt stuff. So he did the whole trust busting thing to try to align these other non-human entities, the companies, again, more with the incentives of Americans as a whole. And it's not surprising, though, that, you know, this is a battle you have to keep fighting. Now, we have even larger companies than we ever had before. And of course, they're gonna try to, again, subvert the institutions, not because, you know, I think people make the mistake of getting all too...

• 46:10Max Tegmark?

  Thinking about things in terms of good and evil, like arguing about whether corporations are good or evil, or whether robots are good or evil. A robot isn't good or evil. It's a tool and you can use it for great things, like robotic surgery or for bad things. And a corporation also is a tool, of course. And if you have good incentives to the corporation, it'll do great things, like start a hospital or a grocery store. If you have any bad incentives, then it's going to start maybe at marketing addictive drugs to people and you'll have an opioid epidemic, right? It's all about, I don't want, we should, we not make the mistake of getting into some sort of fairy tale,

• 46:52Max Tegmark?

  good evil thing about corporations or robots. We should focus on putting the right incentives in place. My optimistic vision is that if we can do that, you know, then we can really get good things. We're not doing so great with that right now, either on AI, I think, or on other intelligent, non-human entities, like big companies, right? We just have a new Secretary of Defense who's going to start up now in the Biden administration, who is, was an active member of the board of Raytheon, for example.

• 47:24Lex Fridman?

  Yeah.

• 47:24Max Tegmark?

  So, you know, I have nothing against Raytheon. I'm not a pacifist, but there's an obvious conflict of interest. If someone is in a job where they decide who's they're going to contract with. And I think somehow we have, maybe we need another Teddy Roosevelt to come along again and say, hey, you know, we want what's good for all Americans and we need to go do some serious realigning again of the incentives that we're giving to these big companies. And then we're going to be better off.

• 47:59Lex Fridman?

  It seems that naturally with human beings, just like you beautifully described the history of this whole thing, of it all started with the genes and they're probably pretty upset by all the unintended consequences that have happened since. But the, it seems that it kind of works out, like it's in this collective intelligence that emerges at the different levels. It seems to find. Sometimes last minute, a way to realign the values or keep the values aligned. It's almost, it finds a way, like different leaders, different humans pop up all over the place that reset the system. Do you, one, I mean, do you have an explanation why that is? Or is that just survivor bias?

• 48:42Lex Fridman?

  And also, is that different, somehow fundamentally different than with AI systems? Where you're no longer dealing with something that was a direct, maybe companies are the same, a direct byproduct of the evolutionary process?

• 48:58Max Tegmark?

  I think there is one thing which has changed. That's why I'm not all optimistic. That's why I think there's about a 50% chance if we, if we take the dumb route with artificial intelligence, that we, humanity will be extinct in this century. First, just the big picture. Yeah, companies need to have right incentives. Even governments, right? We, we used to have governments, usually there were just some king, you know, who was, was the king because his dad was the king, you know? And, and then there were some benefits of having this powerful kingdom because, or empire of any sort, because then it could prevent a lot of local squabbles.

• 49:43Max Tegmark?

  So at least everybody in that region would stop warring against each other and their incentives of different cities in the kingdom became more aligned, right? That's, that was the whole selling point. Harari.

• 49:53Lex Fridman?

  Yeah.

• 49:54Max Tegmark?

  No, well, Harari has a beautiful piece on how empires were collaboration enablers. And then we also, Harari says invented money for that reason, so we could have better alignment and we could do trade even with people we didn't know. So this sort of stuff has been playing out since time immemorial, right? What's changed is that it happens on ever larger scales, right? Technology keeps getting better because science gets better. So now we can communicate over larger distances, transport things fast over larger distances. And so the entities get ever bigger, but our planet is not getting bigger anymore. So in the past, you could have one experiment that just totally screwed up, like Easter

• 50:35Max Tegmark?

  Island, where they actually managed to have such poor alignment that when they went extinct, people there, there was no one else to come back and replace them, right?

• 50:47Max Tegmark?

  If Elon Musk doesn't get us to Mars and then we go extinct on a global scale and we're not coming back, that's the fundamental difference. And that's a mistake I'd rather we don't make for that reason. In the past, of course, history is full of fiascos, but it was never the whole planet. And then, okay, now there's this nice uninhabited land here, some other people could move in and organize things better. This is different. The second thing, which is also different, is that technology gives us so much more empowerment, both to do good things and also to screw up. In the Stone Age, even if you had someone whose goals were really poorly aligned, like

• 51:30Max Tegmark?

  maybe he was really pissed off because his Stone Age girlfriend dumped him and he just wanted to, if he wanted to like kill as many people as he could. How many could he really take out with a rock and a stick before he was overpowered, right? Just handful, right? Now, with today's technology, if we have an accidental nuclear war between Russia and the US, which we almost have about a dozen times, and then we have a nuclear winter, it could take out seven billion people or six billion people, we don't know. So the scale of damage is bigger that we can do. And if, there's obviously no law of physics that says that technology will never get

• 52:12Max Tegmark?

  powerful enough that we could wipe out our species entirely. That would just be fantasy to think that science is somehow doomed not get more powerful than that, right? And it's not at all unfeasible in our lifetime that someone could design a designer pandemic, which spreads as easily as COVID, but just basically kills everybody. We already had smallpox, it killed one third of everybody who got it.

• 52:37Lex Fridman?

  What do you think of the, here's an intuition, maybe it's completely naive and this optimistic intuition I have, which it seems, and maybe it's a biased experience that I have, but it seems like the most brilliant people I've met in my life all are really fundamentally good human beings. And not like naive good, like they really want to do good for the world in a way that well, maybe is aligned to my sense of what good means. And so I have a sense that the

• 53:12Lex Fridman?

  The people that will be defining the very cutting edge of technology, there will be much more of the ones that are doing good versus the ones that are doing evil. So the race, I'm optimistic on the us always like last minute coming up with a solution. So if there's an engineered pandemic that has the capability to destroy most of the human civilization, it feels like to me either leading up to that before or as it's going on, there will be, we're able to rally the collective genius of the human species. I could tell by your smile that you're at least some percentage doubtful.

• 53:55Lex Fridman?

  But is that, could that be a fundamental law of human nature? That evolution only creates, like karma is beneficial, good is beneficial and therefore will be all right.

• 54:09Max Tegmark?

  I hope you're right. I would really would love it if you're right, if there's some sort of law of nature that says that we always get lucky in the last second because of karma. But, you know, I prefer, I prefer not playing it so close and gambling on that. And I think, in fact, I think it can be dangerous to have too strong faith in that. Because it makes us complacent. Like if someone tells you, you never have to worry about your house burning down, then you're not going to put in a smoke detector because why would you need to, right? Even if it's sometimes very simple precautions, we don't take them. If we're like, oh, the government is going to take care of everything for us. I can always trust my politicians, I can always, we advocate our own responsibility.

• 54:54Max Tegmark?

  I think it's a healthier attitude to say, yeah, maybe things will work out. Maybe I'm actually going to have to myself step up and take responsibility.

• 55:03Max Tegmark?

  And the stakes are so huge. I mean, if we do this right. We can develop all this ever more powerful technology and cure all diseases and create a future where humanity is healthy and wealthy for not just the next election cycle, but like billions of years throughout our universe. That's really worth working hard for and not just, you know, sitting and hoping for some sort of fairy tale karma.

• 55:25Lex Fridman?

  Well, I just mean, so you're absolutely right. From the perspective of the individual, like for me, like the primary thing should be to take responsibility and to build the solutions that your skill set allows.

• 55:37Max Tegmark?

  Yeah, which is a lot. I think we underestimate often very much how much good we can do. If you or anyone listening to this is completely confident that our government would do a perfect job on handling any future crisis with engineered pandemics or future AI.

• 55:55Lex Fridman?

  The one or two people out there.

• 55:57Max Tegmark?

  On what actually happened in 2020. Do you feel that the government by and large around the world has handled this flawlessly?

• 56:07Lex Fridman?

  That's a really sad and disappointing reality that hopefully is a wake up call for everybody, for the scientists, for the for the for the engineers, for the researchers in AI especially. It was disappointing to see how inefficient we were at spreading, collecting the right amount of data in a privacy preserving way and spreading that data and utilizing that data to make decisions, all that kind of stuff.

• 56:36Max Tegmark?

  Yeah, I think when something bad happens to me, I made myself a promise many years ago that I would not be a whiner. So when something bad happens to me, of course, it's to process the disappointment. But then I try to focus on what did I learn from this that can make me a better person in the future. And there's usually something to be learned when I fail. And I think we should all ask ourselves, what can we learn from the pandemic about how we can do better in the future? And you mentioned there's a really good lesson. You know, we were not as resilient as we thought we were, and we were not as prepared,

• 57:17Max Tegmark?

  maybe, as we wish we were. You can even see very stark contrast around the planet. South Korea, they have over 50 million people. Do you know how many deaths they have from COVID last time I checked?

• 57:29Lex Fridman?

  No.

• 57:30Max Tegmark?

  About 500.

• 57:34Max Tegmark?

  Why is that? Well,

• 57:38Max Tegmark?

  the short answer is that they had prepared.

• 57:42Max Tegmark?

  They were incredibly quick, incredibly quick to get on it with very rapid testing and contact tracing and so on, which is why they never had more cases than they could contract trace effectively, right? They never even had to have the kind of big lockdowns we had in the West. But the deeper answer to it, it's not just the Koreans are just some better people. The reason I think they were better prepared was because they had already had a pretty bad hit from the SARS pandemic, or which never became a pandemic, something like 17 years ago, I think. So it's kind of fresh memory that, you know, we need to be prepared for pandemics. So they were, right?

• 58:23Max Tegmark?

  And so maybe this is a lesson here for all of us to draw from COVID that rather than just wait for the next pandemic or the next problem with AI getting out of control or anything else, maybe we should just actually set aside a tiny fraction of our GDP to have people very systematically do some horizon scanning and say, okay, what are the things that could go wrong? And let's duke it out and see which are the more likely ones and which are the ones that are actually actionable? And then be prepared.

• 58:57Lex Fridman?

  So one of the observations as one little ant slash human that I am of disappointment is the political division over information that has been observed, that I observed this year, that it seemed the discussion was less about

• 59:19Lex Fridman?

  sort of what happened and understanding what happened deeply and more about there's different truths out there. And it's like an argument, my truth is better than your truth. And it's, it's like red versus blue or different like it was like this ridiculous discourse that doesn't seem to get at any kind of notion of the truth. It's not like some kind of scientific process. Even science got politicized in ways that's very heartbreaking to me. You have an exciting project on the AI front of trying to.

• 59:56Lex Fridman?

  Rethink, you mentioned corporations. There's one of the other collective intelligence systems that have emerged through all of this is social networks and just the spread, the internet is the spread of information on the internet, our ability to share that information. There's all different kinds of news sources and so on. And so you said, like, that's from first principles. Let's rethink how we think about the news, how we think about information. Can you talk about this amazing effort that you're undertaking?

• 1:00:29Max Tegmark?

  Oh, I'd love to. This has been my big COVID project, spent nights and weekends on ever since the lockdown. To segue into this, actually, let me come back to what you said earlier, that you had this hope that in your experience, people who you felt were very talented, were often idealistic and wanted to do good. Frankly, I feel the same about all people, by and large. There are always exceptions, but I think the vast majority of everybody, regardless of education and whatnot, really are fundamentally good, right? So how can it be that people still do so much nasty stuff, right? I think it has everything to do with this, with the information that we're given.

• 1:01:08Lex Fridman?

  Yes.

• 1:01:08Max Tegmark?

  You know, if you go into Sweden 500 years ago and you start telling all the farmers that those Danes in Denmark, they're so terrible people, you know, and we have to invade them.

• 1:01:19Lex Fridman?

  Yes.

• 1:01:19Max Tegmark?

  Because they've done all these terrible things that you can't fact check yourself. A lot of people, Swedes did that, right? And we've seen, we're seeing so much of this today in the world, both geopolitically, you know, where we are told that China is bad and Russia is bad and Venezuela is bad and people in those countries are often told that we are bad. And we also see it at a micro level, you know, where people are told that, oh, those who voted for the other party are bad people. It's not just an intellectual disagreement, but they're Bad people and we're getting ever more divided.

• 1:01:59Max Tegmark?

  And so how do you reconcile this with this intrinsic goodness in people? I think it's pretty obvious that it has, again, to do with this with the information that we're fed and given. Right? We evolved to live in small groups where you might know 30 people in total. Right? So you then had a system that was quite good for assessing who you could trust and who you could not. And if someone told you that, you know, Joe there is a jerk, but you had interacted with him yourself and seen him in action. And you would quickly realize maybe that that's actually not quite accurate. Right? But now that we the most people on the planet are people we've never met. It's very important that we have a way of trusting the information we're given.

• 1:02:44Max Tegmark?

  And so, OK, so where does the news project come in? Well, throughout history, you can go read Machiavelli, you know, from the 1400s and you'll see how already then they were busy manipulating people with propaganda and stuff. Propaganda is not new at all. And the incentives to manipulate people is just not new at all. What is it that's new? What's new is machine learning meets propaganda. That's what's new. That's why this has gotten so much worse. You know, some people like to blame certain individuals, like in my liberal university bubble. Many people blame Donald Trump and say it was his fault. I see it differently.

• 1:03:25Max Tegmark?

  I think Donald Trump just had this extreme skill at playing this game in the machine learning algorithm age. A game he couldn't have played 10 years ago. So what's changed? What's changed is, well, Facebook and Google and other companies. And I don't want, I'm not badmouthing them. I have a lot of friends who work for these companies, good people. They deployed machine learning algorithms, just increased their profit a little bit to just maximize the time people spent watching ads. And they had totally underestimated how effective they were going to be. This was, again, the black box, non-intelligible intelligence.

• 1:04:05Max Tegmark?

  They just noticed, oh, we're getting more ad revenue. Great. It took a long time until they even realized why and how and how damaging this was for society. Because of course, what the machine learning figured out was that the by far most effective way of gluing you to your little rectangle was to show you things that triggered strong emotions, anger, et cetera, resentment. And if it was true or not, didn't really matter. It was also easier to find stories that weren't true. If you weren't limited, that's just the limitation to show people.

• 1:04:38Lex Fridman?

  That's a very limiting factor.

• 1:04:40Max Tegmark?

  And before long, we got these amazing filter bubbles on a scale we had never seen before. Coupled this to the fact that also the online news media were so effective that they killed a lot of print journalism. There's only, there's less than half as many journalists now in America, I believe, as there was, you know, a generation ago. You just couldn't compete with the online advertising. So all of a sudden, most people are not getting, even reading newspapers. They get, get their news from social media. And most people only get news in their little bubble.

• 1:05:20Max Tegmark?

  And so along comes now some people like Donald Trump, who figured out, among the first successful politicians to figure out how to really play this new game and become very, very influential. But I think Donald Trump was a simp, well, he, he took advantage of it. He didn't create, the fundamental conditions were created by machine learning to taking over the news media. So this is what motivated my little COVID project here. So, you know, I said before, machine learning and tech in general, it's not evil, but it's also not good. It's just a tool that you can use for good things or bad things. And as it happens, machine learning in news is mainly used by the big players, big tech,

• 1:06:05Max Tegmark?

  to manipulate people into watch as many ads as possible, which had this unintended consequence of really screwing up our democracy and fragmenting it into filter bubbles. So I thought, well, machine learning algorithms were basically free. They can run on your smartphone for free also if someone gives them away to you, right? There's no reason why they only have to help the big guy.

• 1:06:27Max Tegmark?

  To manipulate the little guy, they can just as well help the little guy to see through all the manipulation attempts from the big guy. So did this project, it's called, you can go to improvethenews.org. The first thing we've built is that this is a little news aggregator, looks a bit like Google News, except it has these sliders on it to help you break out of your filter bubble. So if you're reading, you can click, click and go to your favorite topic. And then if you just slide the left, right slider all the way over to the left.

• 1:06:58Lex Fridman?

  There's two sliders, right?

• 1:06:59Max Tegmark?

  Yeah, there's the one, the most obvious one is the one that has left, right labeled on it. You go to left, you get one set of articles, you go to the right, you see a very different truth.

• 1:07:08Lex Fridman?

  Yeah.

• 1:07:08Max Tegmark?

  Appearing.

• 1:07:09Lex Fridman?

  Well, that's literally left and right on the.

• 1:07:12Max Tegmark?

  Political spectrum.

• 1:07:13Lex Fridman?

  On the political.

• 1:07:13Max Tegmark?

  Yeah. So if you're reading about immigration, for example, it's very, very noticeable. And I think step one always, if you want to not get manipulated, is just to be able to recognize the techniques people use. So it's very helpful to just see how they spin things on the two sides. I think many people are under the misconception that the main problem is fake news. It's not. We, I had an amazing team of MIT students where we did an academic project, use machine learning to detect the main kinds of bias over the summer. And yes, of course, sometimes there's fake news where someone just claims something that's false, right? Like, oh, Hillary Clinton just got divorced or something.

• 1:07:58Lex Fridman?

  Yes.

• 1:07:59Max Tegmark?

  But what we see much more of is actually just omissions. If you go to, there's some stories which just won't be mentioned by the left or the right because it doesn't suit their agenda. And then they'll instead mention other ones very, very, very much. So for example, we've, we've had. A lot, a number of stories about the Trump family's financial dealings. And then there's been some, a bunch of stories about the Biden families, Hunter Biden's financial dealings, right? Surprise, surprise, they don't get equal coverage on the left and the right.

• 1:08:35Lex Fridman?

  Right.

• 1:08:35Max Tegmark?

  One side loves to cover the Biden, Hunter Biden's stuff, and one side loves to cover the Trump. You can never guess which is which, right? But the great news is if you want to, if you're a normal American citizen and you dislike corruption in all its forms, then slide, slide, you can just get, look at both of the sides and you'll, you'll see all the corrupt, those political corruption stories.

• 1:08:58Lex Fridman?

  It's really liberating to just take in the both sides, the spin on both sides. It somehow unlocks your mind to like, think on your own, to realize that, that, I don't know, it's, it's the same thing that was useful, right, in Soviet Union times for when, when everybody was much more aware that they're surrounded by propaganda, right?

• 1:09:23Max Tegmark?

  That is so interesting what you're saying, actually. So Noam Chomsky, you know, used to be our MIT colleague, once said that propaganda is to democracy what violence is to totalitarianism. And, and what he means by that is if you have a really totalitarian government, you don't need propaganda.

• 1:09:44Lex Fridman?

  Right.

• 1:09:45Max Tegmark?

  People will do what you, what you want them to do anyway, out of fear, right? But otherwise, you need propaganda. So I would say actually that the propaganda is much higher quality in democracies, much more believable. And it's really-

• 1:10:01Lex Fridman?

  Brilliant.

• 1:10:02Max Tegmark?

  It's really striking. When I talk to colleagues, science colleagues, like from Russia and China and so on, I notice they are actually much more aware of the propaganda in their own media than many of my American colleagues are about the propaganda in Western media.

• 1:10:17Lex Fridman?

  That's brilliant. That means the propaganda in the Western media is just better.

• 1:10:20Max Tegmark?

  Yes!

• 1:10:21Lex Fridman?

  That's so brilliant.

• 1:10:22Max Tegmark?

  Everything is better in the West, even the propaganda.

• 1:10:25Lex Fridman?

  Oh, man.

• 1:10:27Max Tegmark?

  But they're-

• 1:10:30Lex Fridman?

  That's good.

• 1:10:31Max Tegmark?

  But when you, when, once you realize that, you realize there's also something very optimistic there that you can do about it, right? Because first of all, omissions, as long as there's no outright censorship, you can just look at both sides and pretty quickly piece together a much more accurate idea of what's actually going on, right?

• 1:10:51Lex Fridman?

  And develop a natural skepticism, too.

• 1:10:53Max Tegmark?

  Yeah.

• 1:10:54Lex Fridman?

  Just a analytical, scientific mind about the way you're taking information.

• 1:10:58Max Tegmark?

  Yeah, and I, I think, I have to say, sometimes I feel that some of us in the academic bubble are too arrogant about this and somehow think, oh, it's just people who aren't as, oh, who's educated, the ducks are fooled, when we are often just as gullible also, you know, we read only our media and, and don't see through things. Anyone who looks at both sides like this and compares will immediately start noticing the shenanigans being pulled. And, you know, I think, what, what I tried to do with, with this app is that the big tech has the stomach stent to try to blame the individual for being manipulated, much like big tobacco tried to blame the individuals entirely for smoking.

• 1:11:39Max Tegmark?

  And, and later on, you know, our government stepped up and said, actually, you know, you can't just blame little kids for starting to smoke, we have to have more responsible advertising and this and that. I think it's a bit the same here, it's very convenient for a big tech to blame, so it's just people who are so dumb and get fooled. The blame usually comes in saying, oh, it's just human psychology, people just want to hear what they already believe. But Professor David Rand at MIT actually partly debunked that with a really nice study showing that people tend to be interested in hearing things that go against what they believe, if it's presented in a respectful way. Like, suppose, for example, that you have a company and you're just about to launch

• 1:12:24Max Tegmark?

  this project and you're convinced it's going to work, and someone says, you know, Lex?

• 1:12:29Max Tegmark?

  I hate to tell you this, but this is gonna fail. Here's why. Would you be like, shut up, I don't wanna hear it? La, la, la, la, la, la, la, la, la. Yeah. Would you? You would be interested, right? Yes. And also, i- if you're on an airplane, um, back in the co- pre-COVID times, you know, and the guy next to you is clearly from the opposite side of the political spectrum, but is very respectful and polite to you, wouldn't you be kind of interested to hear a bit about how he or she thinks about things? Of course. But it's not so easy to find out respectful disagreement now, because like, for example, if you are a Democrat and you're like, oh, I wanna see something on the other side, so you just go breitbart.com.

• 1:13:11Max Tegmark?

  And then after the first 10 seconds, you feel deeply insulted by something and they, it's, it's not gonna work. Or if you take someone who votes Republican and they go to something on the left and they just get very offended very quickly by them having put a deliberately ugly picture of Donald Trump on the front page or something, it doesn't really work. So this news aggregator also has a nuanced slider, which you can pull to the right and then to make it easier to get exposed to actually more sort of academic style or more respectful, um.

• 1:13:45Max Tegmark?

  That's brilliant. Portrayals of, of different views. And, and finally, the, the one kind of bias I think people are mostly aware of is the left-right, right? Because it's so obvious, because both left and right are very powerful here, right? Both of them have well-funded TV stations and newspapers and it's kind of hard to miss. But there's another one, the establishment slider, which is, is also really fun. I, I, I love to play with it. And that's more about corruption. Yes. Because if you have, um, the society that, where

• 1:14:20Max Tegmark?

  Almost all the powerful entities want you to believe a certain thing. That's what you're going to read in both the big media, mainstream media on the left and on the right, of course. And powerful companies can push back very hard, like tobacco companies pushed back very hard back in the day when some newspapers started writing articles about tobacco being dangerous. So it was hard to get a lot of coverage about it initially. And also, if you look geopolitically, right? Of course, in any country, when you read their media, you're mainly going to be reading a lot of articles about how our country is the good guy and the other countries are the bad guys, right? So if you want to have a really more nuanced understanding, you know, like the Germans used to be told that the, the British used to be told that the French were the bad guys

• 1:15:04Max Tegmark?

  and the French used to be told that the British were the bad guys. Now they visit each other's countries a lot and have a much more nuanced understanding. I don't think there's going to be any more wars between France and Germany. But on the geopolitical scale, it's just as much as ever, you know, big Cold War, now US-China and so on. And if you want, if you want to get a more nuanced understanding of what's happening geopolitically, then it's really fun to look at this establishment slider because it turns out there are tons of little newspapers, both on the left and on the right, who sometimes challenge establishment and say, you know, maybe we shouldn't actually invade Iraq right now. Maybe this weapons of mass destruction thing is BS.

• 1:15:45Max Tegmark?

  If you look at the journalism research afterwards, you can actually see that clearly, that both CNN and Fox were very pro, let's get rid of Saddam, there are weapons of mass destruction. Then there were a lot of smaller newspapers. They were like, wait a minute, this evidence seems a bit sketchy and maybe we, but of course, they were so hard to find. Most people didn't even know they existed, right? Yet it would have been better for American national security if those voices had also come up. I think it harmed America's national security, actually, that we invaded Iraq.

• 1:16:19Lex Fridman?

  And arguably, there's a lot more interest in that kind of thinking too, from those small sources. So like the, when you say big, it's more about kind of the reach of the broadcast.

• 1:16:33Lex Fridman?

  But it's not big in terms of the interest. I think I think there's a lot of interest in that kind of anti-establishment or like skepticism towards, you know, out of the box thinking. There's a lot of interest in that kind of thing. Do you see this news project or something like it being basically taken over the world as as the main way we consume information? Like, what's how do we get? How do we get there? Like, how do we, you know? So, OK, the idea is brilliant. It's a it's a you're calling it your little project in 2020. But how does that become the new way we consume information?

• 1:17:14Max Tegmark?

  I hope, first of all, there's the plant a little seed there because normally the big barrier of doing anything in media is you need a ton of money. But this costs no money at all. I've just been paying myself, pay a tiny amount of money each month to Amazon to run the thing in their cloud. We're not there never will never be any ads. The the point is not to make any money off of it. And we we just train machine learning algorithms to classify the articles and stuff. So it just kind of runs by itself. So if it actually gets good enough at some point that it starts catching on, it could scale. And if other people carbon copy it and make other versions that are better, that's more the more the merrier.

• 1:17:53Max Tegmark?

  I think there's a real opportunity for machine learning to empower the individual against the list out the powerful players. It's, as I said in the beginning here, it's been mostly the other way around so far that the big players have the AI and then they tell people this is the truth. This is how it is. But it can just as well go the other way around. And when the internet was born, actually, a lot of people had this hope that maybe this will be a great thing for democracy, make it easier to find out about things. And maybe machine learning and things like this can can actually help again. And I have to say, I think it's it's more important than ever now, right? Because This is very linked also to the whole future of life, as we discussed earlier.

• 1:18:39Max Tegmark?

  Right, we're getting this ever more powerful tech, you know. Frank, it's pretty clear if you look on the one or two generation, three generation time scale that there are only two ways this can end geopolitically.

• 1:18:50Lex Fridman?

  Yeah.

• 1:18:50Max Tegmark?

  Either it ends great for all of humanity, or it ends terribly for all of us. There's really no in-between. And we're so stuck in that because, you know, technology knows no borders. And you can't have people fighting when the weapons just keep getting ever more powerful indefinitely. Eventually, luck, the luck runs out. And, you know, right now, we have, I love America, but the fact of the matter is, what's good for America is not opposite in the long term to what's good for other countries. It would be if this was some sort of zero-sum game like it was thousands of years ago,

• 1:19:35Max Tegmark?

  when the only way one country could get more resources was to take land from other countries, because that was basically the resource, right? Look at the map of Europe, some countries kept getting bigger and smaller, endless wars. But then, since 1945, there hasn't been any war in Western Europe, and they all got way richer because of tech. So the optimistic outcome is that the big winner in this century is going to be America and China and Russia and everybody else, because technology just makes us all healthier and wealthier, and we just find some way of keeping the peace on this planet.

• 1:20:12Max Tegmark?

  But I think unfortunately, there are some pretty powerful forces right now that are pushing in exactly the opposite direction and trying to demonize other countries, which just makes it more likely that this ever more powerful tech we're building is gonna use disastrous ways.

• 1:20:27Lex Fridman?

  Yeah, for aggression versus cooperation, that kind of thing.

• 1:20:30Max Tegmark?

  Yeah, even look at, look at this military AI now, right? 2020, it was so awesome to see these dancing robots. I loved it, right? But one of the biggest growth areas in robotics now is, of course, autonomous weapons. And 2020 was like the best marketing year ever for autonomous weapons, because in both Libya, civil war, and in Gornokarabakh.

• 1:20:56Max Tegmark?

  They made the decisive difference, right? And everybody else is like watching this, oh yeah, we want to build autonomous weapons too. In Libya, you had, on one hand, our ally, the United Arab Emirates, that were flying their autonomous weapons that they bought from China, bombing Libyans. And on the other side, you had our other ally, Turkey, flying their drones. And they had no skin in the game, any of these other countries. And of course, it was the Libyans who really got screwed. In Nagorno-Karabakh, you had, actually, again, now Turkey is sending drones built by this company

• 1:21:37Max Tegmark?

  that was actually founded by a guy who went to MIT AeroAstro, do you know that?

• 1:21:43Lex Fridman?

  No.

• 1:21:43Max Tegmark?

  Bakr al-Rahim, yeah. So MIT has a direct responsibility for ultimately this. And a lot of civilians were killed there, you know. And so because it was militarily so effective, now suddenly there's like a huge push, oh yeah, yeah, let's go build ever more autonomy into these weapons and it's gonna be great. And I think actually, people who are obsessed about some sort of future Terminator scenario right now should start focusing on the fact that we have two much more urgent threats happening from machine learning. One of them is the whole destruction of democracy that we've talked about now,

• 1:22:24Max Tegmark?

  where our flow of information is being manipulated by machine learning. And the other one is that right now, you know, this is the year when the big arms race in out of control arms race in autonomous weapons is gonna start or it's gonna stop.

• 1:22:40Lex Fridman?

  So you have a sense that there is, like, 2020 was an instrumental catalyst for the race of, for the autonomous weapons race?

• 1:22:49Max Tegmark?

  Yeah, because it was the first year when they proved decisive in the battlefield. And these ones are still not fully autonomous, mostly they're remote controlled, right? But, you know, we could very quickly make things about, you know, the size and cost of a smartphone, which you just put in the GPS coordinates or the face of the one you want to kill, a skin color or whatever, and it flies away and, you know, does it? The real good reason why the US and all the other superpowers should put the kibosh on this is the same reason we decided to put the kibosh on bioweapons. So, you know, we gave the Future of Life award that we can talk more about later.

• 1:23:31Max Tegmark?

  Matthew Messelson from Harvard before for convincing Nixon to ban bioweapons. And I asked him, how did you do it? And he was like, well, I just said, look, we don't want there to be a $500 weapon of mass destruction that even all our enemies can afford, even non-state actors. And Nixon was like, good point. You know, it's in America's interest that the powerful weapons are all really expensive. So only we can afford them, or maybe some more stable adversaries, right? Nuclear weapons are like that. But bioweapons were not like that. That's why we banned them. And that's why you never hear about them now. That's why we love biology.

• 1:24:15Lex Fridman?

  So you have a sense that it's possible for the big powerhouses, in terms of the big nations in the world, to agree that autonomous weapons is not a race we want to be on? That it doesn't end well?

• 1:24:28Max Tegmark?

  Yeah, because we know it's just going to end in mass proliferation. And every terrorist everywhere is going to have these super cheap weapons that they will use against us. And our politicians have to constantly worry about being assassinated every time they go outdoors by some anonymous little mini drone, you know? We don't want that. And if, even if the US and China and everyone else could just agree that you can only build these weapons if they cost at least 10 million bucks, that would be a huge win for the superpowers and frankly, for everybody. The, you don't, and people often push back and say, well, it's so hard to prevent cheating. But hey, you could say the same about bioweapons, you know?

• 1:25:11Max Tegmark?

  Take any of your, our MIT colleagues in biology, of course, they could build some nasty bioweapon if they really wanted to. But first of all, they don't want to because they think it's disgusting because of the stigma. And second,

• 1:25:25Max Tegmark?

  Even if there's some sort of nutcase and want to, it's very likely that some of their grad students or someone would rat them out because everyone else thinks it's so disgusting, right? And in fact, we now know there was even a fair bit of cheating on the bioweapons ban. But none, no countries used them because it was so stigmatized that it just wasn't worth revealing that they had cheated.

• 1:25:47Lex Fridman?

  You talk about drones, but you kind of think that drones is like remote operation.

• 1:25:54Max Tegmark?

  Which they are mostly still.

• 1:25:56Lex Fridman?

  But you're not taking the next intellectual step of like, where does this go? You're kind of saying the problem with drones is that you're removing yourself from direct violence. Therefore, you're not able to sort of maintain the common humanity required to make the proper decisions strategically. But that's the criticism as opposed to like, if this is automated and just exactly as you said, if you automate it and there's a race, then you're going to the technology can get better and better and better, which means getting cheaper and cheaper and cheaper.

• 1:26:28Max Tegmark?

  Yeah.

• 1:26:29Lex Fridman?

  And unlike perhaps nuclear weapons, which is connected to resources in a way like it's hard to get the, it's hard to engineer, yeah. It feels like it's, you know, there's too much overlap between the tech industry and autonomous weapons to where you could have smartphone type of cheapness. If you look at drones, you know, it's a, it's a, you know, for a thousand dollars, you can have an incredible system that's able to maintain flight autonomously for you and take pictures and stuff. You could see that going into the autonomous weapon space that's, but like, why is that not thought about or discussed enough in the public, do you think?

• 1:27:11Lex Fridman?

  You see those dancing Boston Dynamics robots and everybody has this kind of,

• 1:27:17Lex Fridman?

  Like as if this is like a far future.

• 1:27:20Max Tegmark?

  Yeah.

• 1:27:20Lex Fridman?

  They have this like fear like, oh, this will be Terminator in like some, I don't know, unspecified twenty, thirty, forty years. And they don't think about, well, this is like some much less dramatic version of that is actually happening now. It's not gonna have, it's not gonna be legged, it's not gonna be dancing, but it's, it's already has the capability to use artificial intelligence to kill humans.

• 1:27:45Max Tegmark?

  Yeah, the Boston Dynamics leg robots, I think the reason we imagine them holding guns is just because you've all seen Arnold Schwarzenegger.

• 1:27:52Lex Fridman?

  Right.

• 1:27:52Max Tegmark?

  Right? That's our reference point. That's pretty useless. That's not gonna be the main military use of them. They might be useful in, in law enforcement in the future. And then there's a whole debate about, do you want robots showing up at your house with guns telling you to, uh, who will be perfectly obedient to whatever dictator controls them. But, but let's leave that aside for a moment and look at what's actually relevant now. So there, there's a spectrum of things you can do with AI in the military. And again, to put my card on the table, I'm not the pacifist. I think we should have good defense.

• 1:28:29Max Tegmark?

  So, for example, a predator drone is a, basically a fancy little remote controlled airplane. Right? There's a human piloting it and the decision ultimately about whether to kill somebody with it is made by a human still. And the, this is a line I think we should never cross. There's a current DOD policy, again, you have to have a human in the loop. I think algorithms should never make life or death decisions. They should be left to humans. Now, why might we cross that line? Well, first of all, these are expensive, right? So, for example, when, when, uh, When Azerbaijan had all these drones and Armenia didn't have any, they start trying

• 1:29:13Max Tegmark?

  to jerry-rig little cheap things, fly around. But then, of course, the Armenians would jam them, or the Azeris would jam them. And remote-controlled things can be jammed. That makes them inferior. Also, there's a bit of a time delay between, you know, if we're piloting something far away, speed of light, and the human has a reaction time as well. It would be nice to eliminate that jamming possibility and the time delay by having it fully autonomous. But now you might be, so then, if you do, but now you might be crossing that exact line. You might program it to just, oh, yeah, the air drone, go hover over this country for a while. And whenever you find someone who is a bad guy, you know, kill them. Now

• 1:29:57Max Tegmark?

  the machine is making these sort of decisions. And you, and some people who defend this still say, well, that's morally fine, because we are the good guys, and we will tell it the definition of bad guy that we think is moral. But now, it would be very naive to think that if ISIS buys that same drone, that they're going to use our definition of bad guy. Maybe for them, bad guy is someone wearing a US Army uniform. Right. Or maybe, maybe there will be some weird ethnic group who decides that someone of an other ethnic group, they are the bad guys, right? Yes. The thing is, human soldiers, with all our faults, right, we still have some basic

• 1:30:41Max Tegmark?

  wiring in us, like, no, it's not okay to kill kids and civilians. And Thomas Weppe has none of that. It's just gonna do whatever is programmed. It's like the perfect Adolf Eichmann on steroids. Like, they told him, Adolf Eichmann, you know, he wanted to do this, and this, and this, to make the Holocaust more efficient. And he was like, Yeah. And off he went and did it, right? Yeah. Do we really want to make machines that are like that? Like completely amoral and will take the user's definition of who is the bad guy? And do we then want to make them so cheap? That all our adversaries can have them like? What could possibly go wrong? That's the, that's, I think, the big argument for why we want to.

• 1:31:25Max Tegmark?

  This year, really put the kibosh on this. And I think you can tell there's a lot of very active debate even going on within the US military. And undoubtedly in other militaries around the world also about whether we should have some sort of international agreement. To at least require that.

• 1:31:44Max Tegmark?

  These weapons have to be above a certain size and cost, you know, so that.

• 1:31:51Max Tegmark?

  Things just don't totally spiral out of control.

• 1:31:55Max Tegmark?

  And finally, just for your question, but is it possible to stop it? Because some people tell me, oh, just give up, you know? But again. So, so Matthew Meslson, again, from Harvard, right? Who the bioweapons hero?

• 1:32:10Max Tegmark?

  He had exactly this criticism, also with bioweapons. People were like, how can you check for sure that the Russians aren't cheating?

• 1:32:18Max Tegmark?

  And. He, he told me this, I think, really ingenious insight. He said, you know, Max? Some people think you have to have inspections and things and you have to make sure that people that you can catch the cheaters with a hundred percent chance. You don't need a hundred percent, he said. One percent is usually enough. Because if it's an enemy, if it's another big state. Like suppose China and the US have signed the treaty. Drawing a certain line and saying, yeah, these kind of drones are okay, but these fully autonomous ones are not. Now suppose you are.

• 1:32:57Max Tegmark?

  China and you have cheated and secretly developed some clandestine little thing, or you're thinking about doing it, you know, what's your calculation that you do? Well, you're like, okay, what's the probability that we're going to get caught?

• 1:33:10Max Tegmark?

  If the probability is a hundred percent, of course, we're not going to do it.

• 1:33:14Max Tegmark?

  But if the probability is five percent that we're going to get caught, then it's going to be like a huge embarrassment for us. And it doesn't have, it's, we still have our nuclear weapons anyway, so it doesn't really make an enormous difference in terms of deterring the US, you know?

• 1:33:33Lex Fridman?

  And that is the stigma that you kind of established, like this fabric, this universal stigma over the thing.

• 1:33:40Max Tegmark?

  Exactly. It's very reasonable for them to say, well, you know, we probably get away with it, but if we don't, then the US will know we cheated and then they're going to go full tilt with their program and say, look, the Chinese are cheaters and that's going, now we have all these weapons against us and that's bad. So the stigma alone is very, very powerful. And again, look what happened with bioweapons, right? It's been 50 years now. When was the last time you read about a bioterrorism attack? The only deaths I really know about with bioweapons that have happened, when we Americans managed to kill some of our own with anthrax, you know, the idiot who sent them to Tom Dashil and others in letters, right? And similarly, in Sverdlovsk in the Soviet Union, they had some anthrax in some lab

• 1:34:23Max Tegmark?

  there, maybe they were cheating or who knows, and it leaked out and killed a bunch of Russians. I'd say that's a pretty good success, right? Fifty years, just two own goals by the superpowers and then nothing. And that's why whenever I ask anyone what they think about biology, they, they think it's great. They associate it with, with new cures, new diseases, maybe a good vaccine. This is how I want to think about AI in the future. I want, and I want others to think about AI too, as a source of all these great solutions to our problems, not as, oh, AI, oh yeah, that's the reason I feel scared going outside these days.

• 1:35:00Lex Fridman?

  Yes, it's kind of brilliant that the bioweapons and nuclear weapons, we've figured out. I mean, of course, there's still a huge source of danger, but we figured out some way of creating rules and social stigma over these weapons that then creates a stability toward whatever that game theory stability that of course.

• 1:35:22Max Tegmark?

  Exactly.

• 1:35:23Lex Fridman?

  And we don't have that with AI and you're kind of screaming from the top of the mountain about this that we need to find that because just like, you know, it's very possible, you know, with future of life, as you've point out, institute awards pointed out that, you know, with nuclear weapons, we could have destroyed ourselves quite a few times and it's, you know, it's a learning experience that doesn't is very costly.

• 1:35:54Max Tegmark?

  We gave, you know, this future life award, we gave it the first time to this guy, Vasily Arkhipov, you know, he was on, most people haven't even heard of.

• 1:36:03Lex Fridman?

  Yeah, can you say who he is?

• 1:36:04Max Tegmark?

  Vasily Arkhipov, he has, in my opinion, made the greatest positive contribution to humanity of any human in modern history. And maybe it sounds like hyperbole here, like I'm just over the top, but let me tell you the story and I think maybe you'll agree. So during the Cuban Missile Crisis, we Americans first didn't know that the Russians had sent four submarines, but we caught two of them and we didn't know that, so we dropped practice depth charges on the one that he was on, try to force it to the surface. But we didn't know that this nuclear submarine actually was a nuclear submarine with a nuclear torpedo.

• 1:36:46Max Tegmark?

  We also didn't know that they had authorization to launch it without clearance from Moscow. And we also didn't know that they were running out of electricity, their batteries were almost dead, they were running out of oxygen, sailors were fainting left and right. The temperature was about 110, 120 Fahrenheit on board. It was really hellish conditions, really just a kind of doomsday. And at that point, these giant explosions start happening from Americans dropping these. The captain thought World War III had begun. They decided that they were going to launch the nuclear torpedo. And one of them shouted, you know, we're all going to die, but we're not going to disgrace our navy, you know. We don't know what would have happened if there had been a giant mushroom cloud all of a sudden, you

• 1:37:28Max Tegmark?

  know, and against Americans. But since everybody had their hands on the triggers. Pretty, you don't have to be too creative to think that it could have led to all our nuclear war, in which case we wouldn't be having this conversation now, right? What actually took place was they needed three people to approve this. The captain had said yes, there was the Communist Party political officer, he also said yes, let's do it. And the third man was this guy, who said niat. Yeah. And for some reason, he was just more chilled than the others, and he was the right man at the right time. I don't want us as a species rely on the right person being there at the right time, you know? We tracked down his family, living in relative poverty outside Moscow.

• 1:38:14Max Tegmark?

  We flew his daughter, he had passed away, and flew them to London. They had never been to the West even, it was incredibly moving to get to honor them for this. The next year, we gave this Future Life Award to Stanislav Petrov, have you heard of him? Yes. So he was in charge of the Soviet early warning station, which was built with Soviet technology and honestly, not that reliable. It said that there were five US missiles coming in. Again, if they had launched at that point, we probably wouldn't be having this conversation. He decided, based on mainly gut instinct, to just not escalate this.

• 1:38:57Max Tegmark?

  And I'm very glad he wasn't replaced by an AI that was just automatically following orders. And then we gave the third one to Matthew Meselson. Last year, we gave this award to these guys who actually use technology for good. Not avoiding something bad, but for something good. The guys who eliminated this disease, which is way worse than COVID,

• 1:39:20Max Tegmark?

  that had killed half a billion people in its final century, smallpox, right? So you mentioned it earlier. COVID, on average, kills less than 1% of people who get it, smallpox, about 30%. And they just, ultimately Viktor Zdanov and Bill Fegy, most of my colleagues have never heard of either of them, one American, one Russian, they... Did this amazing effort. Not only was Shdanov able to get the US and the Soviet Union to team up against smallpox during the Cold War, but Bill Fegy came up with this ingenious strategy for making it actually go all the way to defeat the disease without funding

• 1:40:02Max Tegmark?

  for vaccinating everyone. And as a result, we haven't had any, we went from 15 million deaths the year I was born in smallpox. So what do we have in COVID now? A little bit short of 2 million, right?

• 1:40:12Lex Fridman?

  Yes.

• 1:40:13Max Tegmark?

  To zero deaths, of course, this year and forever. There have been 200 million people, they estimate, who would have died since then by smallpox had it not been for this. So isn't science awesome?

• 1:40:25Lex Fridman?

  Yeah, that-

• 1:40:25Max Tegmark?

  When you use it for good. And the reason we want to celebrate these sort of people is to remind them of this. Science is so awesome when you use it for good.

• 1:40:35Lex Fridman?

  And those, those awards, actually, the variety there paints a very interesting picture. So the, the, the first two are looking at, it's kind of exciting to think that these, these average humans, in some sense, that they're products of, you know, billions of other humans that came before them, evolution, and some little, you said gut, you know, but there's something in there that, that stopped the annihilation of the human race. And that's a magical thing, but that's like this deeply human thing. And then there's the other aspect where that's also very human, which is to build solution to the, to the

• 1:41:18Lex Fridman?

  existential crises that we're facing, like to build it, to take the responsibility and to take, come up with different technologies and so on.

• 1:41:25Max Tegmark?

  Yeah.

• 1:41:26Lex Fridman?

  And both of those are deeply human. The gut and, and the mind, whatever that is-

• 1:41:32Max Tegmark?

  Yeah. And the best is when they work together. Arkhipov, I wish I could have met him, of course, but he had passed away. He was really a fantastic military officer, combining all, all the best traits that we in America admire in our military. Because first of all, he was very loyal, of course. He never even told anyone about this during his whole life, even though you think he had some bragging rights, right?

• 1:41:53Lex Fridman?

  Yes.

• 1:41:54Max Tegmark?

  But he just was like, this is just business, just doing my job. It only came out later after his death. And, and second, the reason he did the right thing was not because he was some sort of liberal or some sort of, not because he was-

• 1:42:09Max Tegmark?

  Just, oh, you know, peace and love. It was partly because he had been the captain on another submarine that had a nuclear reactor meltdown. And it was his heroism that helped contain this. That's why he died of cancer later also. But he's seen many of his crew members die. And I think for him, that gave him this gut feeling that, you know, if there's a nuclear war between the US and the Soviet Union, the whole world is going to go through what I saw my dear crew members suffer through. It wasn't just an abstract thing for him. I think it was real. And second, though, not just the gut, the mind, right? He was, for some reason, very level-headed personality and very smart guy,

• 1:42:51Max Tegmark?

  which is exactly what we want our best fighter pilots to be also. I never forget Neil Armstrong when he's landing on the moon and almost running out of gas. And he doesn't even change, when they say 30 seconds, he doesn't even change the tone of voice, just keeps going. Arkhipov, I think, was just like that. So when the explosions start going off and his captain is screaming, we should nuke them and all, he's like,

• 1:43:16Max Tegmark?

  "I don't think the Americans are trying to sink us. I think they're trying to send us a message."

• 1:43:23Max Tegmark?

  That's a pretty badass.

• 1:43:24Lex Fridman?

  Yes.

• 1:43:25Max Tegmark?

  Coolness, because he said, if they wanted to sink us. And he said, listen, listen, it's alternating, one loud explosion on the left, one on the right, one on the left, one on the right. He was the only one to notice this pattern.

• 1:43:41Max Tegmark?

  And he's like, I think this is them trying to send us a signal that they want us to surface and they're not going to sink us.

• 1:43:51Max Tegmark?

  And somehow,

• 1:43:54Max Tegmark?

  this is how he then managed to ultimately, with his combination of gut and also just cool analytical thinking, was able to de-escalate the whole thing. And yeah, so this is some of the best in humanity. I guess, coming back to what we talked about earlier, it's the combination of the neural network, the instinctive, you know, with, I'm getting, tearing up here, getting emotional. But he was just, he is one of my superheroes, having both the heart and the mind combined.

• 1:44:25Lex Fridman?

  And especially in that time, there's something about the, I mean, this is a very, in America, people are used to this kind of idea of being the individual. Of like on your own thinking.

• 1:44:36Max Tegmark?

  Yeah.

• 1:44:37Lex Fridman?

  I think under in the Soviet Union, under communism, it's actually much harder to do that.

• 1:44:43Max Tegmark?

  Oh, yeah, he didn't even he even got he didn't get any accolades either when he came back for this. Right. They just wanted to hush the whole thing up.

• 1:44:51Lex Fridman?

  Yeah, there's echoes of that with Chernobyl. There's all kinds of.

• 1:44:56Lex Fridman?

  That's one that's that's a really hopeful thing that amidst big centralized powers, whether it's companies or states, there's still the power of the individual to think on their own to act.

• 1:45:09Max Tegmark?

  But I think we need to think of people like this, not as a panacea we can always count on, but rather as a wake up call, you know. So because of them, because of Arkipov, we are alive to learn from this lesson, to learn from the fact that we shouldn't keep playing Russian roulette and almost have a nuclear war by mistake now and then. Because relying on luck is not a good long term strategy. If you keep playing Russian roulette over and over again, the probability of surviving just drops exponentially with time.

• 1:45:39Lex Fridman?

  Yeah.

• 1:45:40Max Tegmark?

  And if you have some probability of having an accidental nuclear war every year, the probability of not having one also drops exponentially. I think we can do better than that. So I I think the message is very clear. There are once in a while shit happens. And there is a lot of very concrete things we can do to reduce the risk of things like that happening in the first place.

• 1:46:02Lex Fridman?

  On the AI front, if we just link on that for for a second. So you're friends with, you often talk with Elon Musk throughout history. Did a lot of interesting things together. He has a a set of fears about the future of artificial intelligence, AGI. Do you have a sense, we've we've already talked about the things we should be worried about with AI. Do you have a sense of the shape of his fears in particular about AI? Of the which subset of what we've talked about, whether it's creating, you know, it's that direction of creating sort of these giant computational systems that are not explainable. They're not intelligible intelligence.

• 1:46:47Lex Fridman?

  Or is it is it the?

• 1:46:52Lex Fridman?

  And then like as a branch of that, is it the manipulation by big corporations of that or individual evil people to use that for destruction or the unintentional consequences? Do you have a sense of where his thinking is on this?

• 1:47:05Max Tegmark?

  From my many conversations with Elon, yeah, I certainly have a model of how he thinks. It's actually very much like the way I think also. I'll elaborate on it a bit. I just want to push back on when you said evil people. I don't think it's a very helpful concept, evil people.

• 1:47:25Lex Fridman?

  Yes.

• 1:47:25Max Tegmark?

  Sometimes people do very, very bad things, but they usually do it because they think it's a good thing.

• 1:47:30Lex Fridman?

  Yes.

• 1:47:31Max Tegmark?

  Because somehow other people had told them that that was a good thing or given them incorrect information or whatever, right?

• 1:47:41Max Tegmark?

  I believe in the fundamental goodness of humanity, that if we educate people well and they find out how things really are, people generally want to do good and be good.

• 1:47:53Lex Fridman?

  Hence the value alignment.

• 1:47:55Max Tegmark?

  Yes.

• 1:47:56Lex Fridman?

  It's about information, about knowledge, and then once we have that, we'll likely be able to do good in a way that's aligned with everybody else who thinks.

• 1:48:07Max Tegmark?

  Yeah, and it's not just the individual people we have to align. So we don't just want people to be educated to know the way things actually are and to treat each other well, but we also need to align other non-human entities. We talked about corporations, there has to be institutions so that what they do is actually good for the country they're in, and we should align, make sure that what countries do is actually good for the species as a whole, et cetera. Coming back to Elon, yeah, my understanding of how Elon sees this is really quite similar to my own, which is one of the reasons I like him so much and enjoy talking with him so much. I think he's quite different from most people in that he.

• 1:48:51Max Tegmark?

  Thinks much more than most people about the really big picture. Not just what's gonna happen in the next election cycle, but in millennia, millions and billions of years from now. And when you look in this more cosmic perspective, it's so obvious that we're gazing out into this universe that, as far as we can tell, is mostly dead, with life being almost imperceptibly tiny perturbation. And he sees this enormous opportunity for our universe to come alive, for us to become an interplanetary species. Mars is obviously just first stop on this cosmic journey. And precisely because he thinks more long term, it's much more clear to him than to most people that what we do with this Russian roulette thing,

• 1:49:36Max Tegmark?

  we keep playing with our nukes, is a really poor strategy, a really reckless strategy. And also that we're just building these ever more powerful AI systems that we don't understand is also a really reckless strategy. I feel Elon is very much a humanist in the sense that he wants an awesome future for humanity. He wants to be us that control the machines rather than the machines that control us.

• 1:50:03Lex Fridman?

  Yes.

• 1:50:04Max Tegmark?

  And why shouldn't we insist on that? Hey, we're building them after all, right? Why should we build things that just make us into some little cog in the machinery that has no further say in the matter? It's not my idea of inspiring future either.

• 1:50:20Lex Fridman?

  Yeah, if you think on the cosmic scale in terms of both time and space, so much is put into perspective.

• 1:50:28Max Tegmark?

  Yeah. Whenever I have a bad day, that's what I think about. Immediately makes me feel better.

• 1:50:34Lex Fridman?

  It makes me sad that for us individual humans, at least for now, the ride ends too quickly. That we don't get to experience the cosmic scale.

• 1:50:45Max Tegmark?

  Yeah, I mean, I think of our universe sometimes as an organism that has only begun to wake up a tiny bit. Just like when the very first little glimmers of consciousness you have in the morning, when you start coming around.

• 1:50:57Lex Fridman?

  Before the coffee.

• 1:50:58Max Tegmark?

  Before the coffee, even before you get out of bed, before you even open your eyes. It starts to wake up a little bit. There's something here, you know. That's very much how I think of what we are, you know, those, all those galaxies out there, you know, I think they're really beautiful. But why are they beautiful? They're beautiful because conscious entities are actually observing them and experiencing them through our telescopes. If I, you know, I define consciousness as subjective experience, whether it be colors or emotions or sounds. So beauty is an experience, meaning is an experience, purpose is an experience.

• 1:51:41Max Tegmark?

  If there was no conscious experience observing these galaxies, they wouldn't be beautiful. If, if we do something dumb with advanced AI in the future here and Earth originating, life goes extinct. And that was it for this. If there is nothing else with telescopes in our universe, then it's kind of game over for meaning, beauty and meaning and purpose in our whole universe. And I think that would be just such an opportunity lost, frankly. And I think when Elon points this out, he gets very unfairly maligned in the media for all the dumb media bias reasons we talked about, right? They want to print precisely the things about Elon out of context that are really clickbaity.

• 1:52:23Max Tegmark?

  Like he has gotten so much flak for this summoning the demon statement.

• 1:52:28Lex Fridman?

  Oh, yeah.

• 1:52:30Max Tegmark?

  I happen to know exactly the context because I was in the front row when he gave that talk. It was at MIT, you'll be pleased to know, it was the AeroAstro anniversary. They had Buzz Aldrin there from the moon landing, the whole house, Krezge Auditorium packed with MIT students. And he had this amazing Q and A, it might have gone for an hour and they talked about rockets and Mars and everything. At the very end, this one student who was actually in my class asked him, what about AI? Elon makes this one comment and they take this out of context, print it, goes viral.

• 1:53:04Lex Fridman?

  Was it like with AI, we're summoning the demon, something like that?

• 1:53:08Max Tegmark?

  And try to cast him as some sort of doom and gloom dude, you know? You know Elon, that's, he's not the doom and gloom dude. He, he is such a positive visionary and the whole reason he warns about this is because he realizes more than most what the opportunity cost is of screwing up, that there is so much awesomeness in the future that we can, we can and our descendants can enjoy if we don't screw up, right? I, I get so pissed off when people try to cast him as some sort of.

• 1:53:38Max Tegmark?

  Technophobic Luddite. And at this point, it's kind of ludicrous when I hear people say that people who worry about artificial general intelligence are Luddites. Because of course, if you look more closely, you have some of the most outspoken people making warnings are people like Professor Stuart Russell from Berkeley, who's written the bestselling AI textbook, you know. So claiming that he's a Luddite who doesn't understand AI is the joke is really on the people who said it. But I think more broadly, this message is really not sunk in at all. What it is that people worry about, they think that Elon and Stuart Russell and others

• 1:54:22Max Tegmark?

  are worried about the dancing robots picking up an AR-15 and going on a rampage, right? They think they're worried about robots turning evil. They're not. I'm not. The risk is not malice. It's competence. The risk is just that we build some systems that are incredibly competent, which means they're always going to get their goals accomplished, even if they clash with our goals. That's the risk. Why did we humans, you know, drive the West African black rhino extinct? Is it because we're malicious, evil rhinocerous haters? No, it's just because our goals didn't align with the goals of those rhinos and tough

• 1:55:06Max Tegmark?

  luck for the rhinos, you know? So when I'm, the point is just, we don't want to put ourselves in the position of those rhinos, creating these, something more powerful than us if we haven't first figured out how to align the goals. And I am optimistic. I think we could do it if we worked really hard on it. Because I spent a lot of time around intelligent entities that were more intelligent than me, my mom and my dad. And I was little and that was fine, because their goals were actually aligned with mine quite well. But we've seen today many examples of where the goals of our powerful systems are not so aligned. So those.

• 1:55:46Max Tegmark?

  Click-through optimization algorithms that are polarized social media, right? They were actually pretty poorly aligned with what was good for democracy, it turned out. And again, almost all problems we've had in the machine learning, again, came so far, not from malice, but from poor alignment. And it's, that's exactly why, that's why we should be concerned about in the future.

• 1:56:05Lex Fridman?

  Do you think it's possible that with systems like Neuralink and brain-computer interfaces, you know, again, thinking of the cosmic scale, Elon's talked about this, but others have as well throughout history of figuring out how, the exact mechanism of how to achieve that kind of alignment. So one of them is having a symbiosis with AI, which is like coming up with clever ways where we're like stuck together in this weird relationship, whether it's biological or in some kind of other way. Do you think there's, that's a possibility of having that kind of symbiosis?

• 1:56:44Lex Fridman?

  Or do we want to instead kind of focus on this distinct entities of us humans talking to these intelligible, self-doubting AIs, maybe like Stuart Russell thinks about it, like these, we're self-doubting and full of uncertainty and have our AI systems that are full of uncertainty, we communicate back and forth and in that way achieve symbiosis?

• 1:57:10Max Tegmark?

  I honestly don't know. I would say that because we don't know for sure what, if any of our, which of any of our ideas will work, but we do know that if we don't, I'm pretty convinced that if we don't get any of these things to work and just barge ahead, then our species is, you know, probably going to go extinct this century. I think it-

• 1:57:30Lex Fridman?

  This century? You think like, you think we're facing this crisis is a 21st century crisis?

• 1:57:36Max Tegmark?

  Oh, yeah.

• 1:57:37Lex Fridman?

  This century will be remember-

• 1:57:41Max Tegmark?

  On a hard drive.

• 1:57:42Lex Fridman?

  On a hard drive somewhere, or maybe by future generations is like, like there'll be future, future of life institute awards for people that have done something about AI.

• 1:57:56Max Tegmark?

  It could also end even worse, where there is, we're not superseded by leaving any AI behind either, where we just totally wipe out, you know, like on Easter Island. Our century is long, you know, there are still 79 years left of it, right? Think about how far we've come just in the last 30 years. So we can talk more about what might go wrong, but you asked me this really good question about what's the best strategy? Is it Neuralink or Russell's approach or whatever? I think, you know, when we, when we did the Manhattan Project, we didn't know if any of our four ideas for enriching uranium and getting out the uranium 235 were going to work. But we felt this was really important to get it

• 1:58:40Max Tegmark?

  before Hitler did. So, you know, what we did, we tried all four of them. Here, I think it's analogous where there's the greatest threat that's ever faced our species and of course, US national security by implication. We don't know, we don't have any method that's guaranteed to work, but we have a lot of ideas. So we should invest pretty heavily in pursuing all of them with an open mind and the hope that one of them at least works. These are, the good news is the century is long, you know, and it might take decades until we have artificial general intelligence. So we have some time, hopefully, but it takes a long time for us to solve these very, very difficult problems. It's going to actually

• 1:59:23Max Tegmark?

  be, it's the most difficult problem we were ever trying to solve as a species. So we have to start now, so we don't have, rather than, you know, begin thinking about it the night before, some people who've had too much Red Bull switch it on. And we have to, coming back to your question, we have to pursue all of these different avenues and see.

• 1:59:39Lex Fridman?

  If you were my investment advisor, and I was trying to invest in the future, how do you think the human species is most likely to destroy itself in this century?

• 1:59:55Lex Fridman?

  Yeah. And so if, if the crises, many of the crises we're facing are really before us within the next hundred years. How do we make explicit, make known the unknowns and solve those problems to avoid the biggest, starting with the biggest existential crisis?

• 2:00:17Max Tegmark?

  So as your investment advisor, how are you planning to make money on us going destroying ourselves, I have to ask?

• 2:00:22Lex Fridman?

  I don't know. It might be the Russian origins somehow involved.

• 2:00:28Max Tegmark?

  At the micro level of detailed strategies, of course, these are unsolved problems. For AI alignment, we can break it into three sub-problems that are all unsolved. I think you want first to make machines understand our goals, then adopt our goals, and then retain our goals. So to hit on all three real quickly. The problem when Andreas Lubitz told his autopilot to fly into the Alps was that the computer didn't even understand anything about his goals, right? It was too dumb. It could have understood, actually, but you would have had to put some effort in as a

• 2:01:11Max Tegmark?

  system designer, don't fly into mountains. So that's the first challenge. How do you program into computers human values, human goals? We could start, rather than saying, oh, it's so hard, we should start with the simple stuff, as I said, self-driving cars, airplanes, just put in all the goals that we all agree on already, and then have a habit of whenever machine gets smarter, so they can understand one lever higher goals, you know, put them into. The second challenge is getting them to adopt the goals. It's easy for situations like that, where you just program it in, but when you have

• 2:01:49Max Tegmark?

  self-learning systems like children, you know, any parent knows that there is a difference between getting our kids to understand what we want them to do and to actually adopt our goals, right? With humans, with children, fortunately, they...

• 2:02:08Max Tegmark?

  They go through this phase. First, they're too dumb to understand what we want, our goals are. And then to have this period of some years when they're both smart enough to understand them and malleable enough that we have a chance to raise them well. And then they become teenagers, kind of too late. But we have this window with machines. The challenge is they might, the intelligence might grow so fast that that window is pretty short. So that's a, that's a research problem. The third one is how do you make sure they keep the goals if they keep learning more and getting smarter? Many sci fi movies are about how you have something which initially was aligned, but then things kind of go off keel. And, you know, my kids were very, very excited about their Legos when they were

• 2:02:51Max Tegmark?

  little. Now they're just gathering dust in the basement, you know? If we put, if we create machines that are really on board with a goal of taking care of humanity, we don't want them to get as bored with us and, and as my kids got with Legos. So this is another research challenge. How can you make some sort of recursively self improving system retain certain basic goals?

• 2:03:13Lex Fridman?

  That said, a lot of adult people still play with Legos. So maybe we succeeded with the Legos.

• 2:03:18Max Tegmark?

  Maybe. I like your optimism.

• 2:03:20Lex Fridman?

  So not all AI systems have to maintain the goals, right? Some, just some fraction.

• 2:03:25Max Tegmark?

  Yeah. So there, so there is a, there's a lot of talented AI researchers now who have heard of this and want to work on it. Not so much funding for it yet. Of the billions that go into building AI more powerful, it's only a miniscule fraction so far going into the safety research. My attitude is generally, we should not try to slow down the technology, but we should greatly accelerate the investment in this sort of safety research. And also make sure, it's been, it's, this was very embarrassing last year, but you know, the NSF decided to give out six of these big institutes. We got one of them for AI and science you asked me about. Another one was supposed to be for AI safety research.

• 2:04:06Max Tegmark?

  And they gave it to people studying oceans and climate and stuff.

• 2:04:10Lex Fridman?

  Yeah.

• 2:04:12Max Tegmark?

  So I'm all for studying oceans and climates, but we need to actually have some money that actually goes into AI safety measures also and doesn't just get grabbed by whatever. That's a fantastic investment. And then at the higher level, you ask this question, okay, what can we do? You know, what are the biggest risks? I think, I think we cannot just consider this to be only a technical problem. Again, because if you solve only the technical problem, can I play with your robot?

• 2:04:40Lex Fridman?

  Yes, please.

• 2:04:41Max Tegmark?

  If we can get our machines, you know, to just blindly obey the orders we give them. So we can always trust that it will do what we want. That might be great for the owner of the robot. That might not be so great for the rest of humanity. If that person is that least favorite world leader or whatever you imagine, right? So we have to also take, look at, apply alignment, not just to machines, but to all the other powerful structures. That's why it's so important to strengthen our democracy again, as I said, to have institutions, make sure that the playing field is not rigged, so that corporations are given the right incentives to do the things that both make profit and are good for people.

• 2:05:24Max Tegmark?

  To make sure that countries have incentives to do things that are both good for their people and don't screw up the rest of the world. And this is not just something for AI nerds, you know, to geek out on. This is the interesting challenge for political scientists, economists, and so many other thinkers.

• 2:05:42Lex Fridman?

  So one of the magical things that perhaps makes this earth quite unique is that it's home to conscious beings. So you mentioned consciousness.

• 2:05:57Lex Fridman?

  Perhaps as a small aside, because we didn't really get specific to what, how we might do the alignment, like you said, is just a really important research problem. But do you think engineering consciousness into AI systems is a possibility? Is something that we might one day do? Or is there something fundamental to consciousness that is, is there something about consciousness that is fundamental to humans and humans only?

• 2:06:28Max Tegmark?

  I think it's possible. I think both consciousness and intelligence are information processing, certain types of information processing, and that fundamentally, it doesn't matter whether the information is processed by carbon atoms in neurons and brains, or by silicon atoms and so on in our technology. Some people disagree. This is what I think is this physicist, that I, and that consciousness is the same kind of, you said consciousness is information processing. So meaning, you know, I think you had a quote of something like, it's information, knowing itself, that kind of thing.

• 2:07:13Max Tegmark?

  I think consciousness, yeah, is the way information feels when it's being processed. Was be for that, yeah. Complex ways. We don't know exactly what those complex ways are. It's clear that most of the information processing in our brains does not create an experience. We're not even aware of it, right? Like, for example, you're not aware of your heartbeat regulation right now, even though it's clearly being done by your body, right? It's just kind of doing its own thing. When you go jogging, there's a lot of complicated stuff about how you put your foot down. And we know it's hard. That's why robots used to fall over so much, but you're mostly unaware about it. Your brain, your CEO, consciousness module just sends an email, hey, I want to keep jogging along this path. The rest is on autopilot, right? Yes.

• 2:07:57Max Tegmark?

  So most of it is not conscious, but somehow, there are some of the information processing which is. We don't know what, what exactly. I think this is a science problem that I hope one day we'll have some equation for or something, so we can be able to build a consciousness detector and say, yeah, here there is some consciousness, here there's not. Oh, don't boil that lobster because it's feeling pain or it's okay because it's not feeling pain. Right now, we treat this as sort of just metaphysics.

• 2:08:29Max Tegmark?

  But it would be very useful in emergency rooms to know if a patient has locked in syndrome and is conscious, or if they are actually just out. And in the future, if you build a very, very intelligent helper robot to take care of you, you know, I think you'd like to know if you should feel guilty about shutting it down, or if it's just like a zombie going through the motions like a fancy tape recorder, right? And once we can make progress on the science of consciousness and figure out what is conscious and what isn't, then

• 2:09:06Max Tegmark?

  we, assuming we want to create positive experiences and not suffering, we'll probably choose to build some machines that are deliberately unconscious, that do incredibly boring, repetitive jobs in an iron mine somewhere or whatever. And maybe we'll choose to create helper robots for the elderly that are conscious, so that people don't just feel creeped out, that the robot is just faking it when it acts like it's sad or happy.

• 2:09:37Lex Fridman?

  Like I said, elderly, I think everybody gets pretty deeply lonely in this world. And so there's a place, I think, for everybody to have a connection with conscious beings, whether they're human or otherwise.

• 2:09:49Max Tegmark?

  But I know for sure that I would, if I had a robot, if I was going to develop any kind of personal emotional connection with it, I would be very creeped out if I knew it in an intellectual level, that the whole thing was just a fraud. You know, today, you can buy a little talking doll for a kid, which will say things, and the little child will often think that this is actually conscious, and even real secrets to it that then go on the internet, and with all sorts of creepy repercussions. You know, I would not want to be just hacked and tricked like this. If I was going to be developing real emotional connections with a robot, I would want to know that this is actually real. It's acting

• 2:10:31Max Tegmark?

  conscious, acting happy because it actually feels it. And I think this is not sci fi. I think.

• 2:10:38Lex Fridman?

  It's possible to measure, to come up with tools and make, after we understand the science of consciousness, you're saying is we'll be able to come up with tools that can measure consciousness and definitively say like this thing is experiencing the things it says it's experiencing.

• 2:10:52Max Tegmark?

  Kind of by definition, if it is a physical phenomenon, information processing that, and we know that some information processing is conscious and some isn't, well, then there is something there to be discovered with the methods of science. Giulio Tononi has stuck his neck out the farthest and written down some equations for a theory. Maybe that's right, maybe it's wrong, we certainly don't know. But I applaud that kind of efforts to sort of take this, say this, say this is not just something that philosophers can have beer and muse about, but something we can measure, we can study and coming, being that back to us. I, I think what we would probably choose to do, as I said, is if we cannot figure this out, choose to make, to be quite mindful about what sort of consciousness, if any,

• 2:11:36Max Tegmark?

  we put in, in different machines that we have. We, and certainly, we wouldn't want to make, we should not be making much of machines that suffer without us even knowing it, right? And if, if at any point, someone decides to upload themselves, like Ray Kurzweil wants to do, I don't know if you've had him on your show.

• 2:11:56Lex Fridman?

  We agree, but then COVID happens, so we're waiting it out a little bit.

• 2:12:00Max Tegmark?

  You know, suppose he uploads himself into this robo Ray and it talks like him and acts like him and laughs like him and before he powers off his biological body, he would probably be pretty disturbed if he realized that there's no one home. This robot is not having any subjective experience, right? If we, if humanity gets replaced by, by, by machine descendants, do all these cool things and build spaceships and go to intergalactic rock concerts and it turned out, turns out that they are all unconscious, just going through the motions, wouldn't that be like the ultimate robot zombie apocalypse, right? Just a play for empty benches.

• 2:12:43Lex Fridman?

  Yeah, I have a sense that there's some kind of, once we understand consciousness better, we'll understand that there's some kind of continuum. And it would be a greater appreciation. And we'll probably understand, just like you said, it'd be unfortunate if it's a trick. We'll probably definitively understand that love is indeed a trick. That we'll play on each other, that we humans are, we convince ourselves we're conscious, but we're really, you know, us and trees and dolphins are all the same kind of consciousness.

• 2:13:12Max Tegmark?

  Can I try to cheer you up a little bit with a philosophical thought here about the love part?

• 2:13:15Lex Fridman?

  Yes, let's do it.

• 2:13:16Max Tegmark?

  You know, you might say, okay, yeah, love is just a collaboration enabler. And then you'll, and then maybe you can go and get depressed about that. But I, I think that would be the wrong conclusion, actually. You know, like, I know that the only reason I enjoy food is because my genes hacked me and they don't want me to starve to death, not because they care about me consciously enjoying succulent delights of pistachio ice cream, but they just, they just want me to make copies of them, the whole thing. So in a sense, the whole, the whole enjoyment of food is also a scam like this. But does that mean I shouldn't take pleasure in this pistachio ice cream?

• 2:13:58Max Tegmark?

  I love pistachio ice cream and I can tell you, I have, I have, I know this is an experimental fact, I enjoy pistachio ice cream every bit as much, even though I scientifically know exactly why, what kind of scam this was.

• 2:14:12Lex Fridman?

  Your genes really appreciate that you like the pistachio ice cream.

• 2:14:15Max Tegmark?

  Well, but I, my mind appreciates it too, you know? And I have a conscious experience right now. Ultimately, all of my brain is also just something the genes built to copy themselves, but so what? You know, I'm grateful that, yeah, thanks genes for doing this, but you know, now it's my brain that's in charge here and I'm going to enjoy my conscious experience. Thank you very much. And not just the pistachio ice cream, but also the love I feel for my amazing wife. And. All the other delights of being conscious, I don't, actually, Richard Feynman, I think, said this so well, he is also the guy, you know, really got me into physics. Some art friend said that, oh, science kind of just is the party pooper.

• 2:15:00Max Tegmark?

  It kind of ruins the fun, right? When like, you have a beautiful flower, says the artist, and then the scientist is going to deconstruct that into just a blob of quarks and electrons. And Feynman pushed back on that in such a beautiful way, which I think also can be used to push back and make you not feel guilty about falling in love. So here's what Feynman basically said. He said to his friend, you know, yeah, I can also, as a scientist, see that this is a beautiful flower. Thank you very much. Maybe I'm, I can't draw as good a painting as you, because I'm not as talented an artist. But yeah, I can really see the beauty in it. And it just, it also looks beautiful to me. But in addition to that, Feynman said, as a scientist, I see even more beauty that the artist did not see, right?

• 2:15:42Max Tegmark?

  Suppose this is a flower on a blossoming apple tree. He could say, this tree has more beauty in it than just the colors and the fragrance. This tree is made of air, Feynman wrote. This is one of my favorite Feynman quotes ever. And it took the carbon out of the air and bound it in using the flaming heat of the sun, you know, to turn the air into tree. And when you burn logs in your fireplace, it's really beautiful to think that this is being reversed. Now, the tree is going, the wood is going back into air, and this flaming, beautiful dance of the fire that the artist can see is the flaming light of the sun that was bound in to turn the air into tree.

• 2:16:24Max Tegmark?

  And then the ashes is the little residue that didn't come from the air, that the tree sucked out of the ground, you know? Feynman said, these are beautiful things, and science just adds, it doesn't subtract. And I feel exactly that way about love and about pistachio ice cream also. I can understand that it even, there is even more nuance to the whole thing, right? At this very visceral level, you can fall in love just as much as someone who knows nothing about neuroscience.

• 2:16:53Max Tegmark?

  But you can also appreciate this even greater beauty in it. Just like, isn't it remarkable that it came about from this completely lifeless universe? Just a bunch of hot blob of plasma expanding. And then over the eons, you know, gradually first the strong nuclear force decided to combine quirks together into nuclei and then the electric force bound in electrons and made atoms. And then they clustered from gravity and you've got planets and stars and this and that. And then natural selection came along and the genes had their little thing. And you started getting what went from seeming like a completely pointless universe that was just trying to increase entropy and approach heat death into something that looked more goal oriented. Isn't that kind of beautiful?

• 2:17:38Max Tegmark?

  And then this goal orientedness through evolution got ever more sophisticated where you got ever more. And then you started getting this thing, which is kind of like DeepMind's mu zero and steroids, self, the ultimate self-play is not what, what DeepMind's AI does against itself to get better at Go. It's what all these little quirk blobs did against each other in the, in the game of, of survival of the fittest. You know, when you had really dumb bacteria living in a simple environment, there wasn't much incentive to get intelligent. But then the, the life made environment more, more complex. And then there was more incentive to get even smarter. And, and that gave the other organisms more of incentive to also get smarter.

• 2:18:23Max Tegmark?

  And then here we are now, just like, like mu zero learned to become world master at, at Go and chess from playing against itself by just playing against itself. All the quirks here on our planet and electrons have created giraffes and elephants and humans.

• 2:18:41Lex Fridman?

  Pistachio ice cream.

• 2:18:43Max Tegmark?

  I, I just find that really beautiful. And I, to me, that just adds to the enjoyment of, of love. It doesn't subtract anything. Do you feel a little more?

• 2:18:52Lex Fridman?

  I feel way better. That was, that was incredible. So the, this self-play of quirks. Taking back to the beginning of our conversation a little bit, you've, there's so many exciting possibilities about artificial intelligence, understanding the basic laws of physics. Do you think AI will help us unlock? There's been quite a bit of excitement throughout the history of physics of coming up with more and more general, simple laws that explain the nature of our reality. And then the ultimate of that would be a theory of everything that combines everything together. Do you think it's possible that, well, one, we humans, but perhaps AI systems will figure

• 2:19:35Lex Fridman?

  out a theory of physics that unifies all the laws of physics?

• 2:19:42Max Tegmark?

  Yeah, I think it's absolutely, absolutely possible. I think it's, it's very clear that we're going to see a great boost to science. We're already seeing a boost actually from, from machine learning, helping science. Alpha Fold was an example, you know, the decades old protein folding problem solved. And gradually, yeah, unless we go extinct by doing something dumb like we discussed, I think it's very likely that our understanding of physics will become so good that our technology will no longer be limited by human intelligence, but instead be limited by the laws of physics. So our tech today is limited by what we've been able to invent, right?

• 2:20:27Max Tegmark?

  I think as AI progresses, it'll just be limited by the speed of light and other physical limits, which would mean it's going to be just dramatically beyond, you know, where we are now.

• 2:20:40Lex Fridman?

  Do you think it's a fundamentally mathematical pursuit of trying to understand, like, the laws of this, that govern our universe from a mathematical perspective? It's almost like if it's AI, it's exploring the space of like theorems and those kinds of things. Or is there some other, is there some other more computational ideas? More sort of empirical ideas?

• 2:21:06Max Tegmark?

  They're both, I would say. It's really interesting to look out at the landscape of everything we call science today. So here we come now with this big new hammer. It says machine learning on it and ask, you know, where are there some nails that you can help with here? That you can hammer ultimately?

• 2:21:24Max Tegmark?

  If machine learning gets the point that it can do everything better than us, it will be able to help across the whole space of of of science. But maybe we can anchor it by starting a little bit right now, near term, and and see how we kind of move forward. So so like right now, first of all, you have a lot of big data science, where, for example, with telescopes, we are able to collect way more data every hour than a grad student can just pour over like in the old times, right? And machine learning is already being used very effectively, even at MIT, right, to find planets around other stars, to detect exciting new signatures of new particle physics in the sky, and to detect the the ripples in the fabric of spacetime

• 2:22:08Max Tegmark?

  that we call gravitational waves, caused by enormous black holes crashing into each other halfway across the observable universe. Machine learning is running and ticking right now, you know, doing all these things, and it's really helping all these experimental fields. There is a separate front of physics, computational physics, which is getting an enormous boost also. So we had to do all our computations by hand, right? People would have these giant books with tables of logarithms, and oh, my God, it pains me to even think how how long time it would have taken to do simple stuff. Then we started to get little calculators and computers that could do some basic math for us.

• 2:22:52Max Tegmark?

  Now, what we're starting to see is kind of a shift from GoFi computational physics to neural network computational physics. What I mean by that is most computational physics would be done by humans programming in the intelligence of how to do the computation into the computer. Just as when Gary Kasparov got his posterior kicked by IBM's Deep Blue in chess, humans had programmed in exactly how to play chess. Intelligence came from the humans, it wasn't learned, right?

• 2:23:29Max Tegmark?

  Mu zero can be not only Kasparov in chess, but also Stockfish, which is the best sort of GoFi chess program by learning. And we're seeing more of that now, that shift beginning to happen in physics. So let me give you an example. So lattice QCD is an area of physics whose goal is basically to take the periodic table and just compute the whole thing from first principles. This is not the search for a theory of everything. We already know the theory that's supposed to produce as output the periodic table, which atoms are stable, how heavy they are, all that good stuff, their spectral lines. It's called, it's a theory lattice QCD.

• 2:24:14Max Tegmark?

  You can put it on your T-shirt. Our colleague Frank Wilczek got the Nobel Prize for working on it. But the math is just too hard for us to solve. We have not been able to start with these equations and solve them to the extent that we can predict, oh, yeah. And then there is carbon, and this is what the spectrum of the carbon atom looks like. But awesome people are building these supercomputer simulations where you just put in these equations and you make a big cubic lattice of space, or actually it's a very small lattice because you're going at the subatomic scale, down to the subatomic scale, and you try to solve this. But it's just so computationally expensive that we still haven't been able to calculate

• 2:24:57Max Tegmark?

  things as accurately as we measure them in many cases. And now machine learning is really revolutionizing this. So my colleague Fiona Shanahan at MIT, for example, she's been using this really cool machine learning technique called normalizing flows, where she's realized she can actually speed up the calculation dramatically by having the AI learn how to do things faster. Another area like this where

• 2:25:26Max Tegmark?

  We suck up an enormous amount of supercomputer time to do physics as black hole collisions. So now that we've done the sexy stuff of detecting a bunch of this, LIGO and other experiments, we want to be able to know what we're seeing. And so it's a very simple conceptual problem. It's the two-body problem. Newton solved it for classical gravity hundreds of years ago, but the two-body problem is still not fully solved. For black holes. Black hole for, yes, and Einstein's gravity, because they won't just orbit each other forever anymore, two things, they give off gravitational waves and eventually they crash into each other. And the game, what you want to do is you want to figure out, okay, what kind of wave comes out as a function of the masses of the two black holes,

• 2:26:11Max Tegmark?

  as a function of how they're spinning relative to each other, et cetera. And that is so hard, it can take months of supercomputer time and massive numbers of cores to do it, you know.

• 2:26:23Max Tegmark?

  Wouldn't it be great if you can use machine learning to greatly speed that up, right?

• 2:26:30Max Tegmark?

  Now you can use the expensive old GoFi calculation as the truth, and then see if machine learning can figure out a smarter, faster way of getting the right answer. Yet another area like of computational physics, these are probably the big three that suck up the most computer time, lattice QCD, black hole collisions, and cosmological simulations, where you take not a subatomic thing and try to figure out the mass of the proton, but you take something with enormous and try to look at how all the galaxies get formed in there. Oh, wow, yeah. There again, there are a lot of very cool ideas right now about how you can use machine learning to do this sort of better, stuff better.

• 2:27:15Max Tegmark?

  The difference between this and the big data is you kind of make the data yourself, right? So, and then finally, we're looking over the physics landscape and seeing what can we hammer with machine learning, right? So we talked about experimental data, big data, discovering cool stuff that we humans then look more closely at. Then we talked about taking the expensive computations we're doing now and figuring out how to do them much faster and better with AI. And finally, let's go really theoretical. So things like discovering equations, having deep fundamental insights.

• 2:27:54Max Tegmark?

  This comes, this is something closest to what I've been doing in my group. We talked earlier about the whole AI Feynman project, where if you just have some data, how do you automatically discover equations that seem to describe this well? That you can then go back as a human and then work with and test and explore. And you asked a really good question also about if this is sort of a search problem in some sense. That's very deep, actually, what you said, because it is. Suppose I ask you to prove some mathematical theorem. What is a proof in math? It's just a long string of steps, logical steps that you can write out with symbols. And once you find it, it's very easy to write a program to check whether it's a valid

• 2:28:38Max Tegmark?

  proof or not. So why is it so hard to prove it then? Well, because there are ridiculously many possible candidate proofs you could write down, right? If the proof contains 10,000 symbols, even if there are only 10 options for what each symbol could be, that's 10 to the power 1,000 possible proofs, which is way more than there are atoms in our universe, right? So you could say it's trivial to prove these things. You just write a computer, generate all strings, and then check, is this a valid proof? Eh, no. Is this a valid proof? Eh, no. And then you just keep doing this forever. But there are a lot of, but it is fundamentally a search problem.

• 2:29:20Max Tegmark?

  You just want to search the space of all those, all strings of symbols to find the one, find one that is the proof, right? And there's a whole area of machine learning called search. How do you search through some giant space to find the needle in the haystack? It's easier in cases where there's a clear measure of good, like you're not just right or wrong, but this is better and this is worse. You can maybe get some hints as to which direction to go in. That's why we talked about neural networks work so well.

• 2:29:53Lex Fridman?

  I mean, that's such a human thing of that moment of genius of figuring out the intuition of. Of good, essentially. I mean, we thought that

• 2:30:04Max Tegmark?

  Where is it?

• 2:30:05Lex Fridman?

  Maybe it's not right. We thought that about chess, right?

• 2:30:08Max Tegmark?

  Exactly.

• 2:30:09Lex Fridman?

  That the ability to see like 10, 15, sometimes 20 steps ahead was not a calculation that humans were performing. It was some kind of weird intuition about different patterns, about board positions, about the relative positions.

• 2:30:24Max Tegmark?

  Exactly.

• 2:30:24Lex Fridman?

  Somehow stitching stuff together. And a lot of it is just like intuition. But then you have like Alpha, I guess, Zero be the first one that did the self-play. It just came up with this. It was able to learn through self-play mechanism, this kind of intuition.

• 2:30:41Max Tegmark?

  Exactly.

• 2:30:42Lex Fridman?

  But just like you said, it's so fascinating to think, well, they're in the space of totally new ideas. Can that be done in developing theorems?

• 2:30:54Max Tegmark?

  We know it can be done by neural networks because we did it with the neural networks in the craniums of the great mathematicians of our of humanity, right? And I'm so glad you brought up Alpha Zero because that's the counter example. It turned out we were flattering ourselves when we said intuition is something different. It's only humans can do it. It's not information processing. If you, if, it used to be that way. That, again, it's very, it's really instructive, I think, to compare the chess computer Deep Blue that beat Kasparov with Alpha Zero that beat Lee Sedol at the goal. Because for Deep Blue, there was no intuition. There was some pro, humans had programmed in some intuition.

• 2:31:37Max Tegmark?

  After humans had played a lot of games, they told the computer, you know, count the pawn as one point, the bishop is three points, the rook is five points and so on. You add it all up and then you add some extra points for past pawns and subtract if the opponent has it and, and blah, blah, blah, blah. And then what Deep Blue did was just search.

• 2:31:58Max Tegmark?

  Just very brute force, tried many, many moves ahead, all these combinations and a prune tree search. And it could think much faster than Kasparov and it won.

• 2:32:08Max Tegmark?

  And that, I think, inflated our egos in a way it shouldn't have because people started to say, yeah, yeah. It's just brute force search, but it has no intuition.

• 2:32:16Lex Fridman?

  Yeah.

• 2:32:17Max Tegmark?

  Alpha Zero really.

• 2:32:20Max Tegmark?

  Pop our bubble there.

• 2:32:23Lex Fridman?

  Yeah.

• 2:32:23Max Tegmark?

  Because what AlphaZero does, yes, it does also do some of that research. But it also has this intuition module, which in geek speak is called a value function. Where it just looks at the board and comes up with a number for how good is that position? The difference was no human told it how good the position is. It just learned it. And Mu zero is the coolest or scariest of all, depending on your mood. Because it, the same basic AI system will learn what the good board position is regardless of whether it's chess or Go or Shogi or Pac-Man or Lady Pac-Man or Breakout or Space Invaders

• 2:33:08Max Tegmark?

  or any number, a bunch of other games. You don't tell anything and it gets this intuition after a while for what's good. So this is very hopeful for science, I think, because if it can get intuition for what's a good position there, maybe it can also get intuition for what are some good directions to go if you're trying to prove something. If I often, one of the more most fun things in my science career is when I've been able to prove some theorem about something and it's very heavily intuition guided, of course. I don't sit and try all random strings. I have a hunch that, you know, this reminds me a little bit of about this other proof I've seen for this thing. So maybe I first, what if I try this? Nah, that didn't work out. But this reminds me actually, the way this failed reminds me of that.

• 2:33:53Max Tegmark?

  And so combining the intuition that with all these brute force capabilities, I think it's going to be able to help physics too.

• 2:34:04Lex Fridman?

  Do you think there'll be a day when an AI system being the primary contributor, let's say 90% plus wins the Nobel Prize in Physics?

• 2:34:15Lex Fridman?

  Obviously, they'll give it to the humans because we humans don't like to give prizes to machines. It'll give it to the humans behind the system. You could argue that AI has already been involved in some Nobel prizes, probably maybe something with black holes and stuff like that.

• 2:34:29Max Tegmark?

  Yeah, we don't like giving prizes to other life forms. If someone wins a horse racing contest, they don't give the prize to the horse either.

• 2:34:36Lex Fridman?

  That's true. But do you think that we might be able to see something like that in our lifetimes when AI? So like the first system, I would say, that makes us think about a Nobel Prize seriously is like AlphaFold. It's making us think about in medicine physiology, a Nobel Prize. Perhaps discoveries that are a direct result of something that's discovered by AlphaFold. Do you think in physics, we might be able to see that in our lifetimes?

• 2:35:07Max Tegmark?

  I think what's probably going to happen is more of a blurring of the distinctions. So today, if somebody uses a computer to do a computation that gives them the Nobel Prize, nobody's going to dream of giving the prize to the computer. They're going to be like, that was just a tool. I think for these things also, people are just going to, for a long time, view the computer as a tool. But what's going to change is that is the ubiquity of machine learning. I think at some point in my lifetime, finding a human physicist who knows nothing about machine learning

• 2:35:47Max Tegmark?

  is going to be almost as hard as it is today finding a human physicist who doesn't says, oh, I don't know anything about computers. Or I don't use math. It would just be a ridiculous concept.

• 2:35:59Lex Fridman?

  You see, but the thing is, there is a magic moment, though, like with AlphaZero, when the system surprises us in a way where the best people in the world.

• 2:36:12Lex Fridman?

  Truly learn something from the system in a way where you feel like it's another entity.

• 2:36:17Max Tegmark?

  Yeah.

• 2:36:18Lex Fridman?

  Like the way people, the way Magnus Carlsen, the way certain people are looking at the work of Alpha Zero. It's like, uh, it, it truly is no longer a tool in the, in the sense that it doesn't feel like a tool. It feels like some other entity. So there, there is a magic difference like where, where you're like, uh, you know, if an AI system is able to come up with an insight that surprises everybody in a some, uh, in some like major way that's a phase shift in our understanding of some particular science or some, some particular aspect of physics. I feel like that is no longer a tool.

• 2:36:58Lex Fridman?

  And then you can start to say, uh, that like it perhaps deserves the prize. So for sure, the more important, the more fundamental transformation of the 21st century science is exactly what you're saying, which is probably everybody will be doing machine learning. It's to some degree, like if you want to be successful at unlocking the mysteries of science, you should be doing machine learning. But it's just exciting to think about like, whether there'll be one that comes along that's super surprising and, uh, they'll make us question like who the real inventors are in this world.

• 2:37:35Max Tegmark?

  Yeah. Yeah. I think the question of isn't if it's going to happen, but when and, and, but it's important. Honestly, in my mind, the time when that happens is also more or less the same time when we get artificial general intelligence.

• 2:37:50Lex Fridman?

  Yes.

• 2:37:51Max Tegmark?

  And then we have a lot bigger things to worry about than whether it should get the Nobel Prize or not. Right?

• 2:37:56Lex Fridman?

  Yeah.

• 2:37:57Max Tegmark?

  Because when you have machines that can outperform our best scientists at science, they can probably outperform us at a lot of other stuff as well, which can at the minimum, you know, make them incredibly powerful agents in, in the world, you know? And I, I think that it's a mistake to think we only have to start worrying about loss of control when machines get to AGI across the board, where they can do everything, all our jobs. Long before that, they'll be hugely influential. We talked at length about how the, the hacking of our minds with them.

• 2:38:41Max Tegmark?

  Algorithms trying to get us glued to our screens, right, has already had a big impact on on society. That was an incredibly dumb algorithm in the grand scheme of things, right? Just supervised machine learning, yet it had had huge impact. So so I just don't want us to be lulled into a false sense of security and think there won't be any societal impact until things reach human level. Because it's happening already. And it's I was just thinking the other week, you know, when I see some scaremonger going, oh, the robots are coming. The implication is always that they're coming to kill us. Yeah. And maybe you should have worried about that if you were in Nagorno-Karabakh during the recent war there. But more seriously,

• 2:39:25Max Tegmark?

  the robots are coming right now, but they're mainly not coming to kill us. They're coming to hack us.

• 2:39:31Max Tegmark?

  They're they're coming to hack our minds into buying things that we maybe we didn't need to vote for people who may not have our best interest in mind. And and it's kind of humbling, I think, actually, as a human being to admit that it turns out that our minds are actually much hack more hackable than we thought. And the ultimate insult is that we are actually getting hacked by machine learning algorithms that are in some objective sense much dumber than us, you know? But maybe we shouldn't be so surprised because, you know,

• 2:40:03Max Tegmark?

  how do you feel about cute puppies? Love them. So, you know, you would probably argue that in some across the board measure, you're more intelligent than they are. But boy, are are cute puppies good at hacking us, right? Yeah. They move into our house, persuade us to feed them and do all these things. What do they ever do but for us? Yeah. Other than being cute and making us feel good, right? So if puppies can hack us, maybe we shouldn't be so surprised if. A pretty dumb machine learning algorithms can hack us too.

• 2:40:34Lex Fridman?

  Not to speak of cats, which is another level. And, and I think we should, to counter your previous point about their, let us not think about evil creatures in this world. We can all agree that cats are as close to objective evil as we can get. But that's just me saying that. Okay.

• 2:40:50Max Tegmark?

  Have you seen the cartoon? I think it's maybe The Onion, where this incredibly cute kitten, and it just says, um, underneath something that thinks about murder all day.

• 2:41:06Lex Fridman?

  Exactly. That's, that's accurate. You mentioned offline that there might be a link between post-biological AGI and SETI. So last time we talked, you've, you've talked about this intuition that we humans might be quite unique in our galactic neighborhood. Perhaps our galaxy, perhaps the entirety of the observable universe. We might be the only intelligent civilization here, which is, um, and you argue pretty well for that thought. So I have a few little questions around this. One, a scientific question.

• 2:41:50Lex Fridman?

  In which way would you be, if you were wrong in that intuition? In which way do you think you'd be surprised? Like, why were you wrong? You, we find out that you ended up being wrong. Like, in which dimension? So like, is it because we can't see them? Is it because the nature of their intelligence or the nature of their life is totally different than we can possibly imagine? Is it because the, I mean, something about the great filters and surviving them? Or maybe because we're being protected from signals?

• 2:42:34Lex Fridman?

  So all those explanations for, um, for why we haven't heard a big, loud, like, red light that says we're here.

• 2:42:45Max Tegmark?

  Yeah. So there are actually two separate things there that I could be wrong about. Two separate claims that I made, right? The, one, one of them is.

• 2:42:57Max Tegmark?

  I made the claim, I think, most civilizations, when you're going from simple bacteria-like things to space, space colonizing civilizations, they spend only a very, very tiny fraction of their, of their, of their life being where we are. That I could be wrong about. The other one I could be wrong about is a quite different statement that I think that actually, I'm guessing, that we are the only civilization in our observable universe from which light has reached us so far, that's actually gotten far enough to invent telescopes. So let's talk about maybe both of them in turn, because they really are different.

• 2:43:40Max Tegmark?

  The first one, if, if you look at the N equals one, the data point we have on this planet, right, so we spent four and a half billion years flexing around on this planet with life, right? We got, and most of it was pretty lame stuff from an intelligence perspective, you know, it's bacteria, and then the dinosaurs spent, then the things gradually accelerated, right? Then the dinosaurs spent over a hundred million years stomping around here without even inventing smartphones. And, and then very recently, you know, it's only, we've only spent 400 years going from Newton to us, right, in terms of technology, and we've, look what we've done even, you know,

• 2:44:25Max Tegmark?

  when I was a little kid, there was no internet even, so it's, I think it's pretty likely for, in this case of this planet, right, that we're either gonna really get our act together and start spreading life into space, the century, and doing all sorts of great things, or we're gonna, gonna wipe out. It's a little hard, if I

• 2:44:47Max Tegmark?

  I could be wrong in the sense that maybe what happened on this earth is very atypical. And for some reason, what's more common on other planets is that they spend an enormously long time futzing around with the ham radio and things, but they just never really take it to the next level for reasons I don't haven't understood. And I'm humble and open to that. But I would bet at least 10 to 1 that our situation is more typical because the whole thing with Moore's law and accelerating technology, it's pretty obvious why it's happening. Everything that grows exponentially, we call it an explosion, whether it's a population explosion or a nuclear explosion, it's always caused by the same thing. It's that the next step triggers a step after that.

• 2:45:27Max Tegmark?

  So I, we, tomorrow's technol, today's technology enables tomorrow's technology and that enables the next level. And as a thing, because the technology is always better, of course, the steps can come faster and faster. On the other question that I might be wrong about, that's the much more controversial one, I think. But before we close out on this thing about if, if the first one, if it's true that most civilizations spend only a very short amount of their total time in the stage, say, between inventing telescopes or like mastering electricity and leaving their, and doing space travel.

• 2:46:08Max Tegmark?

  If that's actually generally true, but then that should apply also elsewhere out there. So we should be very, very, we should be very, very surprised if we find some random civilization and we happen to catch them exactly in that very, very short stage. It's much more likely that we find this planet full of bacteria.

• 2:46:27Lex Fridman?

  Yes.

• 2:46:28Max Tegmark?

  Or that we find some civilization that's already post-biological and has done some really cool galactic construction projects in their, in their galaxy.

• 2:46:38Lex Fridman?

  Would we be able to recognize them, do you think? Is it possible that we just can't? I mean, this post-biological world, could it be just existing in some other dimension? It could be just all a virtual reality game for them or something? I don't know that, that it changes completely where we won't be able to detect.

• 2:46:57Max Tegmark?

  We have to be honestly very humble about this. I think that I said, I think I said earlier, the number one. Principle of being a scientist is you have to be humble and willing to acknowledge that everything we think, yes, might be totally wrong. Of course, you could imagine some civilization where they all decide to become Buddhists and very inward looking and just move into their little virtual reality and not disturb the flora and fauna around them and we might not notice them. But this is a numbers game, right? If you have millions of civilizations out there or billions of them, all it takes is one with a more ambitious mentality that decides, hey, we are gonna go out and settle

• 2:47:39Max Tegmark?

  a bunch of other solar systems and maybe galaxies. And then it doesn't matter if they're a bunch of quiet Buddhists, we're still gonna notice that expansionist one, right? And it seems like quite the stretch to assume that, you know, we know even in our own galaxy that there are probably a billion or more planets that are pretty Earth-like. And many of them were formed over a billion years before ours, so had a big head start. So if you actually assume also that life happens kind of automatically on an Earth-like planet, I think it's pretty, quite the stretch to then go and say, okay, so we are there billions of, another billion civilizations out there that also have our level of tech

• 2:48:22Max Tegmark?

  and they all decided to become Buddhists. And not a single one decided to go like, go Hitler on the galaxy and say, we need to go out and colonize or, and not a single one decided for more benevolent reasons to go out and get more resources. That, that seems, seems like a bit of a stretch frankly. And this leads into the, the second thing you challenged me to be, that I might be wrong about, how rare or common is life? You know? So Francis Drake, when he wrote down the Drake Equation, multiplied together a huge number of factors and then we don't know any of them, so we know even less about what you get when you multiply together that whole product. Since then, a lot of those factors have become much better known.

• 2:49:04Max Tegmark?

  One of his big uncertainties was, how common is it that a solar system even has a planet?

• 2:49:09Lex Fridman?

  Right.

• 2:49:10Max Tegmark?

  Well, now we know it's very common.

• 2:49:11Lex Fridman?

  Earth-like planets, we know we have better.

• 2:49:14Max Tegmark?

  There are a dime a dozen, there are many, many of them, even in our galaxy. At the same time, you know, we have, thanks to, I'm a big supporter of the SETI Project and its cousins, and I think we should keep doing this and we've learned a lot. We've, we've learned that so far, all we have is still. Unconvincing hints, nothing more, right? And, and there are certainly many scenarios where it would be dead obvious. If there were a hundred million other human-like civilizations in our galaxy, it would not be that hard to notice some of them with today's technology, and we haven't, right? So, so what we can, what we can say is, well, okay. We can rule out that there is a human-level civilization on the moon, and in fact, the

• 2:49:59Max Tegmark?

  many nearby solar systems where we, we cannot rule out, of course, that there is something like Earth sitting in a galaxy five billion light-years away. But we've ruled out a lot, and that's already kind of shocking, given that there are all these planets there, you know? So like, where are they? Where are they all? That's the, that's the classic Fermi paradox. Yeah. And, and so, so my argument, which might very well be wrong, is very simple, really. It just goes like this. Okay, we have no clue about this. It could be the, the probability of getting life on a random planet, it could be 10 to the minus one, a priori, or 10 to the minus five, 10, 10 to the minus 20, 10 to the minus 30, 10 to the minus 40.

• 2:50:44Max Tegmark?

  Basically, every order of magnitude is about equally likely. When, then do the math and ask how close is our nearest neighbor? It's again equally likely that it's 10 to the 10 meters away, 10 to 20 meters away, 10 to the 30 meters away. We can, we have some nerdy ways of talking about this with Bayesian statistics and a uniform log prior, but that's irrelevant. This is the simple, basic argument. And now comes the data, so we can say, okay, how many were, there are all these orders of magnitude. 10 to the 26 meters away, there's the edge of our observable universe. If it's farther than that, light hasn't even reached us yet. If it's less than 10 to the 16 meters away, well, it's.

• 2:51:25Max Tegmark?

  Within Earth's range, it's no farther away than the sun. We can definitely rule that out, you know. So I think about it like this, a priori, before we looked through telescopes, you know, it could be 10 to 10 meters, 10 to 20, 10 to 30, 10 to 40, 10 to 50, 10 to blah blah, equally likely anywhere here.

• 2:51:43Lex Fridman?

  Yeah.

• 2:51:45Max Tegmark?

  And now we've ruled out like this chunk.

• 2:51:48Lex Fridman?

  Yeah.

• 2:51:49Max Tegmark?

  And.

• 2:51:49Lex Fridman?

  Most of it is outside.

• 2:51:50Max Tegmark?

  And here is the edge of our observable universe already.

• 2:51:53Lex Fridman?

  Yep.

• 2:51:54Max Tegmark?

  So I'm certainly not saying I don't think there's any life elsewhere in space. If space is infinite, then you're basically 100% guaranteed that there is. But the probability that there is life, that the nearest neighbor, it happens to be in this little region between where we would have seen it already.

• 2:52:12Lex Fridman?

  Yeah.

• 2:52:13Max Tegmark?

  And where we will never see it, there's actually significantly less than one, I think. And, and I think there's a moral lesson from this, which is really important, which is to be good stewards of this planet and this shot we've had, you know, it can be very dangerous to say, oh, you know, it's fine if we nuke our planet or ruin the climate or mess it up with unaligned AI, because I know there is this nice Star Trek fleet out there, they're going to swoop in and.

• 2:52:41Lex Fridman?

  Yeah.

• 2:52:42Max Tegmark?

  Take over where we failed, just like it wasn't the big deal that the Easter Island losers wiped themselves out. It's a dangerous way of lulling yourself into false sense of security. If it's actually the case that it might be up to us and only us, the whole future of intelligent life in our observable universe, then I think it's both, it really puts a lot of responsibility on our shoulders.

• 2:53:08Lex Fridman?

  Inspiring, it's a little bit terrifying, but it's also inspiring.

• 2:53:12Max Tegmark?

  But it's empowering, I think, most of all, because, because the biggest problem today is, I see this even when I teach, right? So many people feel that it doesn't matter what they do or we do, we feel disempowered. Oh, it makes no difference.

• 2:53:28Max Tegmark?

  This is about as far from that as you can come. I mean, we realize that what we do on our little spinning ball here in our lifetime, could make the difference for the entire future of life in our universe. How empowering is that?

• 2:53:44Lex Fridman?

  Yeah, survival of consciousness. I mean, on the other, a very similar kind of empowering aspect of the Drake equation is, say there is a huge number of intelligent civilizations that spring up everywhere. But because of the Drake equation, which is the lifetime of a civilization, maybe many of them hit a wall. And just like you said, it's clear that that, for us, the great filter, the one possible great filter seems to be coming in the next 100 years. So it's also empowering to say, okay, well, we have a chance to not. I mean, the way great filters work, it does get most of them.

• 2:54:27Max Tegmark?

  Exactly. Nick Bostrom has articulated this really beautifully too. Every time yet another search for life on Mars comes back negative or something, I'm like, yes, yes. Our odds for us surviving.

• 2:54:41Lex Fridman?

  Yes.

• 2:54:42Max Tegmark?

  You already made the argument in broad brush there, right? But just to unpack it, right? The point is, we already know there is a crap ton of planets out there that are Earth-like. And we also know that most of them do not seem to have anything like our kind of life on them. So what went wrongs? There's clearly one step along the evolutionary, at least one filter, roadblock, in going from no life to spacefaring life. And where is it? Is it in front of us or is it behind us, right? If there's no filter behind us and we keep finding all sorts of life. Of little mice on Mars and or whatever, right?

• 2:55:27Max Tegmark?

  That's actually very depressing because that makes it much more likely that the filter is in front of us. And that what actually is going on is like the ultimate dark joke that that whenever a civilization invents sufficiently powerful tech, it just you just set your clock and then after a little while it goes poof for one reason or other and wipes itself out. Now, wouldn't that be like utterly depressing if we're actually doomed? Whereas if it turns out that there is a really, there is a great filter early on that for whatever reason seems to be really hard to get to the stage of sexually reproducing organisms or even the first ribosome or whatever, right?

• 2:56:08Max Tegmark?

  Or or maybe you have lots of planets with dinosaurs and cows, but for some reason they tend to get stuck there and never invent smartphones. All of those are huge boosts for our own odds because been there, done that, you know? It doesn't matter how hard or unlikely it was that we got past that roadblock because we already did. And then then that makes it likely that the future is in our own hands. We're not doomed. So that's why that's why I think the fact that that life is rare in the universe, it's not just something that there is some evidence for, but also something we should actually hope for.

• 2:56:50Lex Fridman?

  So that's the the end, the mortality, the death of human civilization that we've been discussing in life, maybe prospering beyond any kind of great filter. Do you think about your own death? Does it make you sad that you may not witness some of the, you know, you lead a research group on working some of the biggest questions in the universe, actually, both on the physics and the AI side? Does it make you sad that you may not be able to see some of these exciting things come to fruition that we've been talking about?

• 2:57:25Max Tegmark?

  Of course, of course, it sucks the fact that I'm gonna die. I remember once when I was much younger, my dad made this remark that life is fundamentally tragic. And I'm like, what are you talking about, Daddy? Many years later, I felt now I feel I totally understand what he means. You know, we grow up, we're little kids and everything is infinite and it's so cool. And then suddenly that we find out that actually, you know. You got to certainly, this is, you're gonna get game over at some point. So of course, it's, it's, it's, um. It's something that's sad.

• 2:58:01Lex Fridman?

  Are you afraid?

• 2:58:08Max Tegmark?

  Not, not in the sense that I think anything terrible is gonna happen after I die or anything like that. No, I think it's really gonna be game over. But it's more that, um.

• 2:58:20Max Tegmark?

  It makes me very acutely aware of, I just have what a wonderful gift this is that I get to be alive right now. And, and is a steady reminder to just live life to the fullest and really enjoy it. Because it is finite, you know? And I think actually, and we know, we all get the regular reminders when someone near and dear to us dies. That, that, um.

• 2:58:43Max Tegmark?

  You know, one day it's, it's gonna be our turn. It adds this kind of focus. I wonder what it would feel like, actually, to be an immortal being. If, if they might even enjoy some of the wonderful things of life a little bit less. Just because.

• 2:58:57Max Tegmark?

  There isn't that, um.

• 2:58:59Lex Fridman?

  Finite-ness?

• 2:58:59Max Tegmark?

  Yeah.

• 2:59:00Lex Fridman?

  Do you think that could be a feature, not a bug? The fact that we. Beings are finite. Maybe there's lessons for engineering and artificial intelligence systems as well. That are conscious. Like, do you think it makes?

• 2:59:17Lex Fridman?

  Is it possible? That the reason the pistachio ice cream is delicious? Is the fact that you're going to die one day? And you will not have? All of the pistachio ice cream that you could eat? Because of that fact?

• 2:59:31Max Tegmark?

  Well, let me say two things. First of all, I, it's actually quite profound what you're saying. I do think I appreciate the pistachio ice cream a lot more, knowing. That I will, there's only a finite number of times I get to enjoy that. And I can only remember finite number of times in the past. And moreover, my, my life is not so long that it just starts to feel like things are repeating themselves in general. It's so new and fresh. I also think, though, that.

• 2:59:59Max Tegmark?

  Death is a little bit overrated in the sense that

• 3:00:05Max Tegmark?

  it comes from a sort of outdated view of physics and what life actually is. Because if you ask, okay, what is it that's gonna die exactly? What am I really? When I say I feel sad about the idea of myself dying, am I really sad that this skin cell here is gonna die? Of course not, because it's gonna die next week anyway, and I'll grow a new one, right? And it's not any of my cells that I'm associating really with who I really am, nor is it any of my atoms, or quarks, or electrons.

• 3:00:41Max Tegmark?

  In fact, basically, all of my atoms get replaced on a regular basis, right? So what is it that's really me? From a more modern physics perspective, it's the information.

• 3:00:52Max Tegmark?

  And processing in me, that's where my memory, that's my memories, that's my values, my dreams, my passion, my love.

• 3:01:05Max Tegmark?

  It's, that's what's really fundamentally me. And frankly, not all of that will die when my body dies. Like Richard Feynman, for example, his body died of cancer, you know? But many of his ideas that he felt made him very him actually live on. I, this is my own little personal tribute to Richard Feynman, right? I try to keep a little bit of him alive in myself. I've even quoted him today, right?

• 3:01:35Lex Fridman?

  Yeah, he almost came alive for a brief moment in this conversation, yeah.

• 3:01:38Max Tegmark?

  Yeah, and this honestly gives me some solace. You know, when I work as a teacher, I feel if I can actually share a bit about myself, that my students feel worthy enough to copy and adopt as some part of things that they know, or they believe or aspire to, now I live on also a little bit in them, right? And I, so being a teacher is a little bit of what I

• 3:02:14Max Tegmark?

  That's something also that contributes to making me a little teeny bit less mortal, right? Because I'm not, at least not all gonna die all at once, right? And I find that a beautiful tribute to people we didn't respect. If we can, if we can remember them and carry in us the things that we felt was the most awesome about them, right? Then they live on.

• 3:02:40Max Tegmark?

  And I'm getting a bit emotionally here, but it's a very beautiful idea you bring up there. I think we should stop this old fashioned materialism and just equate who we are with our quirks and electrons. Nah, there's no scientific basis for that, really. And it's also very uninspiring.

• 3:03:02Max Tegmark?

  Now, if you look a little bit towards the future, right? One thing which really sucks about humans dying is that even though some of their teachings and memories and stories and ethics and so on will be copied by those around them, hopefully, a lot of it can't be copied and just dies with them, with the brain. And that really sucks. That, that's the fundamental reason why we find it so tragic. When someone goes from having all this information there to just gone, ruined, right? With, with more post biological intelligence, that's gonna shift a lot, right? The only reason it's so hard to make a backup of your brain in its entirety is exactly because it wasn't built for that, right?

• 3:03:47Max Tegmark?

  If you have a future machine intelligence, there's no reason for why it has to die at all. If it wants to up, if you want to copy it, whatever is it into some other quirk blob, right? You can copy not just some of it, but all of it, right? And so, so in that sense.

• 3:04:10Max Tegmark?

  You can get immortality because all the information can be copied out of any individual entity. And it's not just mortality that will change if we get to more post-biological life. It's also the, with that, I think, very much the whole individualism we have now, right? The reason that we make such a big difference between me and you is exactly because we're a little bit limited in how much we can copy. Like, I would just love to go like this and copy your Russian skills, Russian-speaking skills.

• 3:04:42Lex Fridman?

  Yeah.

• 3:04:43Max Tegmark?

  Wouldn't it be awesome? But I can't. I have to actually work for years if I want to get better on it. But if you have, if we were robots.

• 3:04:52Lex Fridman?

  Just copy and paste freely, then that loses completely, it washes away the sense of what immortality is.

• 3:05:00Max Tegmark?

  And also individuality a little bit, right? We would start feeling much more, maybe we would feel much more collaborative with each other if we can just, hey, you know, I'll give you my Russian, you can give me your Russian and I'll give you whatever. And suddenly you can speak Swedish. Maybe that's less a bad trade for you, but whatever else you want from my brain, right?

• 3:05:19Lex Fridman?

  Yeah.

• 3:05:20Max Tegmark?

  And there have been a lot of sci-fi stories about hive minds and so on, where people, where experiences can be more broadly shared. And I think, one, we don't, I don't pretend to know what it would feel like to be a super-intelligent machine, but I'm quite confident that however it feels about mortality and individuality will be very, very different from how it is for us.

• 3:05:49Lex Fridman?

  Well, for us, mortality and finiteness seems to be pretty important at this particular moment, and so all good things must come to an end, just like this conversation.

• 3:06:04Max Tegmark?

  I saw that coming.

• 3:06:05Lex Fridman?

  Sorry, this is the world's worst translation. I could talk to you forever. It's such a huge honor that you spend time with me.

• 3:06:14Max Tegmark?

  Honor is mine.

• 3:06:15Lex Fridman?

  Thank you so much for getting me essentially to start this podcast by doing the first conversation, making me realize falling in love with conversation in itself. And thank you so much for inspiring so many people in the world with your books, with your research, with your talking and with the other, like this ripple effect of friends, including Elon and everybody else that you inspire. So, thank you so much for talking today.

• 3:06:43Max Tegmark?

  Thank you. I feel so fortunate that you're doing this podcast and getting so many interesting voices out there into the ether and not just the five second soundbites, but so many of the interviews I watch you do, you really let people go in into depth in a way which we sorely need in this day and age and that I got to be number one, I feel super honored.

• 3:07:07Lex Fridman?

  Yeah, you started it. Thank you so much, Max. Thanks for listening to this conversation with Max Tegmark and thank you to our sponsors, The Jordan Harbinger Show, Four Sigmatic Mushroom Coffee, BetterHelp Online Therapy, and ExpressVPN. So the choice is wisdom, caffeine, sanity, or privacy. Choose wisely, my friends, and if you wish, click the sponsor links below to get a discount and to support this podcast. And now let me leave you with some words from Max Tegmark. If consciousness is the way that information feels when it's processed in certain ways, then it must be substrate independent.

• 3:07:49Lex Fridman?

  It's only the structure of information processing that matters, not the structure of the matter doing the information processing. Thank you for listening and hope to see you next time.