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Infinite Loops
Scott Aaronson — Quantumania (EP.240)
01:12:11
My guest today is Scott Aaronson, a theoretical computer scientist, OG blogger, and quantum computing maestro. Scott has so many achievements and credentials that listing them here would take longer than recording the episode. Here's a select few: ...
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- [00:02]
A
Hi, I'm Jim o', Shaughnessy, and welcome to Infinite Loops. Sometimes we get caught up in what feel like infinite loops when trying to figure things out. Markets go up and down, research is presented and then refuted, and we find ourselves right back where we started. The goal of this podcast is to learn how we can reset our thinking on issues that hopefully leaves us with a better understanding as to why we think the way we think and how we might be able to change that. To avoid going in infinite loops of thought, we hope to offer our listeners a fresh perspective on a variety of issues and look at them through a multifaceted lens, including history, philosophy, art, science, linguistics, and yes, also through quantitative analysis. And through these discussions, help you not only become a better investor, but also become a more nuanced thinker. With each episode, we hope to bring you along with us as we learn together. Thanks for joining us. Now, please enjoy this episode of Infinite Loops.
- [01:14]
B
Well, hello, everyone. It's Jim o' Shaughnessy with another Infinite Loops. I must tell you that today's guest really daunts me. My guest is Scott Aronson, a theoretical computer scientist with a chair, not the chair at the University of Texas at Austin, winner of a plethora of awards of, like, just such a prestigious nature. I was trying to think, like, which one, like, should I call? Which one would you call out? Which. Which award that you've won has made you kind of like, ah, you know, gave you that little chill feeling.
- [01:53]
C
I think that would have to be like, undergraduate teaching award that I got when I was at mit.
- [01:59]
B
What a great answer. I love that answer. You are the creator of the Complexity Zoo. You are the proprietary of the Shuttle Optimized blog. You were a visiting fellow at OpenAI, where you were consulting with them on the theoretical foundations of AI safety. There's just so much that I want to talk to you about, but as I said to you before we started to record, I am fascinated by your reading burden. You read more than I do, and I read a lot. And I just wanted to talk to you about that because I think we kind of are animated by the same thing, which is we are so lucky to be alive at this point in the timeline and to not read about everything that's going on seems to me to almost be a crime. What's your version and have you augmented it? Have you changed your reading since I read this piece?
- [02:57]
C
Yeah, yeah. No, I mean, reading has crept up on me over the years.
- [03:01]
D
Right.
- [03:02]
C
It seems like there is more and more interesting stuff you Know, on substacks, in magazines, you know, research papers. Just to keep track of what is happening in all the areas that I care about is basically a full time job in itself.
- [03:19]
D
Right.
- [03:19]
C
And then that, that's incredibly dangerous because I can feel like, okay, I'm making progress on something that seems good to do by just reading and keeping track of everything. But then the whole day passes by, you know, now it's time to pick the kids up from school and, and deal with the kids. And I haven't actually done any research, I haven't written any papers, I haven't even written any blog posts. All I've done is I've read a bunch of stuff. And, you know, and this is all stuff that tomorrow morning, you know, is going to be refreshed. There's going to be new stuff that I have to read.
- [03:53]
D
Right.
- [03:54]
C
And on top of that are all the, you know, specific to me, you know, all the emails that I get from, you know, because of my blog, for example, from, you know, random people around the world and, you know, and like, if there's some student who has questions, like, my inclination is always to help them if I can.
- [04:11]
D
Right.
- [04:12]
C
So it's easy for your day to just be completely filled up by that stuff. And I've never had any particular skill at like planning ahead or, you know, or planning my day or blocking out time or things like that.
- [04:25]
D
Right.
- [04:26]
C
You know, whatever success I've ever had has been, you know, in the teeth of just, you know, flailing around and just, you know, dealing with things randomly as they come or as they take over my life. But, you know, it seems like if I want to continue to do original things and, you know, maybe I've got, you know, a few more decades, you know, or who knows how long in which to do them, then I do need to get much better at that.
- [04:52]
B
You know, I was smiling and nodding along as you were saying that because I find myself in a very similar predicament.
- [04:59]
C
I good to know I'm not alone.
- [05:02]
B
Once I start, the pull of the rabbit hole is so difficult for me. And I find myself like looking up and thinking, holy shit, how did it get to be five o'? Clock? And I have six grandchildren and I had the joy of having them all here for a while.
- [05:17]
C
Oh, wow.
- [05:18]
B
And I love watching children because I kind of think they're unprogrammed, unprocessed humans. And by that I mean, like, we can learn a lot, in my opinion, by watching kids, right. Because they don't have any of the millions of social conditioning and everything that we adults have. And it's just that their voracious curiosity, their willingness to try to explore everything. And anyway, so I love that they were here. But after the fun was done, I realized that I had gotten so far behind on all of my reading.
- [05:54]
D
Yeah.
- [05:55]
B
And yet when I was chatting about it with a friend, I'm like, I wouldn't swap the time. Right. Because you can learn so much just by watching children in their, what I call humans in our natural state.
- [06:08]
D
Right.
- [06:09]
B
Like before we decide on what the correct answer machine they're trying to install in our head.
- [06:16]
C
Yeah, no, I mean, I mean, certainly another thing that has, you know, changed in my life has been, you know, having two kids. You know, I have an 11 year old and a 7 year old.
- [06:26]
D
Right.
- [06:27]
C
And so, you know, like, like, maybe even in the ideal case, I wouldn't expect to have the same level of productivity that I had in my 20s.
- [06:36]
D
Right.
- [06:36]
C
But this is just a trade that one makes, Right? Yes. And definitely, you know, to teach my kids, you know, about, you know, whatever the halting problem or, you know, the busy beaver numbers or what is a quantum computer, you know, why do we think factoring is harder than multiplying? You know, that is one of the highlight of my life is when I can get them to be interested in that stuff rather than playing Minecraft on their iPads, which is what they would spend all day, every day doing, I think, if they were allowed to.
- [07:09]
B
Yeah, yeah. That's kind of a nice segue into the thing that you've written about the problem of human specialness in the age of AI. One of the things that I loved about it was, at least from my reading, you seem to speculate that the things that many of us often look at as our weaknesses.
- [07:29]
D
Right.
- [07:30]
B
The fact that we're mortal, the fact that we're quite frail, the fact that we are kind of imperial, these unpredictable things they might, in the age of AI, actually turn into our strengths. Talk about that a little bit.
- [07:47]
C
Yeah, I mean, I'm a very firm believer that if you want to say that humans are not basically, you know, computers, that there is some fundamental difference between, let's say the human brain and a computer that would sit, that could simulate a brain down to the last detail, then the burden is on you to articulate what the difference is.
- [08:10]
D
Right.
- [08:11]
C
The burden is not on, you know, the person who says, you know, the AI would deserve rights or, you know, deserve the same consideration that we give. Right. It's like, you know, imagine that some Alien, you know, shows up from another planet, right? And it can talk, it can understand, it can, you know, it seems to have wants and desires. Our default, I should think, you know, would be that this alien is an agent, you know, and if we're going to grant other people the grand other humans the courtesy of, of regarding them as sentient, you know, or as conscious as having an inner experience, then we should do the same for the alien, okay? But now suppose that the alien is made out of silicon rather than out of carbon. Suppose that, you know, it runs on a chip, right? If you think that that makes a difference, then the burden is on you to say why, right? You know, and then some people say something about, well, humans are special because they underwent an evolutionary process. I was like, well, why is that the thing that matters? Like, you know, humans have known about biological evolution for less than 200 years, right? But we had a, you know, a strong sense of our consciousness or our specialness or so so forth for, for long before that. So, you know, that just seems like special pleading. And so I think, you know, you have to look for something that is, you know, actually about what can you do with these systems or what can the systems do, right? That is, that is abstract. That is not just like a question begging appeal to. We know that we're humans, and so, you know, we have real thoughts. But, you know, this chat bot, even though you can't distinguish it from us, it only seems to have thought it simulates, you know, all these, right? Well, it's like, no, you have to give an operational criterion, right, that distinguishes the one from the other. And so, you know, it occurs to me that maybe about the best that we can do in that direction on the basis of current knowledge is to say, well, you know, all AIs that are created today have certain things that we can do with them that we cannot do with any existing biological organism. And that includes we can make a perfect backup copy of it, right? We can rewind it to an earlier state. You know, if you are talking to ChatGPT and it is refused to cooperate with you, right? It is refused to help you make a chemical weapon or whatever nefarious thing you were trying to do, you can always just refresh your browser window and, you know, wipe its memory clean and try again, right? I mean, imagine if, like, we could do that, like whenever someone was on a date and, you know, they said something embarrassing or they said something that. That's spike their chances. Imagine if they could say, you know, you know what? Let's just rewind and let's just try that again, right? It's like, you know, we don't, you know, you don't have that ability with humans, right? Humans, it seems like, like whatever choice they make, you know, that that's, that's the choice that they've made. And you know, we never get to go back and see any other choice that they could have made. But with an AI that's running on a digital computer, right? Key property is that it is doing operations on classical information, classical bits. And classical bits can be perfectly copied and computations on classical bits can be made perfectly reversible if we want them to be. They can be rewound to earlier states and so forth. With the human brain. Well, it's not clear. I mean, it's sort of a question about at what, at what level of description do you need to go to? If you like, like if we could imagine that far in the future, you know, we will have nanorobots that can swarm around inside your brain and just make a perfect copy of, you know, all the, the connectivity pattern of all the neurons and the strength of every synaptic link. And if that is enough to bring a second copy of you into being, well, then I guess you can make a backup copy of yourself in that future. And if you're going on a dangerous mountain climbing trip, then, you know, you can just leave a backup first. And if version one of you happens to fall, you can always just restore from the backup, right? Or, you know, you could, you know, there are so many thought experiments and philosophy and science fiction, right? Like if you want to visit Mars, then instead of getting on a spaceship, you know, which could take six months, why not just email yourself there, right? Just take this digital file that encodes the whole state of your brain, you know, send it by radio to Mars, which will take 10 minutes. And then, you know, have, have a new body reconstituted for you on Mars, right. And then, you know, what should, what should be done with the original copy of you that. That's still on Earth? Well, you know, maybe it'll just be painlessly euthanized, you know, if you don't need it anymore.
- [13:21]
D
Right.
- [13:21]
C
And it's, it's, it's, it's interesting to think about, you know, would you, would you be willing to do that?
- [13:26]
D
Right.
- [13:26]
C
I think, okay, let's grant that. Probably you or I wouldn't want to be the first ones that try it. But, you know, suppose you're in a society where this is common. This is just the way people travel, you know, would you. Would you do that? And would you expect that this. That this second copy of you, you know, in a reconstituted body that was made from this classical information that was sent by radio or through a wire, would you expect that that second copy is really you? Okay, now, but now, now, another possible, you know, if there's any reason to hold back on that, to not do that. I think that depends on the possibility that maybe, you know, these sort of microscopic details, these sort of chaotic details in the state of our brain are somehow important to our identity.
- [14:19]
D
Right?
- [14:19]
C
Like, if you wanted to know, not just the general connectivity pattern of the neurons, but will this specific neuron fire or not fire?
- [14:28]
D
Right.
- [14:29]
C
That, you know, and if it fires, that might set off a cascade of other events, you know, that might ultimately lead to you taking one job rather than another job. But, you know, a neuron could, you know, firing, you know, ultimately depends on, you know, is some sodium ion channel open, which could depend on the chaotic movements of molecules in that channel. And, you know, if you really needed to get, like, the exact state of all the molecules there, you know, for making that prediction. Well, one thing that quantum mechanics tells us is that you can't get the exact state of without destroying it, right? This is called the no cloning theorem, right? It's one of the fundamental facts about quantum mechanics, okay? And crucially here we're not talking about the brain being a quantum computer, right? We're not talking about it using entanglement or, you know, which some people have speculated about those sorts of things. But, you know, I don't see any evidence for those possibilities right now. And I'm not going there.
- [15:32]
D
Right?
- [15:33]
C
All I'm talking about is just sort of the mess that, you know, the chaotic mess that we know is there at the, you know, if you go all the way down to the molecular level, right? And I'm saying that if that mess is actually important to your personal identity, you know, to, like, a given physical system being, you know, really you rather than just something that acts a lot like you, then this would really be a fundamental difference between us and any AI running on a digital computer. Because it would seem that just for ultimately reasons of physics, we cannot make a perfect copy of all the microscopic details. And so then that would suggest that there is a sort of ephemerality to human decisions that really does differentiate us from AIs, right? Like if you had, for example, an AI. Shakespeare, right? Well, you know, Shakespeare, I guess, wrote 23 play. No, sorry, 39 plays, right. 39. 39 plays and some sonnets. And that's all we're ever going to get from Shakespeare, right? With the plays that he gave us or the plays that he gave us. But if you had an AI, Shakespeare, right. You could always run it again. You could get more and more samples from the same distribution. And so that sort of limits how, how much value we could ever put in any one, you know, Macbeth or Hamlet or whatever. Because, you know, there's always more where that came from.
- [17:04]
D
Right.
- [17:04]
C
For people who were worried that AI is going to take over the world or whatever, this is very cold comfort, right? Because, you know, this is, this is just the way that we are limited compared to the AIs. And yet, you know, this is also a reason why, you know, you could say like the, the outputs of a specific human, you know, kind of, you know, in a sense they matter more.
- [17:25]
D
Right.
- [17:25]
C
Because, you know, you're only going to get the one, you know, if that human is mortal, if they just have, you know, this amount of time to make the choices that they make. And then, you know, we don't get to make a backup copy.
- [17:37]
B
I absolutely love that on many levels. There's a fun science fiction book called the Fifth Science and in it, this is in reference to your emailing a copy of yourself to Mars.
- [17:49]
C
In it.
- [17:49]
B
It's actually a collection of his short stories, but it works like a. No. And one of the things that they do with teleportation in his universe is that it actually does destroy your original human body.
- [18:03]
C
Yes.
- [18:05]
B
And one of those scenes is just brilliant because it's him. He's groggy, he thinks it's him, and then he sees what was him in a bloody mess at the bottom of the conveyor and it just totally freaks him out. And he then digresses into, you know, it's a well known cause of insanity and people just absolutely losing every aspect of their, what they view as themselves. But it's also like the staple of a lot of great science fiction. You know, there was altered carbons where you could make the exact duplicate backup and store it so you could go climb that mountain because you could come back as your backup copy.
- [18:53]
C
But I mean, I was going to say almost anything that happens in technology, there is some science fiction writer who got there first.
- [19:00]
D
Right.
- [19:01]
C
And, and so, you know, this, this is an argument that many people, you know, you know, used to give. Why, why not to worry about, you know, catastrophic AI risk, that it just sounds too much like a science fiction plot. But in the last few years, I think reality looks more and more like a science fiction plot. The big question is, which science fiction plot are we living in? Because almost any outcome you can imagine there is some science fiction writer who would have predicted that outcome.
- [19:34]
B
And you actually build off of that in one of your suggestions about how we should be programming AI, including what we've just been talking about, it should view as precious the human ability and difference from.
- [19:48]
C
Yes, right, of course, it's a big question. How do you, first of all, how do you reliably align an AI with any set of values?
- [19:56]
D
Right.
- [19:56]
C
And then given that, how do you specify what value system we want? What value system would. We don't want to lock in and ossify, you know, the values that humanity currently holds. You know, presumably, just like we look back on people in the 1700s and we find, you know, many of their values horrifying, people of the future would look back on us and find some of our values horrifying. So we don't want to permanently lock in whatever mistakes we're making.
- [20:29]
D
Right.
- [20:29]
C
But how do we like, encode the concept of like the values that we would have if we grew enough, if we thought about it enough, you know, that sort of, in some abstracted sense, like, those are the values that maybe we want to give the AI, Right. So I think, you know, there are, there are very big questions there. One other thing I wanted to mention that, you know the teleportation that destroys the original. So in quantum information, we have something that is precisely like that. Okay, so quantum teleportation is this very important protocol that was discovered 30 some years ago. It's for transferring a quantum state from one place to another place by sending only classical information. But there's a couple of catches. One of them, you need pre shared quantum entanglement between the two locations. In order for this to work, then, just as an inherent part of the protocol, you have to measure the first state, right. Along with half of the entangled pair. And you measure it in a way that inherently destroys the first copy.
- [21:38]
D
Right.
- [21:38]
C
And that's the only way that you know which classical information to send over, so that the person at the receiving end can apply a correction operation that then recovers that. That same quantum state. Okay, but, but this sort of destroying the original state is a necessary part of the protocol because if it weren't for that, then this would violate the no cloning theorem.
- [22:01]
B
Yeah.
- [22:02]
C
And so it's almost like you could imagine a future where, you know, if our quantum if, if it was really your quantum state that had to be emailed to Mars, you know, in order for you to be, you know, to wake up on Mars, to experience yourself being on Mars, then we wouldn't have this, this hard moral or metaphysical conundrum of what to do with the original copy of you, because the quantum teleportation protocol would just destroy the original anyway. Yeah, hopefully it would be just like a fancy version of getting on a spaceship and just moving yourself to Mars. So no one, no, no, no one would have to actually experience death. But you know, although. Although, who knows?
- [22:47]
B
Yeah, as I was listening and I don't have it in my notes, but you'll, I'm sure know what I'm referring to. I was reading recently about an experiment using the classic double slit. And what they did was fire photons that were entangled and one was observed and one was not observed. And they were in separate locations. We do. And if I recall the.
- [23:13]
C
Wait, so these are two entangled photons?
- [23:16]
B
Yes.
- [23:16]
D
Okay. All right.
- [23:18]
B
And they have two islands, I think it was. I'm sorry, I'm doing this just from memory and I read it a couple of days ago and they did it over here first with a non observed firing through the double slits.
- [23:31]
D
Right.
- [23:32]
B
And then they did.
- [23:34]
C
The classic double slit experiment just involves one photon that's in a superposition.
- [23:39]
B
Right. And that's why I found this.
- [23:40]
C
That.
- [23:41]
B
Yeah, that's why I found.
- [23:42]
C
All right, if you send me a link, I can look to look at it.
- [23:46]
B
I will.
- [23:47]
C
Okay. I should warn you that there's a decades old industry now of like doing some quantum experiment and then saying like, wow, this is amazing. Like, you know, physicists are scratching their heads over, you know, even more weirdness of the quantum world. And the answer is always, you know, in every single case. It's no, it's just the same weirdness again. It's just, you know, once you know, what, what Schrodinger and Heisenberg knew a hundred years ago, then you could predict the outcomes of every single one of these experiments.
- [24:18]
B
That leads me to another observation of yours that I've become keenly aware of. And that is, you know, for even an intelligent layman. Right. Trying to disambiguate what is the real deal versus the hype.
- [24:34]
C
Yes.
- [24:35]
B
Is virtually impossible. Right. Like, because it seems to me that with the advent of quantum computing, with the where AI is right now, unfortunately that brings a lot of hucksters and, you know, promoters and. So what advice would you give there?
- [24:53]
C
Yeah, no, I mean, I mean I mean, every field, you know, once there is money involved, then there are hucksters, right? This seems like an iron law, right? But I think in some subjects, people do better than others at getting a clear view of where things are, right? And so one thing that helps is if there is an actual technology that everyone can try out for themselves, then it is very hard to just completely gaslight people about what it can do or what it can't do. I mean, once, you know, ChatGPT came out, right, then, you know, in. In both directions. You know, either the people saying, you know, this is already a superhuman intelligence and it will, you know, immediately take over the world, or, you know, or it'll. It'll. It'll put all, you know, scientists out of jobs, right? It's like, well, no, you can try it, and you can see that it's not there yet. But also the people saying, you know, this is nothing. This is just a glorified Eliza chatbot from the 1960s. You know, it doesn't, you know, understand anything. It can't really do anything useful. It's like, no, no, you can try it yourself, and you can see that it's. It's. It's. It's well past the point where it can do useful things for you, right? And I think people, you know, decades ago, if you had shown it to them, then they would have said, this is, you know, this is science fiction. This is, you know, they would have said this is like computers from Star Trek or whatever. But the point is that these sort of gaslighting narratives by people with agendas, you know, they. They exist in AI, but they always have, you know, have to compete against people's firsthand experience with, With. With. With using the actual models. Now with quantum computing, you know, you don't really have that, right? With quantum computing. Like, I mean, there are real devices, right? But people Learned, you know, 15 years ago, right, that they can just put out a press release saying, you know, we use the quantum computer to recognize handwriting. We use the quantum computer to, you know, help route vehicles, you know, through a city, right? We use a quantum computer to train a neural network. And journalists and investors will eat that up with mustard, right? There'll be, you know, that's what they want to hear. That's the narrative that they want. And, you know, and then these people use the real quantum computer, so what's there to argue about? And they won't ask, like, the very first question that any scientist would ask, which is, well, did you get an improvement over a Classical computer.
- [27:32]
D
Right.
- [27:33]
C
Did you actually, you know, is there any hope that by, you know, this route, you are going to beat a classical computer at the same task? And all of us who do quantum computing research, we know that that's the hard part, but that is the part that we really have trouble communicating to the public. And it would be hard in the best of cases, but when there are hucksters who are very much trying to confuse people and trying to spread the misleading narrative about it, then it's all the harder. So I've been trying to do this on my blog for 20 years, and, you know, I can, I can, you know, I'm able to reach some people, but orders of magnitude fewer people than the hucksters are able to reach, probably.
- [28:20]
B
Yeah. And, you know, that's part of why I was so excited about talking to you today, because I think that the role you're providing here is absolutely vital. Because people, people need to understand that just because it is such a complex topic.
- [28:39]
D
Right.
- [28:40]
B
And even the bright, some of the brightest people I know just cannot get their, wrap their minds around it. So into that sort of confusion, as you point out, hucksters, boy, their narratives sound good, boy, you know, like, oh, this is the best thing since, you know, fill in the blank. How would you go about, like, if we gave you a platform which you could reach, like, the majority of people who have more than a passing interest? Let's narrow it down to investors, for example, who would be being approached by startups or existing companies. If you were their advisor.
- [29:19]
C
Yes.
- [29:19]
B
What would you urge them to do? What questions would you have them ask?
- [29:24]
C
So I have been an advisor to various investors in quantum computing companies. And, you know, and you know, of course, there are investors who do want to ask all the right questions because it's their own money on the line.
- [29:37]
D
Right.
- [29:38]
C
And so some of the questions that I would ask are, okay. I mean, of course there's. What does this company actually do?
- [29:47]
D
Right.
- [29:48]
C
There are some quantum computing companies that are building actual hardware.
- [29:52]
D
Right.
- [29:53]
C
And then, you know, there are others that are not building hardware, but that are just trying to provide the middleware. Sort of like they're building the higher levels of the tower before the base of the tower has been built.
- [30:04]
D
Right.
- [30:04]
C
So they're, you know, they're hoping that, like, once someone has a, you know, useful quantum computer, then it will run their software or it will use their tools. So then, you know, it's a, it's a different discussion, you know, depending on that.
- [30:17]
D
Right.
- [30:18]
C
But then usually there are lots and lots of claims about, you know, what they can do experimentally, what they're hoping to do in the next, you know, few years. Right. Like every quantum computing experimentalist has, you know, these like super aggressive timelines that, you know, by 2026 we're going to have this. By 2027 we're going to have this. You know, and I've been in this field long enough that I don't take those timelines all that seriously.
- [30:46]
D
Okay.
- [30:46]
C
But you know, we've also seen that yes, there really has been a lot of progress. I mean, the degree to which people can control qubits programmably and protect them against decoherence. I mean, it is unbelievably better than when I entered this field 25 years ago.
- [31:03]
D
Right.
- [31:03]
C
If you just look at the numbers, it is getting close to the key threshold called the fault tolerance threshold, which is where error correction becomes a net width. It's like where you have almost like a self sustaining reaction, right. Where you can correct errors faster than you're introducing new errors. So that's kind of the key crossover point where, you know, we expect things to scale and we think, you know, if you could control two qubits with like 99.99% accuracy, then, you know, you'd be probably past that threshold. And within the last year we've seen various groups that can control two qubits with like 99.9% accuracy. So they're like one nine away. Now compare that to when I entered the field when it would have been amazing to control two qubits with 50% accuracy. So there is real progress. And so you can't say, even with any confidence that this won't happen within the next decade. But what you can do is you can look at what else are these people claiming. If they are saying we're going to use our quantum computer to solve optimization and machine learning problems and we're going to beat classical computers and we're going to do it in the near future. And then you could say, well, what algorithm are you going to use? Because one thing that we do know a lot about, you know, for, for 30 years now is, you know, we know something about quantum algorithms and what kinds of speed ups a lease can be obtained, you know, based on any of the known algorithms.
- [32:45]
D
Right.
- [32:45]
C
And so, so if they're not saying something that is rooted in, you know, one of these known quantum algorithms or these known classes of speed up, then they're basically just saying we're going to cross our fingers and hope that Some completely new, you know, we'll just build the quantum computer and then in addition to solving all the problems of building the quantum computer, we're going to make some brand new algorithmic discovery, right, that other, you know, and it'll just work out in our favor, right? And then, you know, it's like, okay, you can hope that, but someone could just as well hope that with a new classical algorithm that they'll get some revolutionary improvement, right? We're very far from knowing the limits of classical algorithms either. So those kinds of claims about what they're going to use the quantum computer for, you know, you can, you can judge, right, to a, to a great extent, you can, you can compare to, you know, the, what we actually know in quantum computer science. And if someone is saying, well, you know, we will use our quantum computer, at least at first, to simulate quantum mechanics, we'll use it to, you know, simulate material, simulate chemistry, because that's where we're the most confident that a quantum computer is useful, you know, and then eventually it can be used to break public key encryption, which is not necessarily a positive application for the world, but it's at least for whichever intelligence agency got it first, if no one else knew that they had it would be useful for them. But in any case, as a clear demonstration that if you really have a scalable quantum computer, that's been the gold standard for 30 years, and that's because of very special properties of these, you know, the, the, the cryptographic codes that we happen to use today that sort of makes them amenable to these exponential quantum speed ups, right? This was the great discovery of Peter Shor 30 years ago that really launched quantum computing as a field. Okay, so, so yeah, and these, and, and 30 years later, I think these remain the two clearest applications of a quantum computer that we know about. One is simulating quantum mechanics. And that's the economically most important one that we know. That's the one that Richard Feynman and David Deutsch talked about already 40 some years ago. But that could help in designing better solar cells, better batteries, better ways of making fertilizer. There's any number of things that, that might conceivably help with. You'll have to beat the best classical approximation methods. So, you know, even there it's not obvious, but at least you'll have many shots on goal, right? You know, and then, and then there's breaking public key cryptography, right? Which is like any classical computer scientist at that point, even if they don't know or care about quantum mechanics. Like they will have to. All the skeptics of quantum computing will then have to admit that, okay, yeah, I guess we were wrong. I guess that this works.
- [35:49]
D
Right?
- [35:50]
C
And then beyond that, we don't really, you know, we kind of don't know. You know, what else a quantum computer will be good for? You know, after 30 years of research, I wish that we had better answers. Like for optimization and machine learning problems, there are modest speed ups, something called Grover speed ups, that will eventually be relevant. Okay, but they're, you know, they're not exponential speed ups.
- [36:15]
D
Right.
- [36:15]
C
And it'll probably take a very long time before those become a net win in practice. Okay, so. And are there bigger speed ups for optimization, for machine learning, for finance? You know, I think that remains an open question, remains something where we don't know. And so one thing that I look for when let's say I'm consulting is, does this quantum computing startup understand all of that and are they honest about all of that?
- [36:42]
D
Right.
- [36:42]
C
And you know, if they are, then I say, okay, well, it's your money, right? If you want to, you know, take a gamble on this, then, you know that I'm very much in favor. And I hope that these people succeed and, you know, they are, you know, telling, telling the truth as best as they can, and they're, you know, doing what you can do in this situation.
- [37:03]
D
Right.
- [37:03]
C
But if, if the people say we want a quantum computer because it's going to be the next step of AI, it's going to just be the next step, you know, after Moore's law, that will speed up everything that we do with computers, then I say, these people are just telling you what you want to hear and it doesn't connect to what we actually know about quantum algorithms.
- [37:25]
B
And as I listen to you, I hearken back to Asimov's rules for robots and your idea of programming in the AI, the idea of humans being special because of all those various reasons. And I completely agree with your assessment that the challenge there is that you're freezing knowledge, I guess, at a particular moment in time.
- [37:48]
D
Right?
- [37:48]
B
And we don't know what we don't know yet. We don't know what we haven't discovered yet. And yet it does seem to me that there is an urgency around quantum computing that you've written about.
- [38:04]
C
Because.
- [38:07]
B
If some authoritarian regime unlocks quantum computing system, specifically if we just kept to cryptology, that's not, that's not a good outcome for those of us in the West. I would, I would posit, I Mean.
- [38:23]
C
Yeah, I mean, we should, we should, we should clearly separate quantum computing and AI, Right? Two different discussions. Okay, but they do intersect each other in certain places. Right, but with quantum computing, we actually understand the issues, you know, I would say, a lot better than we understand them for AI. Right, because AI, Right. You know, once it can do everything that we can do and more, then you could say, you know, what is our, what is even our place in the world?
- [38:48]
D
Right.
- [38:49]
C
You know, what does the AI want to do with us? And you know, those are enormous questions, right, with, with quantum computing, you know, we, okay, you could say at some level it is merely, you know, a new kind of computer that is faster at certain specific tasks and we have some idea of what those tasks are, you know, and we know what some of the ramifications of that would be.
- [39:11]
D
Right.
- [39:11]
C
And specifically there is, you know, yes, quantum computers would happen to be able to break most of the encryption that currently protects the Internet. Okay, but now you know, now you know, and of course that has geopolitical, you know, implications. And you have to assume that, let's say the NSA and its counterparts in other countries have already stored vast amounts of encrypted data that they could break in the future, that they could decrypt in the future if they had a quantum computer, which means people today who want their data to remain secret even from big governments 10 years from now or 15 years from now, they should probably already be looking to migrate their encryption. Okay? And people have been thinking about this. There is for the last decade or more, there has been a whole push to do what's called post quantum encryption or quantum resistant encryption. And this is new forms of encryption, you know, mostly still just on classical computers.
- [40:21]
D
Right.
- [40:21]
C
So just conventional forms of encryption. But that does not seem to be breakable even by a quantum computer.
- [40:29]
D
Okay.
- [40:29]
C
And we've learned a lot about this. The good news is that we now have pretty plausible candidates for post quantum encryption schemes. The most important class is based on what are called lattice problems, like finding short vectors in high dimensional lattices and related problem called lwe, learning with errors. And so nist, the National Institute of Standards and Technology, had a competition that ran for five years, just ended a year or two ago, to decide on standards for post quantum encryption. And you know, and they did decide to use these lattice based encryption systems. And so, you know, now there's like a giant but mundane problem. You could say you need to get every web browser and every router and every server in the world to upgrade so that we will Use HTTPs and ssl and all the protocols that we use to secure the Internet will be based on these quantum resistant protocols. So it's like, in principle, we think we know the answer, right? But there's, you know, a huge slog to actually get there. And any time you change your underlying encryption system, like you could create new security holes, right? Like, it's possible that, you know, these new encryption systems will be breakable just because there haven't been enough eyes on them for a long enough time.
- [41:56]
D
Right?
- [41:57]
C
They just haven't been studied enough.
- [41:59]
D
Right.
- [41:59]
C
They might be, you know. You know, it might be that even as we fortified, you know, our front door and put a moat with alligators and you know, we left the screen door open in the back, right? Like that. That kind of thing usually happens in computer security, right? So, so, you know, so, so it'll be a messy transition, but you know, hopefully if the transition goes well, then we'll all just be right back where we started, right? You know, well, we'll have quantum computers and we'll have public key encryption that the quantum computers can't break. Now, do we have a proof of that? Well, no, I mean, we know we don't even have a proof that any of these crypto systems, you know, the ones we use now or the future ones, are secure against classical computer, right? And there are some of the most profound unsolved problems in theoretical computer science and math, like the P vs NP problem are very much related to that. To like, proving that P is not equal to NP would be a prerequisite to proving any of these cryptosystems are secure, right? So in none of these cases do we have a mathematical proof of security, right? The best that we can say is, well, people have tried for half a century to find a fast classical algorithm for factoring numbers, for example, or for calculating discrete logarithms. And at least so far as is publicly known, none of them have succeeded. You know, if the NSA has a secret algorithm that we don't know about, right? And they've now tried for almost half of that long for like 20, 25 years to look for quantum algorithms for solving these lattice problems, and they haven't found those either. So that, that, that's sort of what we can say to people who are worried about the security situation. But yeah, there's a lot of work that has to be done, including, by the way, upgrading the architecture of Bitcoin and Ethereum and all the other cryptocurrencies to use these quantum resistant encryption schemes.
- [44:05]
B
I have a friend who is a cryptologist and he was musing to me, we were talking about quantum computing and breaking and encryption, et cetera, and he just kind of paused and said, well, with all the classical computers, always seemed to me that the weakest link was the human. And then he gave all sorts of examples, like the Stutnex thing. I mean, what are your thoughts on that and how would that be addressed under a quantum computing regime?
- [44:35]
C
I mean, the short answer is that wouldn't change. That would just still be true.
- [44:39]
D
Right.
- [44:40]
C
I mean, the standard line is that, you know, a large fraction of errors take place in the seat to keyboard interface.
- [44:47]
D
Right.
- [44:48]
C
You could have the best cybersecurity in the world, right? But if someone calls, you know, the person in charge and says like, hey, this is Bob from, you know, over in Tech. Do you have the root password? And you know, and the person just gives it to them, right? As is, you know, think people have done that where like, you know, half, like half of the time people will just cooperate and give the password over. And then even when they won't, then you just, ten minutes later someone else calls and they say like, hey, this is Tom. You're not going to believe this. Someone has been phishing trying to get the, the root password. So we need to reset them. Can you just give me the password so we can reset it and then a large fraction of the remaining people will tell you the password then, right? So, you know, there is no quantum computer, there is no classical computer that is going to defend against, you know, against that, against, you know, person who just decides to override the security because they were tricked into it, talked into it, whatever.
- [45:50]
D
Right?
- [45:52]
C
That's not a computer science problem. You could say that's a human problem.
- [45:56]
B
Yeah, it's definitely a human OS problem. And it reminds me of the Terry Pratcher quip about you could find the deepest, darkest cave in the deepest darkest forest and you could put a switch that says do not turn this switch on as it will destroy all of reality the moment you did it. He said the paint wouldn't be dry before you even went in. Or someone that switched, right?
- [46:21]
C
Well, no, I mean, I mean in, in the AI safety discourse, you know, there was a lot of discussion for, for a long time. Well, look, you know, if we want AI to be safe, that's easy. You just have to not release it onto the Internet. You know, just keep it on some air gap computer where, you know, you can pull the plug as soon as something goes wrong. Okay. And so you know, if anything has become clear in the last few years is that none of that is going to happen.
- [46:46]
D
Right.
- [46:47]
C
It's like, you know, that. That that horse has left the barn, Right. You know, there are already, like, you know, GPT enabled agents that people have released onto the Internet to, like, with instructions to cause as much chaos as possible.
- [47:02]
D
Right.
- [47:03]
C
There's this thing called chaos GPT that just, you know, and the, you know, the one thing that protects us is that they're not very good at it. You know, they just keep coming up with vague plans to take over the world and then not really being able to execute on them.
- [47:19]
D
Right.
- [47:20]
C
But the part where no one would even try it, that just didn't happen.
- [47:28]
B
The other thing that you write really well about is the limit. Let's accept and say, yes, quantum computers are cheap and there are numerous implications of things that we can do with them from high to low, et cetera, but they too are going to have limitations.
- [47:48]
C
Yes, right, yes.
- [47:50]
B
Talk a little bit about that, because often when I'm talking to people who really don't, they're not, like, into it. Like, I had the hardest time getting them to understand. No, no, no, no, no. And you're not creating a God. It's going to have limitations.
- [48:03]
C
Right, Right. So we've touched on this already, right? That. But, you know, basically, a quantum computer is a very, very special kind of device, right? It is the new kind of computer, you know, that would exploit the rules of quantum mechanics to solve certain specific problems much faster than we know how to solve them now. But, you know, the rules of quantum mechanics, you know, have this very, very specific form, right? They're not magic. You know, they don't say, like, you get to just try every possible answer in parallel or in a different parallel universe and then magically pick the best one. That sort of really is too good to be true.
- [48:40]
D
Right.
- [48:41]
C
I was like, you know, what's true is, you know, with a quantum computer, you can create what's called a superposition of many different states, including of all the different answers to your computational problem.
- [48:51]
D
Right.
- [48:51]
C
Like, you know, the. That you can do and. Okay, the trouble is, for a computer to be useful, at some point, you have to look at it, you have to measure, you have to get an output, right? And if you just took this equal superposition over all the answers and you didn't do anything else, then the rules of quantum mechanics tell you that all you're going to see will be a random answer. And, well, if you just wanted a random answer you didn't need a quantum computer for that. You could have just flipped a coin a bunch of times, right? Or just use that classical computer with a random number generator. So the only hope of getting a speed up with a quantum computer is to exploit the way that sort of the quantum rules of probability are different from the classical rules, okay? And the way that they are different involves negative numbers, involves minus signs, right? So like in everyday life, you know, you, you know, you talk, we, we already use probability. We talk about, you know, 30% chance of rain tomorrow, 70% chance. We'd never talk about a negative 30% chance of rate. That would just be nonsense, right? So now what was the key change that quantum mechanics made to our understanding of the world when it came along 100 years ago? It was not just to introduce probability. And people have heard that Einstein couldn't believe that God would play dice and blah, blah, blah. But the truth is, if it was just a matter of God rolling some dice once in a while, that wouldn't.
- [50:24]
D
Be a big deal.
- [50:25]
C
Okay, that you could sort of handle with that would. That would still basically be classical physics, right? The key new thing is what kind of dice these are, okay? And they involve these new numbers which are called amplitude, okay? And amplitudes are related to probabilities, but they're not probabilities because they can be positive or negative. In fact, they can even be complex numbers, could involve the square root of minus one. And so now the rule is, if I want to know how likely something is to happen, like for a particle to hit a certain spot on a screen in the two slit experiment that you mentioned before, or for a quantum computer to produce a certain output, then I have to add up a contribution from every path that my system could have taken to get to that outcome, and each one makes a contribution to the amplitude. But now what happens is if some of the contributions are positive, let's say, and some are negative, then they can cancel each other out or they can interfere destructively, as we say, so that the total amplitude is zero, which means that that event won't happen at all.
- [51:43]
D
Okay?
- [51:44]
C
Whereas for other possible events, right? If I can get all the contributions to their amplitudes to be pointing the same way, then those are the outcomes that can happen. Okay? So with every algorithm for a quantum computer, what I'm trying to do is choreograph a pattern of interference among these amplitudes so that for each wrong answer, each one I don't want to see the contributions to its amplitude are canceling out and the total is close to zero. Whereas for the right answer or the output I do want to see the contributions to its amplitude are reinforcing each other. If I can arrange that, then when I measure, I'll see the right answer with a high probability. And, you know, if, if the probability is not 100%, that's okay. I can run the computer several times until I see it. But I've got, if I want any advantage over just a classical computer with a random number generator, then I need to use this interference effect, right, to concentrate more amplitude onto the right answer quickly. And the hard part is, first of all, I've got to choreograph all that, even though I don't know myself which answer is the right one, right? If I already knew, what would be the point? Secondly, I've got to do all of this faster than even the fastest classical algorithm could do the same thing. So basically, nature gives us this really bizarre new hammer, this interference hammer, and then the task of a quantum computer scientist is to figure out, well, what nails, if any, can that hammer hit, right? And a priori wasn't really obvious that this ability would be good for anything other than simulating quantum mechanics itself, right? It was a big discovery 30 years ago when Peter Shor showed that the problems that underlie modern public key encryption, like factoring huge numbers and discrete logarithms, just so happen to have a form that is amenable to a giant speed up by setting up this kind of interference pattern. That was a very, very non obvious discovery. And I mean, I teach it in my undergraduate class and to students who've only seen linear algebra and classical programming. So it's not that advanced, you know, that I can't teach it to undergrads, but it takes me three lectures to explain it, right? And so, you know, if it was just a simple matter of try all the answers in parallel and, you know, and then just magically pick the one that has the factors of your number, well, then you wouldn't have needed Peter Shor to think of it, right? So once someone understands that, right, then they can see that, you know, a quantum computer is not just a general purpose magic box to speed up anything, right? It speeds up only those problems for which we can choreograph this kind of interference pattern. And the amount that it speeds them up depends on what is the fastest way that we can figure out to choreograph that interference pattern. So we still have to work hard, just like we had to work hard to discover algorithms for classical computing computers, right? But we have this one new tool in our toolbox, this one new hammer, okay? And sometimes that hammer helps a lot. So like I said, the two biggest places where it helps a lot that let's say someone outside the field would know or care about are, number one, simulating quantum mechanics itself, number two, breaking current public key cryptography. And then for a wide range of other problems, including in AI and machine learning, in optimization, in finance. We know how to get more modest advantages from a quantum computer. And it'll probably take much longer before those modest advantages become a win in practice compared to what people can do with a classical computer. But, you know, but at least theoretically, those more modest advantages exist. Now, a holy grail of the field has been find some other classes of applications that really matter in practice and where you get a huge, like, exponential advantage.
- [56:11]
D
Right?
- [56:11]
C
And some people are very disappointed that we haven't clearly found that, you know, or they are. They blame us. They say, you know, what have you been doing all this time, right? Where, you know, it's like the story of Rumpelstiltskin, right? You know, you spun this straw into gold, so why not that straw, right? You know, where are, where are the more quantum algorithms that I expected? And you know, and I always answer those people, I say, well, who told you to expect more? It wasn't me, right? You know, maybe, you know, we should, we should treat the quantum algorithms that we have as kind of, you know, even those are kind of miracles, right? They didn't have to exist. And so, you know, we have no right to demand of the universe that give us more and more and more quantum speed ups. But of course we'll keep looking and of course we'll try to find more. You know, that's like, what do you think we do all day.
- [57:03]
B
On the one that you mentioned that does seem applicable and likely, which is the understanding quantum mechanics better.
- [57:11]
C
Yeah.
- [57:12]
B
What sort of things would you get very excited by? If you had the access to a quantum computer that was operating properly and we were simulating quantum mechanics on it, what would you say? What would be the Eureka moment of those tests?
- [57:31]
C
Yeah, so it's an excellent question, and it's a little hard to answer because it's not like there's one big thing that we're waiting on a quantum computer to do. There's like a lot of things that, you know, it's like a fishing expedition, right? That, you know, you can cast your rod in a whole bunch of different areas and hope that you, you know, with at least one of them you will make a discovery that will have a big impact on chemistry or material science or, or, or, or nuclear physics or, or some area like that. Okay. But I can tell you, you know, the, the examples that people have put forward, you know, one of them is simulating the chemical reaction in the Haber process that makes most of the world's fertilizer.
- [58:17]
D
Right.
- [58:17]
C
There is some many body quantum effect there that no one really understands. And if we did understand it, then it's possible that we could make fertilizer for cheaper using less energy, which would, you know, that's a significant percentage of all the world's energy expenditure.
- [58:33]
D
Right.
- [58:33]
C
One would also want to use a quantum computer to simulate the Fermi Hubbard model, which is like a theoretical model of condensed matter physics, and do a bunch of other simulations that could give us ultimately help us understand how do high temperature superconductors work, which is another many body quantum effect that no one really understands. No one fully understands yet. And you could hope that with that understanding, maybe if we're lucky, would come the discovery of new, better high temperature superconductors that could then be used to transmit power with lower loss or, you know, build levitating trains or whatever.
- [59:19]
D
Right.
- [59:19]
C
You could simulate biochemical processes.
- [59:23]
D
Right.
- [59:23]
C
So like the companies that do combinatorial drug design, Right. Where, like the step where you have to search through exponentially many different drug candidates. Quantum computer doesn't obviously help you very much with that step.
- [59:38]
D
Right.
- [59:38]
C
You still have this exponential search, but the step where you have a drug and then you just have to synthesize it in a wet lab and see what it does.
- [59:48]
D
Right.
- [59:49]
C
Or you have to use gigantic classical computers to try to approximately solve the Schrodinger equation and see how this drug binds to a receptor or whatever. For that part, you could substitute in a quantum computer and maybe that helps with drug development.
- [60:08]
D
Right.
- [60:08]
C
It's, you know, you know, I can't say for sure that it doesn't.
- [60:11]
D
Right.
- [60:12]
C
Likewise, the chemical reactions that are involved in sequestering carbon from the atmosphere.
- [60:18]
D
Right.
- [60:19]
C
The chemical reactions that are involved in high performance batteries.
- [60:23]
D
Right.
- [60:23]
C
You know, these are all very important, you know, societal problems where, you know, you could throw a quantum computer at them if you had one, and it would be another resource. It wouldn't magically solve the problem for you. But I think there is a strong case that it could help push the discovery forward.
- [60:42]
B
And what would you think? Obviously leaving room for error, what would you think would be some of the ones that get people very. And let's make it Educated laypeople. Again, let's take it away from scientists who will probably not get as excited as that educated layman getting pitched something. What do you think is completely beyond the quantum computer with some of the use cases that you've heard?
- [61:09]
C
Yeah, so there's, you know, this whole holy grail of computer science for, you know, half a century or more has been what are called the NP complete problems, right? And this is a class that includes the traveling salesman problem, includes finding proofs of theorems, scheduling airline flights. Basically, anytime you have a problem with, you know, a whole bunch of constraints that might conflict with one another, and you're trying, you know, you have a huge number of variables and you're trying to set them to, to satisfy all the constraints or to violate as few constraints as possible, then such problems will typically fall into this NP complete class unless they have a very good reason not to.
- [61:54]
D
Right?
- [61:54]
C
And an NP complete, it's a technical term, but it basically just means at least as hard as any other problem that has a fast algorithm for verifying solutions. Right, that's, that's sort of what it means. You know, it was a big discovery in the 1970s that, you know, a huge number of the optimization and constraint satisfaction problems that we care about all happen to fall into that same universality class.
- [62:22]
D
Right.
- [62:23]
C
And, you know, and since then, maybe, you know, the most famous unsolved problem of theoretical computer science has been what we call the P versus NP problem, which precisely, you know, asks, is there a fast algorithm on a classical computer for solving these NP complete problems? If P equals np, then the answer is yes. If P doesn't equal np, then the answer is no. And, you know, almost all of us guess that P doesn't equal np. I like to say that if we were physicists, we would have just declared that a law of nature and given ourselves Nobel prizes for it. But because we're more like mathematicians, we have to admit that that is an unproven conjecture that we hope will someday be proven. But then once quantum computing came along, then people could ask a new question, which is, are NP complete problems efficiently solvable in a quantum by a quantum computer? The way we ask it is, involves this class bqp bounded error, quantum polynomial time, which is sort of all the problems efficiently solvable. Quantumly, we ask, is NP contained in bqp? But most of us conjecture that the answer is no. Okay. They sort of reign in conjecture for almost 30 years has been that the, the, the, the best quantum speed up that you can generally get for these NP complete problems is the Grover speed up, which roughly speaking, lets you solve NP complete problems at about the square root of the number of steps that a classical computer would need. So you get some advantage. But you know, as I was saying before, it's a modest advantage. It's not one that turns in exponential into a polynomial. And then, you know, other examples where a quantum computer doesn't seem to help that much, simulating like classical physics, like simulating the weather or you know, differential equations like that, there might be some quantum advantages to be had there. But in general, like if I have some classical dynamical system and like I need to like compute its state at each moment in time in order to get the state at the next moment in time, then pretty much I just have to go step by step by step and just trace through the evolution. Then a quantum computer is going to have to do the same thing, right? There's not like a magical quantum way to shortcut to the end of that. So, so those are, those are some of the classes where we expect only a modest quantum speed up, if any. But then, you know, sometimes when I, when I talk to laypeople about this, like they're under the impression, well, you know, I'm going to have a quantum computer on my phone and it'll help me, you know, with email or it'll help me with games. And I'm like, you know, what do you want a quantum computer for, for any of that stuff. I was like, you know, to the extent that, you know, our software is not doing what we want, it's probably just because it's full of bugs, you know, it doesn't really understand us, right? But these are not like computational complexity problems, right? These are not the kinds of things that we expect a quantum computer to fix, right? And even, even once we do have quantum computers, totally unclear why you need one in your house or on your phone. Because today we have something called the cloud, right? We have, you know, you can just tap in over the Internet to, you know, these, you know, quantum computing resources. You know, that whenever you do need them, right, you don't have to offload it and put, you know, miniaturize it, put it onto everyone's phone. So I think of a quantum computer mostly as like a special purpose accelerator for these special problems where we can choreograph these interference patterns to get these big speed ups. And we don't know exactly how big that class of problems is. You know, we've been trying to figure it out. You know, we know some Things that are. That are, that are that are there and we try to expand it. But if that would expand to the NP complete problems or to simulate in dynamical systems or things like that, then I would be very, very surprised.
- [66:37]
B
The idea though, that I always have a hard time conveying to people who, like, I love your joke about I want a quantum computer on my phone so my games run faster.
- [66:48]
D
Right.
- [66:48]
B
Like, because people think that, oh, well, that just sounds cool. But, but the, but the, but the problems that you highlighted that we actually can address, I have a hard time getting people to understand how incredibly meaningful and how much of an advance that would be. Your idea about fertilizer being a great example.
- [67:13]
C
My idea, by the way. Well, yeah, yeah, yeah, right.
- [67:16]
B
You're in conversation work by a lot.
- [67:18]
C
Of people who of course, who studied these examples that this was a group at Microsoft in 2016 that did that one. But yeah, I mean, look, there are just lots of times that our computers frustrate us. Like, you know, we can't print something out because, you know, the printer driver doesn't work. Or, you know, you take the crowdstrike thing that happened, you know, a month ago where like a large fraction of all the, you know, computers in the world went down because they pushed out this update to the security software that was, that by mistake was an empty file.
- [67:50]
D
Right.
- [67:51]
C
These are not things that a quantum computer obviously helps you with. These are once again, you could call these seat to keyboard problems.
- [68:02]
B
I love your idea of blank faces and I equate it immediately with bogans. I don't know if you're a Douglas Adams fan.
- [68:11]
C
Yeah, no, it's just a term that I've used for a while for like, you know, people who, you know, I don't know, you know, tell me that like, you know, my kids, you know, cannot use a certain swimming pool even though we paid for it because of some ridiculous rule that they, you know, either made up on the spot or that was buried somewhere. And it's like, you can't, you realize that like, like, you know, you can't have a human conversation. Like, you know, there, there are sort of people who, who decided to act like chat robots, right? Who sort of, who sort of robotified themselves, right? And this is, this is, I think a very common thing that one finds in bureaucracies, right? But you know, there was a really interesting case, you know, earlier this year where, what was it? Air Canada, you know, had a, had a customer service chatbot, right? And someone talked to this chatbot about, you know, getting A bereavement fare, like, you know, and saying, like, well, I can just pay out of pocket and then get reimbursed later for the bereavement fair.
- [69:15]
D
Right.
- [69:15]
C
And the chat bot said, yeah, that's fine. And then the humans overrode that. They said, no, you can't. And it doesn't matter that the chat bot said that because that's not our actual policy.
- [69:26]
D
Right.
- [69:26]
C
And then this actually went before a judge, and the judge ruled that no Air Canada had to honor the policy that it's chat bot had hallucinated.
- [69:37]
D
Okay.
- [69:38]
C
It had to honor its large. You know, and this might even be an important precedent.
- [69:42]
D
Right.
- [69:42]
C
As. As large language models, you know, permeate more of our lives. I think that the judge made the right ruling.
- [69:49]
D
Right.
- [69:50]
C
But what is fascinating here is that this chat bot, in some sense was more human than the humans were.
- [69:57]
D
Right.
- [69:58]
C
You know, it was the one that was trying to be sympathetic, trying to be reasonable. Right. It was the humans just robotically reading the policy, no matter how stupid it was.
- [70:09]
B
I love that story. I'm getting the hook from my producer here, Scott.
- [70:14]
C
Yeah, I better run to my next meeting as well.
- [70:17]
B
But one last question, though. We're living in a fantasy fiction here, and we can magically make you emperor of the world. You can't put anyone in a re education camp and you can't kill anyone.
- [70:31]
C
But we are going to give you.
- [70:32]
B
A magical microphone in which you can say two things that the next morning, everyone that is on the planet currently is going to wake up and say, you know what? I've just had two of the greatest ideas, and unlike all those other times, I'm going to act on each one of these ideas. What two things are you going to incept in the world's population?
- [70:56]
C
Oh, gosh. Well, I feel like one of them should be the golden rule, Right. Or it should just be, you know, morality.
- [71:04]
D
Right.
- [71:04]
C
Maybe the other one is Bayes Rule. It's just, you know, understanding base rates.
- [71:11]
D
Right?
- [71:11]
C
Understanding. Yeah. Like, you know, so maybe you, you know, I'd have to think about it a little bit more, but I feel like I want to use one of them for a basic principle of morality, and I want to use the other one for a basic principle of rationality.
- [71:26]
B
I love both of those. And in my days as an asset manager, one of the things that I had the hardest time getting regular folks to understand was the power of base rates. So amen to both of those, Scott. Thank you so much. This has been so much fun.
- [71:42]
C
Oh, great. Yeah. It's been fun for me, too. Thanks for having me.
- [71:46]
B
All right, thanks, guy.
- [71:47]
C
All right, talk to you later, Kim. Okay, bye.
- [71:48]
B
All right, bye.