AI Has Free Will? (ft. Sabine Hossenfelder)

Does free will exist? It's a question that's haunted philosophers for centuries. But physicist Sabine Hassenfelder has a provocative answer that might just disturb you. He says, free will doesn't exist.

People just go, what do you mean by free will? And I was trying to say, well, it doesn't really matter, because what I'm talking about is, like, what do we know about the laws of physics? And why is it so hard to make sense of this, like, on a personal level, if you know that your brain is made of particles and we know the laws that those particles are.

Ruled by, everything is determined by the laws of physics. But here's the paradox that's fascinated me. I've talked to Sam Harris, Dan Dennett, Robert Sapolsky, all brilliant minds who agree that free will is an illusion. Yet when I asked them if they've ever encountered someone who acts like they don't have free will, they all said no. How can we all be determined by physics, yet live as if we're making genuine choices? This isn't some abstract philosophical exercise.

No.

Sabine's insight has real implications for artificial intelligence, quantum computing. In the future of consciousness, she explains why I may already have the same kind of agency that we do and why quantum computers could reveal that we fundamentally misunderstand the nature of reality.

Sabina, it's so great to see you again after more than a year. I don't think we talked very much in 2024, so it's great to see you.

Good to see you, Brian.

You've been had a wonderful video yesterday, day before, about this thought that changed your life. And to me, I was a little depressed because it seemed to say that, you know, everything is phys and everything is determined, and therefore, you know, you should maybe naively not be happy, but you turned out to be very happy. So can you explain what determinism is? Because, Sabina, I've talked to everybody. I've talked to Sam Harris, I've talked to you, I've talked to Dan Dennett, the late Dan Dennett, his final podcast. I've talked to Robert Sapolsky. They all say free will doesn't exist. And yet I say, have you ever met somebody who acts like they believe that they don't have free will? And they all say no. So how can it be that we don't have free will, but everybody acts like we have free will?

Well. Well, it all depends on what you mean by free will. So if you watch my video, you'll have noticed that I avoided using the word this. Is why I was talking about determinism, because otherwise people just go, what do you mean by free will? And I was trying to say what doesn't really matter? Because what I'm talking about is like, what do we know about the laws of physics? And why is it so hard to make sense of this? Like on a personal level, if you know that your brain is made of particles and we know the laws that those particles are ruled by. Right. So where's my place in this now? You said I seem to be happy about it, but really it was more like I was unhappy before. So I was trying to solve a problem and I finally succeeded. So, so what I talked about in the video was that I finally eventually managed to shift my point of view on myself basically and make made peace with knowing that everything is determined up to this random element.

And I read Sam Harris book, which, you know, this, it's only like 460 pages or something. And I agreed with everything except for the one paragraph he wrote about physics. So. But yeah, otherwise it, you know, I think he's right. I think what the disagreement mostly is about is what people even mean by free will, which is what. Which is exactly why I don't like to talk, talk about it. I just think it's a nonsense term. Like even the combination of free and will doesn't really make sense.

Like so, so if you think you're your will determines your decisions, then it's not free. Like that's the entire point of having a will, that you, you make the decision. Right. So, so, so what I was trying to get at in the video is that I began to think of myself as an information processing thing basically that goes through the world. And I think it's, it's made me more aware the information that I consume and how much it affects me. So that was my point. And so of course this entire question of free will is becoming more and more relevant with artificial intelligence that is rapidly coming into the world more and more powerful and people starting to ask like, does it have free will? At which point do we agree that it has free will and is worth protecting on some level?

Sam Harris says it will have free will or already does. So how do you react to that? I mean, how can you say that? You know, free will as a concept doesn't exist. When we think of AI, at least as you know, for now, as, you know, as running on GPUs and with large language models with billions of tokens, how can it be possible that it could be even said to have that. If, if, if we're determined, then certainly the determiner of the programmer of the AI must, must be in some super, you know, superposition, you know, super above the AI level. Do you agree with him, first of all, that I can be said to have free will modulo the fact that we can't define it?

Yeah, well, I say I doesn't have free will exactly the same way that we don't have free will, because in both cases it's, it's determined. But I think there is still at this point a measurable degree of differ. So I think the most compatible definition of free will that I know is the idea that it's got something to do with agency. You have a system. How much of the behavior of the system is determined by the external inputs and how much of it comes from some internal complicated deliberation about what's going on. And I think it's, you know, even if you can't, you know, rigorously quantify it, like, I mean, you know, philosophers, right, it's not like they write down an equation and then say you can calculate your amount of free will using this formula. I mean, that would be nice. But we're not quite there yet.

But. So even on this vague level, you can say, yeah, I think humans have more free will than a phone. And AI at the moment is somewhere in between, right? It's clearly doing more than a phone where you push a button and it pops up a window or something. It's not that simple. But it's also much more constrained than humans because it's still very apparent what kind of prompt they're working off. Like they're not really doing their own thing. So they're doing a few of those things. Which is why philosophers, I think, are arguing over it.

Like with AI agents coming online, they're setting their own goals and producing a plan. And then they work off this plan and they think about the plan and then they revise it and it's going to get more complicated along those lines. And so I think it's a valid question to ask, but personally I'd say, like, it's a very, very low level of free will.

I wonder if you could say in German for me what Einstein said in 1907. He said the following was his happiest thought, that here he is on the finger puppet level. He said if he was in free fall, that he would experience no gravitational force. Can you say it was the happiest thought of my life? Because that's what he said. That's what he called that realization the Einstein equivalence. Can you say it was the happiest thought of my life in German?

Glucose to danke minus limbs. So, so now it might be that I mistranslated back something that was mistranslated into English in the first place. So I'm not exactly sure that this is the right quote, but you said something along those lines for sure. Yeah. And so you want me to explain the, the elevator experiment or, well, thought experiment?

No, not really. I want to, I want to pivot to what would it mean for a computer or an AI to have a happy thought? And furthermore, could an AI have such a thought because it doesn't have a body? And so we wouldn't know what that sensation of freefall that Einstein visualized and felt viscerally, how can a computer have a happy thought? And how could it visualize what freefall feels like in order to replicate and be an AI Ae, you know, an artificial intelligent Albert Einstein.

Yeah, well, that's a very good point. So like there's this question, will AI ever become truly intelligent without actually having a body? Like, do you actually need to put it into a robot? There are two answers that I have to this. One thing is you can simulate, simulate a robot walking around in the virtual reality. And, and so it doesn't actually need a physical robot, just like a simulation of it, if you see what I mean. And, and people are already doing this. Like this is a thing like if, if you want to, if you want to train your robot, you don't, you don't let it walk stairs up and down for a billion years. You, you squeeze that billion years into a few days on a supercompute and let it learn to walk stairs in a virtual reality. So that, that's already, already a thing.

The other thing is that I, I gen, generally I believe it to be possible, like you could reach human level intelligence with the lucky thoughts and, you know, genuine insights about reality without the direct sensory input from physical reality. But I believe it would take a very long time because if you think about it like, it also took humans a very long time to, to become as intelligent as we are now. Right? So any, this is what you want to avoid. You, you want to get that fast, right? And so this is why I believe that the most likely way we'll reach human level intelligence is by some sort of access to the real world so that they can learn what it actually means to interact with something. Or if you want to use the causal model approach, you need to be able to interfere with certain causal relations, to figure out how they work. And we basically do this from the day we're born or even before that, who knows? And so I think this is going to be a real game changer. You know, once we have robots walking around, they're going to collect their own data, they're going to create their own models of the world, but much more efficiently than we could have done. You also asked about happiness.

Like, can AIs have an emotion? Well, again, at the moment, I think the answer is no, not in any reasonable meaning of the word. But you always have to ask, like, what do we actually mean by this? Like, so, so for us, happiness evolved as a reward function, right? It's the, it's the response to doing something, right? So, so you, you got a good meal, that's good. It's going to help you survive. Dopamine.

Yeah, the dopamine hit. We have to have robot. Robotamine or something for the robots to have, right?

And it's, and, and of course, AI already has a reward function, right? So it has the, it has the root of it because it needs that to learn. And the newer models are also learning to improve themselves by way of a proper reward function. And I think at some point that'll be very similar to a particular emotion, in this case happiness. And then you can ask, well, what about all the other emotions? And then, you know, we have to talk about, like, will they actually have different sort of. Yeah, pain. Right. And will they have different emotions? Like, will AI have emotions that we don't have that we can't even relate to? I don't know. I have no idea.

Like, it's, it's also. You could also ask this question about aliens, right? So if aliens have emotions, do they have the same emotions? Do they have different emotions that we won't be able to relate to? Well, who knows? I have no idea.

What do you, what do you make of all the alien, you know, kind of sightings that are in the zeitgeist as, as you might say, what do you make of these, you know, claims by respected, you know, military personnel, mostly in America, by the way. But what do you make of it? As a physicist, I mean, wouldn't you be happy if this were tr. Could learn the laws of the 23rd century today?

Totally. Like, I would love to see intelligent life from other planets within my lifetime because they've got to have, like, if they manage to travel here, they must have more advanced technology than we have. Like, they could probably help us solve many Problems, answer many questions, and so on and so forth. I was just, you know, chatting about this with Kurt the other day. It's a difficult topic because I think that a lot of what people talk about is incredibly flaky and it's nonsense. And on the other hand, I think we shouldn't just dismiss everything because if we make a mistake with that, it's going to be a huge mistake. And I think it's. You know, I think it's actually possible that there's intelligent life out there and it sends some probes into the galaxy like we are planning to do, and maybe one of those arrived here and fell into the ocean.

You know, that. That seems totally possible to me. That doesn't mean that I actually believe we found one. So. And so I'm a little bit unhappy with the situation that we're in in which everyone who talks about UFOs or UAPs or whatever you want to call it now, you know, it kind of moves themselves into that because I think we need to take this more seriously. Also, I have to say, if you listen to any of these Congress or Senate debates that they did, there's this one guy from NASA. The guy from NASA, every time, basically he gets to say something. He basically says, oh, and by the way, we need more funding.

He got the assignment. Right. And actually, speaking of assignments, you have this wonderful product or service, actually it's free, called Quiz With It. Right. I want to ask you about AI education. First of all, do you use AI in Quiz With It? Is there going to be a job for people like me in 40 years? A professor, you know, standing up in front of a bunch of students with a piece of rock and scraping on another piece of rock, and then they're listening and. Or is this going to be my avatar talking to their avatar? Or better yet, you're a better explainer than I am. Why can't they take quantum mechanics with you instead of with me? Or how about they take it with Bohr, Schrodinger, you know, Heisenberg, et cetera, or learn GR from good old Einstein himself? So what's the future of education in the age of AI? Will professors like me have a job? Please say yes.

And how do you use Quiz with It? How does Quiz with it use AI and give a little plug or talk about Quiz with It, please, in case my audience.

Okay, yeah. So Quiz with it is a platform that I developed together with a team of software engineers. And yes, we do use AI. We have a GPT link. And so the way that it works is that it'll automatically create questions with answers on any topic that you enter. So you can just enter the topic and then you'll get questions with answers, or you can be more specific about it and you can actually enter some text of some, I don't know, blog post or something. You can also just enter the link and will pull down the text automatically. Or you can, and this is what I do.

You can use a YouTube video and we'll, we'll pull down the transcript and then we'll generate questions from this and you can quiz yourself on it, whether you actually understood it, whether you remember it correctly. And so the reason I did this was that, I mean, there are lots of quiz apps out there, but none of them actually did what I wanted to do. I wanted users to be able to collect points from taking multiple of my quizzes and also for other creators to be able to do, do the same. So that was basically the idea. Now there's this broader question of what's AI going to do to education? And I think that's a really big topic at the moment because that's really a sector where AI can have a huge impact. And it's already having an impact. And the question is, like, where will it go? I mean, at the moment it's very hard to tell. I think in the end it'll come down to how much do we value human interaction? Right? So, like, I mean, so, so this example you had, like, can students learn physics from Einstein or Bohr? I think the answer is probably no, because we don't have enough material to, to train the AIs on.

Like, there are only so many recordings from a century ago.

Oh, but we have, I mean, Einstein wrote a million, 2 million words. I mean, I have Galileo's, all of his writings on the dialogue, which is about a hundred, eight hundred thousand words. We recorded an audiobook with Carlo Rovelli and Frank Wilczek and others. There's plenty of written material. Right. We'll never get Galileo's voice, but I don't think we need it.

Yeah, but when these people write their academic papers, that's not like 100 who they really were. So like, like if you write a paper and then you were to talk about it, it's not exactly the same. This is what I mean. Like, so we can try to reconstruct an approximation to who Einstein might have been, but I think it wouldn't be even close to the real thing because we're just missing too much. Like most of the real Einstein is Lost because we don't have any recordings of it. And the people who knew him personally are dead and that's that. And it's a shame, but this is probably somewhat tangential because who would know the difference anyway, right?

And am I really myself when I'm teaching? I mean, I'm, you know, I'm different than I am with my kids. Right? I mean, what is the whole you. And, but the core question I have is, you know, is, is this going to take one of the jobs? You know, people are always worried about AI taking jobs away from people, from actual, you know, human people. And it seems to me that this would be one of the simplest things to take away. Right? I mean, my students sit there in class and I do things differently because I do experiments and I do flipping, you know, where we solve problems together and I work around with them. But, but you know, there are other professors. Don't let them use AI. I make them use AI because I think it's going to be a tool.

It's like not letting them use, you know, a computer was. Or a spreadsheet, you know, 20 years ago. It's crippling them. And so, but, but the question is, you know, if we could have this a. You know, these education companies that are basically what universities are. I mean, the third most important thing that universities do, according to Isadore Rabbi, was, you know, to teach. Like it was getting fun or doing research, getting money. We'll talk about that later, I hope with modern academia in trouble.

But, but yeah, I mean, why, why learn, you know, just quantum mechanics? Forget about like, do I get their whole self? Do I get their whole personnel? Of course not. But, but can I learn quantum mechanics from an AI holographic? You know, I mean, think, think big. What is it going to look like in 20 years? I mean, do we need professors to teach? Why can't we just do research?

Yeah, I, I think it's definitely going to take over a lot of these education jobs. And I mean, look, I'm, I'm sure you'. And I mean, I've seen you, you know, your examples in your videos. Like, I've never been in your lecture, but I can kind of extrapolate from that. And I'm pretty sure you do great lectures. Many of my professors were not particularly good and I'm pretty sure I'd have been better off with even today's AIs just because they would have been more, you know, more personalized in some sense. They would have been more attentive to work what, what problems I am facing rather than just, you know, writing down their lectures and, and, and not caring if anyone even listens. And, and, and so this is why I, I think that there's for real, you know, a lot of those people who don't really care about teaching and, and, you know, do it because they have to, are going to be replaced with AI.

And, but I mean, there is the question, like, how much does this human element matter? And I think that there's going to be like a long tail where humans can do things that are irreplaceable for a long time. So I think, like, personally, you don't need to worry about it, but maybe some people have to worry about it.

I kind of want to parlay that into a question about what AI can't do in a certain sense or may not be able to do. And I'd love to get your opinion about this. So there's this phenomenon called lock in. I don't know. Have you ever heard of lock in? It's basically the first technology. Oops, sorry.

Yeah, right. You mean computer development.

Yeah, so that's in computer development. There's also, you know, there's an example, allegedly the space shuttle, for example, the Hubble Deep field was only taken because of the width of two horses, rear ends. Have you ever heard this described before, Sabina?

No.

Okay, we'll see if you, if you think I'm a good teacher after this. Okay, so the original chariots and roads in Rome were governed by the width of the horses that were the form of locomotion. Right. A chariot would be pulled by two horses and that eventually became the width of a standard rail gauge on a train. So the gauge is the separation of rail tracks. Right. In the United States, when they were building the space shuttle, the rocket boosters that would launch the space shuttle, the solid rocket boosters back then were made in Utah, which is in the western US and they had to be transported to Florida, where the space shuttle was launched from. To get there, the engineers knew they had to get through three tunnels, three train tunnels.

And so the width of the rocket, which determines the specific impulse that it can impart, which determines the maximum altitude of the space shuttle, which carried the Hubble telescope, can be traced to the width of a horse's butt back in Roman times. Okay, so that's an example of lock in. The technology the Hubble Deep Field has nothing to, but it was set by something different. I want to ask you the following question. We have very good LLMs and GPUs they're married together. It's beautiful. They're doing something very special. Is there a danger in that they're so good at what they do that they're only going to be good at what they do like that.

And they're not going to be able to do specific tasks other than language perhaps very well. Because they were originally designed for video games. I mean GPUs were designed for video games and the neural nets were designed for mimicking human brain activity. And I've got the brain of one of my arch competitors here. This. Yeah, this is someone's brain that we don't like. But, but are we prisoning our imprisoning ourselves because of the success of GPUs +LLMs, is it going to limit our ability to do new physics for example?

Well, so there are actually, I mean people are producing processes that are, are particularly well adapted to neural nets and they're actually called npus I think neuroprocessing units. And you can push this even further. Like people try to actually how the human brain works by actually using physically changeable connections to encode the weights and so on. So there's a whole industry behind this. So I don't direct see this worry, but I do see the worry. This locked in issue is often a problem if you, if you look at the basis, it's an economic problem like so because you know, if you want to transport this thing, you're not going to rebuild the entire railroad system and all the tunnels like you could do it, but that'd be insane. And we have the same problem like for example, why is it so hard to get off fossil fuels? Whereas because our entire economy is built around it. Like this saws a locked in problem.

And you could say well it would have been more sensible to build battery powered cars much earlier, but we didn't. So we're stuck with it. And now we'll have to invest a lot of money to get out of it and onto a bigger maximum basically. So yeah, this problem is everywhere. So if you look at the current large language models, they're facing a big problem there which is that they've invested like hundreds of millions of dollars into building these models. So that makes it very hard to say, okay, let's forget about large language models, we need to do something entirely different because then they'll have to start all over. So they have a huge bias on trying to tweak these models a little bit to make them a little bit better to get to local maximum. If you see the Visual I have in mind, whereas you might have a much higher maximum after you've crossed the valley and put in a lot of money.

But I think that this is going to be a problem for specific companies. So what I think is going to happen is you're going to have new Companies which develop AIs based on a new system. We can speculate about exactly what this would be and then they're going to overtake the large language models very, very quickly at some point. We're not at this point and it might be a few years off, but I think that's what's going to happen. So it's quite interesting like, so no one really knows like what GPT5 is actually going to be like. So I've just heard people say it's going to be different than the other ones. So no one really knows what they're working on. Right.

And so also if you look at companies like Meta, Google, DeepMind, they're actually doing a lot of different things. So I think they're risk averse. So I think they see it coming that large language models aren't going to get us all the way to AGI. So we need something else. And they're trying to figure out what that something else is.

You made a wonderful video recently about quantum computing and I wonder if I could provoke you to respond to this kind of snide comment that I like to make about quantum computing, that quantum computers are great at simulating quantum computers and breaking encryption. But essentially those two use cases which were predicted by Feynman and others back in the 80s, between those two narrow use cases, do you think the promises of quantum supremacy and other things are overblown? Or do you think that there's still potential that justifies the hype and that they're not, as I call them, two trick ponies.

I think it's always useful to look at who puts money into these things. And I think it's quite telling that there are lots of banks and similar insurance companies and so on interested in that kind of stuff. And why is that? Because one of the applications that they want to put on a quantum computer are some of those optimization problems that you could use for asset management where they say, well, we could actually invest our money much better if only we had enough computing power. But these problems are too complex, complicated to solve, therefore we need a quantum computer. And so the thing is that in this trading world, even small computing advantages can make tens of billions of dollars in difference. And I think that is driving a lot of Interest. And you know, I've never actually worked myself on quantum computing. I just follow this from the periphery.

I think it's not totally crazy. There's always the question, like in practice, how much of a difference would it actually make? So no one knows. But I think they see the possibility that you can make a lot of money with it. And this is why they're interested in it, because they want to be the first to do it before everybody else can also do it. But will we actually get there? Well, that's a different question.

So speaking of things that are in the present rather and in the future, I recently hosted Eric Weinstein at UCSD talking about his theory of geometric unity. I know you've talked with Kurt Jumongo recently. He did an interview and he did a multi hour exposition of it. And then, you know, we're speaking in June, but. But you know, a couple weeks ago he spoke with Sean Carroll and Piers Morgan and they had a very heated debate. First of all, what do you make of this, like physics being discussed as debates? I've been asked to debate people like Terrence Howard, the actor who's gotten a lot of fame for things like one times one equals two and other phenomena. What do you think? Is there a point of debate? I mean, we have peer review and then people like Eric will kind of rail against peer review. And so it sort of sets them in this insulated cage where it's hard for them to get credibility outside of their own kind of inner circle of cheerleaders.

But what do you make of this excitement about theories of everything? We don't even have a grand unified theory, right? We don't have a theory that unites the three stronger forces, let alone own a theory of everything. What do you make of this quest for the theories of everything? Is this some macho thing that people are concerned with? Or is there something really important about the approach to having multiple approaches like Peter White or Garrett Lisi or Eric Weinstein or Stephen Wolfram?

So I think these are two separate questions. The first one is what do we make of this debate culture? And the other thing is how serious are we to take theories or everything? So generally I like this debate idea because personally I want to see more debate about scientific topics. I think this is something that science has been missing for a long time. You know, like this public presence where people actually argue about science, you know, on a level that hopefully to some extent the general person can understand. Like the way that we argue about other things or about sports or politics or whatnot so science has been missing this for a long time and I'm very happy to see that this is coming. And you know, I try to contribute my own little share to that. What I'm not so happy about is the topics that they pick for this. And this brings me to the second part of your questions, like, what do I make of all this theory of everything stuff? So, I mean, it is an interesting question and arguably that attracts some attention, but I think we're overstressing this.

Like, personally, I think it'd be more worthwhile to talk about other topics every once in a while. Like, so, for example, I talk a lot about nuclear fusion, talk a lot about quantum computing. There are other topics in physics and science overall than this theory of everything.

Yeah, it does seem to get a lot of attention. I also get a lot of emails about those, you know, kind of theories of everything thing. And I've stopped. I've basically started charging. If people want to ask me questions, fine, you can ask me questions. But I charge, you know, $1,000 an hour and that usually weeds them out or it makes it very profitable and I send the money to charity. That's my, my new thing. When somebody has a 10 subscriber YouTube channel, I'll come on it, but they have to donate a thousand dollars to do research.

Speaking of research, Sabina, I want to ask you, you're a theorist. Our mutual friend Lenny Susskind, he has written a book called the Theoretical Minimum, a series of books about the. The minimum amount of information a theorist should know to be a physicist. I want to ask you a different question. To your students or people that treat you like a mentor and a professor, what would you say is the experimental minimum? What should be the minimum amount of information that a bright theoretical graduate student, what should she know about the experimental techniques, technology, et cetera, say, in your field? My field, et cetera.

Okay, you just expect me to answer this question like this, Like I'm going to spit out list with 10,000 words like, like an AI or something. We actually did have several experimental lessons on, you know, how partly accelerators work or something and on data analysis and stuff like this. So. And we did have mandatory, I'm sure you have this too, like mandatory experimental sessions where we, we had to work with very outdated experimental equipment that won.

The Nobel Prize in 1914. Yeah, exactly.

Yeah, exactly. That kind of stuff. Yeah. And I do think it's necessary though. I wrecked some of this equipment. You know, I wasn't meant to be an experimentalist.

That's why I never invited you to my labs. You wondered why the Simons Observatory would be in pieces if you were ever. No, we do that ourselves. Let me ask you a different question. Question then. What experiment, if funded, if you were queen of the world, as you are of YouTube and many other domains, if you had this kind of ultimate power and you had the power of the purse, the budget, what experiment do you think would be the most decisive experiment, as Karl Popper called it? What experiment would you most like to see done? Obviously, you know, you've had your criticisms of, you know, the future, circular colliders and so forth, but what experiment would you like to do given, you know, a reasonable, normal budget, say, you know, 30 of all the physics budget for the next 10 years? What. What would you put it on?

Okay, you mean like in the foundations of physics? Sort of like overall, in the entire world?

Like anything that interests you? Yeah, anything of. It's the Hassenfelder machine. What would it be? Yeah, like a billion postdocs.

Right. Okay. So. So the thing is, like, if it was anything, like, in any discipline of science, I would. I would have to look into the. This closely. Like, I'm sure there are, like, questions that would have a huge societal impact, but I can't pull them out of my head immediately because I've never thought about it. But I have thought about the foundations of physics stuff a lot, and this is what my first book was about, basically.

So, so what should we do in the foundations of physics? And the answer that I arrived at was that we should focus on experiments that could test. Test predictions that we arrived at based on resolving an inconsistency. And so one of the things is quantum gravity, because we need theory of quantum gravity to resolve an inconsistency. And there are people who are looking into the. Into this, but they're like, like a few small groups. And I'm like, can we just throw a few billions at this and get it done, like, within a few years rather than a few decades? Like, so this is one thing. The other thing, which is kind of my pet peeve, is that people don't take the measurement problem, quantum mechanics, seriously enough. And so in this case, the problems actually, not that we don't have data, but I think that they don't analyze the data that they have.

Like, so, for example, I think there's a possibility, let me just leave it vaguely, that quantum computers might ultimately not behave the way that quantum mechanics actually predicts. And so now you're in this weird situation that quantum Computers actually do things that people don't understand. And then they say, well, they chalk it up to, well, it's just some complicated thing going on and they give it a name and then they parameterize it, but they don't think about, like, what it actually means. And so I'm afraid that because we don't have the theory for it, they don't even know what to look for in the data. And so this is another thing where I would say put a few billions into this. Like, like look for what happens to measurement devices as they get smaller or to quantum systems as they get larger. Like where, where is the Heisenberg cut? Right. So, and, and how much of this can we measure? Like, and there, there are so many things that you could try to test, like what does it depend on? Does it depend on the temperature? Does it depend on the size of the thing? Does it depend on the number of particles or the density, or as Penrose says, on the gravitational energy or something like this? These are all questions that no one's looking at.

And to me this just seems crazy because it's like, like this is something that we would actually need for the technology development in that area. So this is what I would do if you gave me the money. Do you want my bank information now?

Well, no, I want to do something very risky. So, you know, I'm the principal investigator of the Simons Observatory in Chile at. We just got first light finally on the four telescopes that are down there, three of which are looking for primordial tensor perturbations and the cosmic microwave background B mode polarization. And one of them, the massive 6 meter diameter telescope, can see very fine scale structure in the cmb. But one of the things we're looking for are kind of, you know, departures from the standard model, including things like dark matter and in particular things like axions. Would you say that the kind of case should be closed on axions given the kind of opprobrium that you seem to dish and dish out, at least on your expost. What do you think is the prospect for things like axions or even things like inflation itself? Do you think that we are experimentalists, should be spending some of those hundreds of millions, not billions, but on other pursuits?

Again, those are two different questions like axions and inflation. Let me talk about axions first. People now use the word axions to mean all of kinds, kinds of things. Like it used to be this very specific thing, you know, the, the axial that was introduced by Wilchek and Weinberg that came out of the Pachy Quinn thing and so on. And, and, and that was ruled out already in the 1970s. Right. And, and so then, then people invented other axions and now they actually use the word axions or pseudo axion sometimes if the thing.

Axion like particles.

Axion like particles or whatnot for our kinds of scalar fields that have all kinds of couplings. So that becomes a very vague question in some sense. And I don't even know what exactly you're looking for. Is it just scalar fields with a low mass or is it this particular coupling to the stress energy and the stress energy, the field tensor or what is it?

Yeah, we get both. Well the technical way we look for it is through a conversion of the, what's called E mode polarization with the B mode polarization. Polarization which is forbidden to exist unless there's some parity violating or some, you know, Chern Simons like term that gets added to the electromagnetic Lagrangian. So you know, Turner and others came up with this a long time ago. How it would affect, you know, how you could couple basically give the photon mass. I mean they're kind of like massive photons. There's so many of them, they're extremely light, you know, 10 to the -26 EV or something like that. The coupling is extremely weak.

But they have the right scales and kind of we're ruling out, you know, parameter space both in laboratory settings and in they, you know, could be maybe magically explained, you know, a different kind of whip miracle. They could explain, you know, why these galaxies aren't so cuspy in the small galaxy Problem of structure formation, postdictions, retrodiction to explain the weird phenomena we can't explain with dark matter. But I assume you also maybe have some questions about alternatives to dark matter as well, right? Are you still somewhat favorably inclined towards MOND or MOND like theories?

Yeah, you know, I changed my mind about this three times a day. So first of all, maybe, let me say I actually think for the reason you mentioned that particles with a very small mass have a good motivation to be dark matter candidates because they have every reasonable way to be prevent this galaxy cusp issue. And I actually wrote a paper about this with, with a student. Actually the student wrote the paper and my name's on it. That's how it really happened. But yeah, so this is why I know a little bit like fuzzy dark matter is like the, the overarching term because it blurs out this cusp like this is basically the idea and yeah, I mean, it sounds good to me. Devil's in the details. Like, so, so even if you find, find this, how would you know that it actually is a particle? How do you know that you can't also explain it with something else? Like this is this entire, what they call the inverse problem.

Like, so if you have the data, how do you know which theory actually was the right one to explain the data? This is why in cosmology, like, they're always trying to fit together several different things so that they can say, well, there was only this one explanation for which everything fit together. But so now do you want me to say something about modified gravity or first about inflation? Because, so first inflation and then, yeah, okay, yeah, inflation. So inflation has exactly the same problem like this. So, so we do have some data that you can explain with inflation, but that doesn't prove that inflation was actually the only way to explain this data. So it's very hard to tell apart inflation from some, some other mechanism that could be the speed of light limit, as I'm sure you're familiar with. Like there are people who say we can do, do this faster than light cosmology, where we have some funky fields that can do weird things. And I think on a mathematical level, they would say they would both the same observational results. And so physicists default on inflation, I think, just because that was the first idea.

But I think on a logical level, as philosophers would say, the theory is underdetermined. We just can't tell them apart. And I think this is something to keep in mind. So I, I'm not against inflation, I'm a little bit against all this inflation potential building, you know, where, where everyone has like five different potentials and then they try to squeeze some predictions out of it. And I'm like, what kind of prediction is this? Like, you just made up the, the potential, right? You might as well make up the prediction. So that doesn't make any sense to me. So that's my perspective on inflation.

Okay, now, modified gravity.

Modified gravity, yeah, so. So I've always thought of MOND as some kind of phenomenological effective model. So it clearly captures some things that we observe. And so now the question is like, so it undoubtedly in my mind captures some truth, but the question is like, is this indicative of some underlying modified gravity that's different from general relativity, or is it actually any fact that we, we might be able to derive from dark matter if we knew how? So this is why every once in a while, you know that people who Say that actually the effects that we attribute to modified gravity, they're just statistical artifacts. They come from the data analysis or something else that went wrong. So, yes, so. So that I think is the difficult question, like, what do you make out of it? And then of course, there are people who always, like, Mont has been rude, ruled out because of, I don't know, the bullet cluster. Yeah, yeah, the bullet cluster.

So, so. And yeah, yeah, that's true, but the bullet cluster also ruled out dark matter. Right. So. So, I mean, if you look at the details, this is just generally an observation that's difficult to explain one way or the other. And there, there are a couple of other such things. Like, you know, every once in a while someone claims we've seen a galaxy that doesn't have dark matter, or there's a galaxy that's only made of dark matter. And.

And then you look again at this, like five years later, they're like, oh, sorry, this observation went away. It was something else. Or, you know, it was something without data. So I kind of stopped paying attention to it because, you know, a lot of headlines that just disappear. You never hear of them again. So basically, unfortunately, I have to say that the situation is still inconclusive. So we still haven't been able to rule out modified gravity. We still haven't been able to rule out dark matter.

So where are we going? Yeah, right. What can we do? Speaking of ruling out things that we physicists can't even explain in the first place, dark energy, and in particular the cosmological constant, I have tomorrow video with Kyle Dawson, who is the past spokesperson of the DESI experiment and still a major leader of it. And he was here at UCSD to give a colloquium we talked about about lambda CDM possibly being in mortal danger if not killed at the 4.2-sigma1 and 36,000 chance of being wrong by fluke, what do you make of these measurements that seem to kill the cosmological constant? Your friend Einstein might have been right when he said it was a blunder in the first place.

Right. So I think maybe people need a little bit of context. So what they say they found is that dark energy is actually not constant, but it's getting weaker over time, and there's discrepancy between it being constant and it getting weaker, that is at 4.2-sigma, depending on how you look at the data. So, you know, I'm not sure we need to take these sigmas too seriously. So the issue is, like, there are a lot of tensions in Cosmology, some of which could be be resolved by saying that dark energy actually isn't consolid, but it changes with time. Unfortunately, that's a different time dependence. Like, from a theoretical perspective, that is very confusing. There are also people who have criticized the, the DESI paper have said like it's actually in conflict with some other data.

So, and, and the issue is, the issue with the data analysis, like this is not something that someone like me can reasonably check. Like you just look at the data and they say, oh, we have this data and we did this analysis and this is the result. And then you're like, okay, if they say so, right, what are you going to do about it? I can't spend several months trying to reproduce this plot. So basically what I do is I sit around and wait for other people to do it, people who know what they're talking about. So I'm not sure that I'm making much sense. I guess what I'm trying to say is that I think this is, isn't as high a confidence level as they make it sound. Like 4.2 sigma sounds very convincing, but to me it doesn't feel that high.

Well, yeah, I mean, feeling, you know, and data. I guess, I guess the question, you know, is it's odd that we seem to know and many, many more sigma that there's something like dark energy. And what's under, you know, kind of attack now is the equation of state. You know, this additional term that generates the evolution of the equation of state. State. It can be measured in many ways. The BAO is just one of them. And the fact that there's these tensions and then there's tensions within the tension.

So I've said that what we really need is a good psychoanalyst. We need a therapist for the field. That's where the billion dollar Sabina Hassenfelder experiment should go. We should have a team of psychotherapists. But in reality, I think the tensions with intentions, in other words, there's a tension between the Hubble constant and early times and late times and then the different data that see that as well, there'll be a tension between the lambda being a constant or dark energy being a constant or not. So how does one navigate here? I mean, which tension should we take the most seriously?

Well, you just take all the data and you feed it into an AI and then you see what comes out. I've actually been seriously thinking about this, but if you think about it for a little while, you see a big problem with it with which might actually be the problem. Which is. Well, first of all, it's not actually a lot of data. And AI does need, at least the current AIs, they need a lot of data for training. And you just, in cosmology, you always think like, it's a lot of data, like, because there are lots of galaxies out there. But then you look at what they actually measure and it's like 3 pixels per galaxy or something, right? And the sample is like 150. So you know, it's like portraying an AI is, it's not a lot to go by.

The other issue is, and other people have made this point much more eloquently than I possibly can, is that this data is all. Well, first of all, you need to exactly understand your instrument because that always has some sort of sampling bias, it has an instrument bias and so on. Then the data, you know, it's got to be evaluated with knowing what the instrument actually can do. Then it's got to be cleaned, it's got to be internal, interpreted. And then often it's a, you know, there's some foreground which you're familiar with. And then often the data is already interpreted with the model in mind. So, you know, for example, redshift is one of those things that they try to attach to the data based on the model that predicted the universe expands with this particular redshift. And so if you only have access to like to the final data data, that becomes a mess, like, because you have, you have no idea really what was actually already, what already went in.

And there are some people who say that I've talked about this in some more details, that this might actually be part of the reason for why we have these tensions. So let me see if I get this, this example together correctly. So there is the cosmological principle, right? The cosmological principle says that if you average the universe on sufficiently large scale scales, then meta should be equally distributed. And so you can ask the question like, what does sufficiently large scales mean? And you can calculate this in the lambda CDM model. Now some people use this to calculate what direction we're moving into, because like the CMB dipole, or you can do the same thing with quasars and so on, on. Because if you want to know what this direction is, you evaluate this relative to the background, which. But now here's the thing. You have calculated by using lambda cdm, so it becomes this.

But you've already put in the model, in calculating what you see what I mean? And so now the issue is a Lot of people who do the analysis, like which model fits the data best, just use the data that has already been massaged by using the model. So this is all. This is complete mess. So data and astrophysics, generally, complete mess. You don't want to touch it unless you really, really have to.

Right. I did an interview with David Wiltshire of the Timescape Cosmology.

All right.

And that's hopefully out by the time this video is out. But the, you know, kind of concept that we live in a, you know, in a. A void perhaps, and that these are mimicking what you'd see if you lived in a universe with a cosmological constant or without a cosmological constant at all, or just, you know, some. Some very small or maybe negligible amount of dark energy. Okay, Sabine, I know it's getting late there, but we have a million questions from the audience. I have to ask some of them. Okay. First one, Sabina.

This comes from Bobby Cosmic. Dear Professor, I would like to hear both of your thoughts on the apparent decline of academia in the United States. States. I've been hearing a lot of negative talk about research in universities. I've been hearing that publication quality and academic rigor are not what they used to be. So how do you respond to Bobby Cosmic?

So I have no particular insights in what's going on in American University in particular recently. I haven't been in the United States for a long time. Of course, I talk to Americans like our host, Brian. Right. So first of all, I'd say that, like the. The decline of academic research is not specific to the United States. Certainly not. We see the same in Europe and in other countries that I hear of.

It's worse in some countries than in others, but that's a different story. I think it's something to do with the overall organization of the scientific system, the way that people are rewarded. We previously talked about the reward function. Right. Your happiness bonus. So scientists who work in academia, they get rewarded for doing certain things, one of which is publishing papers, because then they can apply for more money to get more grants, and it just keeps the cycle going. So. So they continue to be employed.

And this gives them very weird incentives. It. It's a very. It. It makes it very appealing to work on something that's low risk so that you have a high chance for it to get funded so that other. Other people need to appro. And so there's a lot of bias in this system. And they're basically.

It's basically completely. It's a completely closed system because well, first of all, there's peer review. But also if you look at the grant cycle, right, the people who sit on the review panels are the same people you work with. And so there's very little external oversight. And that's bad. And I think it's been going on, on for much too long. People have complained about this pro of these problems, like for 30 years or something. No one's doing anything about it.

And there will come a point where it just falls apart, like, where everyone can see like people like, this is like a complete waste of money. And I think that actually in the foundations of physics, we're pretty close to, to reaching that point.

Yeah, that was a question by Doc Dealgood. Is there any progress in the foundations of quantum quantum mechanics?

Well, yes, I'd say actually for two reasons. One reason is on the experimental side. There's basically progress every day. Like, this is really amazing. This is why I talk so much about quantum technology, because it makes new things possible. We were already talking about the idea of testing quantum gravity in the laboratory. This idea only becomes possible because of advances in quantum tech. And this is like real progress.

Like 10 years ago, people weren't even talking about it. Or maybe they just began talking about it. But you get the idea like. And this is actually driven by, by the ability to put bigger objects into quantum superpositions, better detectors. They're pushing all the quantum limits. So, so there's really something happening on the theoretical side. This has had the effect that there's a revived inter interest in quantum foundations. What's still missing a little bit is people who try to push beyond quantum mechanics.

This is what I've called physics beyond quantum mechanics. Like physics beyond the standard model. I think that's what we need. There are a few theories or models of that type. For example, Penrose is one, generally collapse models, but very few. And I think we need more of them. And then we need to get experimentalists to actually test them because I think there's something to find. This is what I already talked about earlier.

Yeah, great. Okay. Nemo's YouTube Ask a Little bit of an obnoxious question. Did you really receive a letter from a particle physicist that you made a video about?

It's a real email. And so maybe let me say one thing.

So he's talking about. First of all, you made a very popular video about six months ago.

Yeah, yeah. It was a surprise to me because I thought it was kind of a niche thing and I wanted to get this out. This has been sitting in my, inbox for a long time. It was an email, a very honest email, in my opinion, that I received in response to a criticism I wrote of the community, the foundations of physics in general, but particular about politics. Particle physicists. I said this. So, so I, I know the person who claimed to be sending the email personally. I've met them several times and my husband also knows him.

And so I, I, I showed this to my husband like already when it arrived. And we, we've just, we've talked about this like many times and we're both pretty convinced it's actually the real person. And I also, I looked them up and they still work at this place, but they're pretty close to retirement. And you know, I'm like living that live. Like, what's the point of pissing on their leg now? Yeah, it doesn't really make it.

Did you agree with their perspective? I mean, in terms of the challenge of the field and ignoring, you know, I trust you implicitly, you know, that you received it and that your feelings are about it and your assessment of it was valid. Valid. But did you believe that they had, you know, legitimate gripes about it and if so, what can be done about it? I mean, can, is there anything practical about their suggestions or were they just complaining?

Well, so there's a certain irony actually. So I, I took out the details from what I read, but actually the, the, so the person was going on about that there's, you know, certain models that are all crap and it's just refurbished something. I think this was the phrase that they used. I didn't know this because that was a fear that, that, you know, I don't myself work on that I, it would never happen have occurred to me. So I learned something and I was, you know, I was like, okay, it's the same thing as I see in my own field. And of course I've gotten many other emails from other people, like in completely different disciplines, like everything from, from medicine to computer science, where people say, well, we see the same thing in, in my discipline with this topic or this other topic. But the issue is that those people, they don't want to go on record record. So this is like a general issue.

Yeah. And I mean this is the same problem that I already talked about earlier. So people just have an incentive to make up these things that they can continue getting grant money, whether or not this actually makes any sense. Yeah, I mean it makes sense to them personally because it feeds their family. But from a scientific research perspective, it doesn't make any sense. And So I think, I mean, I.

Think in experimental, well, it's hard to, we should break down, you know, what they. Some other time perhaps when we're together in London next in the fall. But, but the notion of, you know, kind of the self interested, you know, pay for health insurance for my family, you know, it's a valid one. But to the extent that scientists don't believe what they're talking about, like for example, I don't, I would say the probability that we'll detect inflation via B mode polarization is very low because there's a huge amount of parameter specific space that we'll never be able to access even if inflation took place. In other words, we won't be able to do any kind of legitimate testing or mapping of the inflaton's potential because we simply won't see it. But that doesn't mean that inflation didn't take place. In other words, we can't falsify or prove inflation. But I don't think that it's illegitimate for me and my colleagues to propose to do these things because if you don't take the shot, you'll never know.

And, and we may see something which would not ironically be as valid as important for proving inflation, which I don't think is a sensible concept, but for disproving all these other concepts from Stephen Hawking and I talked to Thomas Hertog last week from their model no boundary, all these models that don't predict Penrose's model, Turok Steinhardt, Aegis, all these models that don't predict B modes, in a sense we're doing the opposite, we're trying to falsify those. But anyway, I don't see it as illegitimate. I know that there are people that do it, as you say, to feed their family, but I think the vast majority of people, they're very interested in uncovering some tiny minute piece of the grand puzzle and fabric of science. But we can leave that there. I have a technical question for you from Phil Kalis. Does Sabina think non local models could disprove the mind as machine on argument, could biology perhaps participate in non local physics in irreducible ways not replicable by digital machines?

Well, dear, what I'm going to say about this. Well, so I mean general comment that one could make is that it kind of depends on what you mean by digital machine. So it's a quantum computer digital machine. So there's a, a. I think there's a fair possibility that the brain actually uses quantum effects and if that's the case, then you might need a quantum computer to get something similar to what goes on in the human brain. I think it's kind of unlikely, but I think one can't dismiss it out of hand. So I'm not, I'm not sure I understand the reference to non locality because I don't know exactly what the person means by non locality. So if they just mean non local the same way that quantum mechanics is non local, then I think that should answer the question.

I think that's right. I think that's what. Okay, just one or two more questions and then we'll wrap up and go on to a very brief extravaganza. So let me just see if there's anything else from the audience here. Okay, the last thing from the audience. How concerned are you, Sabina, about what you've called AI slop? I assume it's quite, quite significant concern in science that these machines can generate infinite numbers of seemingly legitimate scientific research. What is that going to do for the actual scientific method?

It's, it's going to be terrible. And we're only just seeing the beginning of it because it's, it's only just like about now that the models actually become good enough to make reasonably looking plots and produce reasonably, you know, something that is, if you look at it, you can't immediately tell it was written by an AI or it was produced by an AI. And what's going to happen is that journals are going to get completely overrun by this. And I think we're already seeing the beginning of it and it's going to be a huge problem because they'll have to figure out a way to filter out all of the AI slop. And we've seen exactly the same problem already happening in other dispositions disciplines. Like they're just getting overrun with AI slop and they have to figure out very quickly how to deal with it. And that's a real risk. What's going to happen in science is that it becomes much more narrow minded because they'll have to come up with something quickly.

And a reasonable thing to do is probably to go by personal credibility. Like if you look at the person who actually does the submission and then you run into the problem that it becomes, it becomes like a close club or something. Yeah, and, and that's bad because, because I think you need outsiders you put forward to having fresh ideas like, and that's going to hit especially hard people from particular countries because we know that a lot of the junk actually comes from, you know, somewhere in the Middle East. Or something like that. There's some countries where they have a lot of those papers almost going on. And I think, like, the publishers are not remotely prepared for what's to come. Like, think, for example, of the archive. Like that, you know, you and I are used to.

They, they have a moderation queue, right? So if, you know, something comes in and looks a little bit fishy, then their system flags, gets sent to a human moderator. But there are only so many of those because they don't have a lot of money. They're all volunteer years and it can take a very long time already now, like, I have a friend who has two papers in the moderation queue and they've been stuck there for two months. And you can just, I mean, maybe, you know, it's. I shouldn't extrapolate from one data point. Right, but that's a pretty bad example. Like, you'd think, like, if the paper's really crap, they should at least find someone to look at it and just read, reject it. Right.

But what's up? They're not, they're not doing anything. And now, now imagine like people are going begin to submit their AI slop to the archive because they went through one way or the other. It's going to be terrible. Yeah. So this, this is why I'm worried about it.

Yeah. I think that we'll get back to, you know, what they did in the 1800s. You know, you'll have Marie Curie will stand up at the Royal Institution or, you know, Max Planck and do a demonstration. This glowing film or this glowing rock makes this photographic emulsion exposed. Well, Sabina, what else are you working on? What would you like the listeners to do as a CTA for high CTR, obviously. Your YouTube channel is massive. It's been an inspiration to me. I have what the Germans call Mitt Freude whenever I see you tick past another 100k on your way to 10 million, please, soon.

Besides science without the gobbledygook quiz with it, where else should people. What should people be excited that's on the horizon from you?

So actually my poor YouTube channel has been doing really badly in the past couple of months now. I've been wondering why. So I'm like wondering, like, wait, wait.

Wait, you can't say that because you're talking to somebody who's got the square root of the number of subscribers you have. So what do you mean it's been doing badly? You've gotten, you know, 200,000 plus views on every video. I kill for those numbers.

No, no, so, so, so it went down like by a factor 1/2. So for just like really suddenly. And I'm a little bit, you know, distrust about it because I'm not doing anything differently.

Everybody's seeing that. Everybody. I mean, I've. I've looked at channels with 6 million subscribers and they'll get 50,000 views. I have a friend who's got, you know, literally a 6 million view subscriber channel and he's getting 100,000 thousand views, which is not, you know, less than 10%. I think it's common. I mean, I'm seeing it, but I'm not. Yeah, I was never as big as you, so I don't, I don't know.

And what's your North Star? I mean, what are you optimizing for? Is it, is it views as, you know, is it some. Something cynical to get more views, you get more adsense revenue? I mean, I can't imagine that. So what's your guiding metric?

Yeah, so I mean like the. I've given up on the ad revenue because, you know, they have this issue that your video has to be longer than eight minutes or something. And most of my videos are like 7 minutes, 30 seconds or something. So I've just, I've just given up on this. No, but I'm, I'm. I'm. The reason it bothers me is like I'm. I'm wondering like, am I doing something wrong? Like, should, should I.

Do I have to improve something? I mean, of course we all have fluctuations like ups and downs and I know I've seen a couple of those, but. But none of that was that sudden such. And so, so severe for no particular reason. Like every once in a while, you know, I make a video that upsets a lot of people and you know that there'll be like 100 people unsubscribe or something and. Okay, that's fine with me. But there wasn't anything like it. Like there was no trigger or anything.

Right.

So I have no idea.

I think that's happening a lot. I think there's just so much content out there, especially with AI channel channels. I was always, you know, curious why you don't do, you know, videos like this podcast basically format or, or, you know, we are in front of a green screen mostly for your videos. But you know, maybe it's. People find it more authentic when you're. I stopped using a green screen about six months ago. Not that I can give advice to you, but. But people seem to like, you know, sitting at a Table and, and you know, just talking to the camera.

Like your vlog you put up yesterday, a couple days days ago, you walking in the woods. It's very vulnerable, it's very authentic. What about more content like that?

Yeah, well, I've been thinking about it but it's, it's always like there's a lot of information that I need to compress quickly into my, into my new summaries and the green screen just works very well for that sort of thing and we have an established routine that I can't just unroot one day to, to the next. So of course I've, I've been thinking about it. Yeah, so. So you asked some question, but I'm kind of getting cognitively tired so.

Yeah, well, maybe we'll finish up. But, but they, but I have seen a lot of people's channels, you know, in, in severe view decline. I do think it's because of the sport, you know, the, the infinite number of choices that we have. The AI slop of talking head videos, you know, that they can make an infinite number number of. You know, just search the archive and put up some paper and, or search your. I think what they're doing is they're searching your, your feed and then just making a bunch of, you know, shorter form content and trying to front run. You know, you mentioned something on X and they'll say, oh, she's going to make a video about it, so. But we don't have to talk inside baseball.

I'll ask you a question. I have a professional, you know, question to ask you at least about YouTube, but I can't do it online because it's highly confidential. So we'll stop the interview now. But are you working on another book or just, just.

Oh, right now I remember you asked me what I'm working on. Yeah, maybe I've tried working on another book but it didn't progress very far like. So it's stuck at something like 5,000 words, which is not a terrible lot. I've actually recently, you may laugh about it, but I've returned to working on a paper about the foundations of quantum mechanics because I feel like this is like my life's work and I need to finish it and I need to get it out before I die and so.

Yeah, well, I can't wait for that to come out. You'll come back on hopefully when that comes out. So quiz with it. I'll put a link to it. I might make a short, just where we talked about. Quiz with it and I'll put it up as a. As an homage to you and everything you do as a kind of an advertisement because I use it and I find it very helpful. There are very few tools, just on a technical level, that scrape the YouTube transcript so flawlessly and so efficiently so I can use it.

I'm so happy you say this. You wouldn't believe how much of a headache it was to get.

I know how much of a headache it is because I try to do it myself with, you know, my 14 year old kid and it just doesn't work. So I have him making 3D printed brains instead. But Sabina, we'll see each other in a few days. By the time this comes out, I will see each other in London. I can't wait to see you. Maybe we'll do an in person quick, quick post because we haven't been well. We were in person at Peter thiel's house in 2018 when your first book came out. And then before that it was 2010 in Stockholm where you invited me to give a lecture on the foundations of quantum gravity or Future of Quantum Gravity Conference with Lee Smolin.

15 years. Crazy.

I know as well. My wife was pregnant. You were pregnant, I think. I don't know how you do it all, but you do it so wonderfully. Sabine Hasenfelder, thank you so much.

Thank you.

Free will or determinism? Quantum computers or classical? These are questions that touch everything around us, from AI development to quantum mechanics itself to how we live our daily life. I thoroughly enjoyed Sabina's perspective and I know you'll enjoy this deep dive episode with Robert Sapolsky where we explore his research on behavior and biology that led him to conclude that free will is a complete illusion and what that could mean for society, justice and human responsibility. Don't forget to like, comment and subscribe.