Authors in August: Vasant Dhar & “Thinking With Machines”

27:18As George Shultz, the former Secretary of State, once wrote, he entitled an influential essay I remember reading, Trust is the Coin of the Realm. And I know that you are of this school as well, Vassat. Would you tell the story of jumping into a swimming pool next to your dad as a kid? And When can we trust AI and when can we can't and how can we tell the difference? You know, I have this chapter on trust in my book and I start that off with this vignette where, you know, we'd gone to the swimming pool. It was in one of these sort of colonial, big colonial clubs in India, big swimming pool, you know, and my I was with my dad and he jumped in and he said, hey, come on, jump in.

27:59And I didn't know how to swim, but I just jumped in. How old were you? I don't know, six. Wow. Wow. You know, and I don't know how to swim, but, you know, he was there and, you know, I sort of jumped right in. I went to the bottom, I came up, you know, and I felt him sort of propping me up, you know, pushing me a little bit away, seeing if I could swim and, you know, I sort of managed. And then he said, see, now you can swim, you know, but the reason I jumped in was because there was just complete trust. You know, I knew that nothing bad was going to happen. You know, if I went to the bottom, he'd like drag me up.

28:29So complete trust. And so, you know, I sort of opened the chapter with that incident and then, you know, talk about, you know, trust in the broader sense, you know, and whether we should trust AI. Now, I wrote this article in the Harvard Business Review like 12-ish years ago, I'm forgetting, called, you know, when to trust robots with decisions and not to. And that was based on sort of about 10 or 15 years of, you know, real, you know, implementing algorithms in finance and sports and medicine. And the question I came up with in each of those domains was, why should I trust the algorithm, right?

29:07Why do I trust this algorithm in finance that's wrong almost half the time, you know? And then when I asked myself, why I don't trust a driverless car, that's rarely wrong. You know, the answer sort of became so obvious, which is that it depends on the cost of error, right? If the cost of error is really high, you're going to be reticent to trust something. You know, if the cost of error is low, not much to be lost, trust it, especially if it doesn't make mistakes that often. So that's what I realized is that trust really depends on how often an answer will be wrong and the consequences of the error.

29:43That is the consequence of being wrong. And when I looked at the world in that sense, it all made sense, right? That is my finance algorithms are wrong a lot, but the cost of error was low because I take very little risk in each position. I've got hundreds the positions on during a day, even a position blows up, it's not going to blow up my portfolio, right? There isn't that huge sort of systemic risk. On the other hand, in a driverless car, and by the way, I have had a near-death experience, you know, a little over two years ago, you know, so the costs of error there are very high, like death.

30:15And so I would hesitate before I trust an algorithm in a situation where the cost of error is death. Part of my own experience, and I use ChatGPT and have every day for three years now, but not 30 years. But part of my experience has been that, yeah, it hallucinates. And you certainly go right there in your book. And by the way, let me mention your book, Thinking with Machines, 2026. Like I've read it in full because I always do before an author in August podcast. But this is really fresh. You are reacting to things that were just months ago, in some cases, Vasant, although you're able to look back decades ago.

30:51But one of the points that you make in and around trust, and I always feel this with Chad Chippity or, as you mentioned, Claude, is when you can get it not just to identify an answer or give a pattern, but explain, explain itself. For example, your list of 10 stocks for Claude yesterday. I know that you are smart with prompting and so much of AI seems to be who's smart with prompting. But asking the AI actually to explain its decisions or choices, maybe not in every circumstance is that possible, but doesn't that greatly increase the trust that we have? It does. And, you know, as and you mentioned sort of sensemaking a little bit earlier, right, that I've actually spent most of my career, most of my time actually making sense of the outputs of the AI, you know, and that is critical because that's what people always want to know, like what's, you know, right, number one, what's the story here, like what's it really doing at a high level, like explain the story, right, the story really matters, right, the connection between the story and the numbers is critical, right, so what's the story, and then they want to know why does it work, why does it fail, when does it work, When does it fail?

32:03And so it's just a constant process of probing and sense-making. And very often it results in failure. That is, you just cannot explain it. And if you just can't explain it and find a sort of a logic behind it, then you're much more uncomfortable with the question about whether this is real or ephemeral. And that's true in every domain, but it's particularly challenging in finance because finance is such a noisy problem, such a noisy problem, right? You can have two situations that seem virtually identical and yet the outcomes are very different, right? That confuses the hell out of the machine and it also makes it much harder to explain something, right?

32:52So in finance, I find myself explaining things in two ways. One is in drawing analogies of a new system with systems that we already understand. So, for example, people understand trend following, they understand momentum, right? So you can explain the system by saying, well, it behaves like long-term momentum when volatility is low, but it has a very short-term momentum orientation when volatility increases, right? An explanation like that starts to make sense to investors, right? You know, someone can nod along and say, okay, you know, I can buy that, that, you know, in volatility is low, you sort of, you know, you go with the trend when it's high, be careful because things will revert more often.

33:38And then you will also show that the system actually changes positions more often when things get volatile versus when they're quiescent, right? So it's those kinds of things that I find useful in trying to explain the behavior system is drawing an analogy between that and things that we already know. Yeah. Scaffolding that we have as investors or just thinkers. You know, it makes me smile when we hear the stock market was up or down this day for X reason. The glib headlines, the quick assignment of why the market did what it did. Usually a single factor or story explaining a million different directions and moves and positions.

34:23I've always been amazed by that kind of a statement. I was like, how do they know this? Where's the data? Where's the evidence? Yes, well said. So actually, to your point, it's actually also important not to make up the wrong story. The story has to be the right one. And one of the traps that we can fall into is making ourselves believe a story that we shouldn't believe in. That is one of the traps that we sometimes fall into when we really want to believe something. And as Richard Feynman said, the easiest person to fool is yourself. So you have to really take pains to avoid that at all cost.

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35:37Let's talk just briefly about writing your book, Vasant. I mean, you've lived this subject for more than 40 years. Why was Thinking with Machines the book you wanted to write now? And who did you imagine your reader is? Who's sitting across the table from you as you write? You know, so I was very ambitious in who I wanted to read this book. I felt that this is a pivotal technology at a critical moment. And I wanted to write a book that was accessible to everyone. Students, parents, teachers, scientists, policymakers, grandma, everyone. So I wanted to make this book accessible to everyone. And so I had to write it in a way that was faithful to the concepts, but was understandable, right?

36:28So that was one of my objectives. The other objective I had was that these different constituents would get something out of the book, each one different. So, you know, so this is also a book for my colleagues, right? That is people who know a lot about AI, know everything about AI. Even for them, there's something interesting in there about how to think about AI in a new way, right? So that was my motivation was to write a book with broad-based appeal that was accessible to everyone and yet had sufficient sort of intellectual heft that even my colleagues and expert scientists in the field would say, hey, this is an interesting way.

37:07It's an interesting way to look at AI and where it's going. for policymakers. Again, it was, it provides some sort of a blueprint for how to think about AI, you know, because one of the questions that, you know, I raise in the book is, are our laws sufficient for this era of AI, or do we need to be thinking in terms of new laws, new policies? So short answer, I was very ambitious. I wrote it for everyone and I wanted there to be something in it for everyone. And it really delivers. In my foolish opinion, I would say just, It's an 11-chapter book, and it's about 200 pages long. It has some appendices after.

37:44But, Vasant, what you do is you're not telling AI through technology, but through stories, through your own career, medicine, markets, that we've already talked some about. Of course, great interest to Rule Breaker Investing listeners. Decision-making, we've talked about trust. So I so appreciate that, and I have two reactions back for you. One of them is a joke question that you'll handle very well. But my first reaction is chapter 11, your final chapter on its own is worth the price more than the price of the book. Because at that point, having told the backstory, having shared a lot of thoughts around these things we've discussed in this conversation, for instance, you then get to the what does the future look like?

38:27How does this all play out? How do laws change? Who owns financial assets? Rather than give my money to my children, I could give them to an AI that continues to embody me and my choices. And how do you tax that? And how is that run? And those are just a couple of silly examples, but of interest to people listening to us right now. But Chapter 11 is a phenomenal and stark confrontation of how this technology challenges so many of the received mores that you and I and many of us have grown up with. And there are whole new constructs that need to happen. And we can get there a little bit later. But in the meantime, I just wanted to ask you my joke question, which was, well, you wrote it yourself in the book, Vasant.

39:10You said some people suggested that I have ChatGPT write this book, but I still write better than an AI machine, you wrote, although those days are numbered. By the way, you do write better than an AI machine. Any thoughts back on that? You know, there's a lot in there, David. And I'll just start by saying that I have to thank my podcast producer for telling me, because we were at this conference and he said, Vassad, if you write another book on AI, I'm not going to read it. But if you write your story, I will. He said, because you've got a really interesting story. He knows my story. And he says, you know, you've seen the field.

39:44You know, you had sort of a front row seat. If you write it and make it personal, I'll read it. And so I have him to thank for that. And I should really thank him because everyone who reads it tells me that they really enjoyed the personal stories more than anything else. It's sort of, you know, it's sort of, you know, they were useful in sort of weaving together my story of AI. I'm curious, did writing the book change any of your own views? You know, that's a great question because, you know, in a sense I felt almost like an LLM when I was writing the book, you know. I had this near-death experience on April 15th, 2024, which I describe in the book and I was in complete shock but what I did during that week just after the accident is I sort of thought about like you know what's important to you in life you know you could have been dead you know and one of the things I thought to myself is like you know I will regret not having written this book because I've been thinking about it for five years you know it's been in the works for a long time and it would be a shame if I didn't write it so in that week I sat time and wrote the first two chapters of the book you know so that was like okay i have the first two chapters i know the roadmap i know which way it's going you know but there was um you know it reminds me of a judge i don't know whether it was um sam alito or someone else who once said a supreme court judge who said sometimes the writing cooperates and sometimes it doesn't you know and a lot of things become clear in the process of writing and i'm going to go off on a bit of a tangent here if you don't mind which is that i will never use the ai to write or edit anything and i tell my students the same thing you know develop the writing muscle because writing is not just writing it's a process of gaining clarity right that is the process of writing gives you clarity.

41:41And if you just tell the machine to write it, you'll never experience that sort of clarity that emerges from the process of writing, right? So that's like really important to me is to write myself because that clarifies things in my mind. And it was the same thing for my book. Even though I had a reasonable idea about the roadmap of the book, I did not have chapter 11 planned when I wrote the first two chapters, right? I knew that I would write a chapter on governance, but by the time I had written all of the chapters preceding it, you know, on, you know, the boomer and bat and truth and trust.

42:17And by the time I got to governance, I knew exactly what I wanted to say. But writing the book was a process of achieving clarity as well, even though I knew what I was going to write. How will I know what I think until I write it down? Some of one of those, I can't remember who said that, but that's something I've always felt as a writer myself. I do want to push back slightly on one aspect. And again, we all have our different standards and codes of conduct. For me, having written my original manuscript for Rule Breaker Investing, I asked AI to do what Mr. Carrick, my 11th grade composition teacher, did on my compositions back in high school, which was to strike through with a red line words that didn't add.

43:00And so at least for my own experience, having an editor, much like a human editor, was, I think very helpful for my book, Help Me Save. It turns out one in every eight words, and therefore I could add content back that I wouldn't have had otherwise. And I've said, and you may disagree with this, and if so, I support that. But I've said to a lot, I wish every writer would actually take the time to do that because it would be a lot more efficient for many of us to read through without, turns out, me being so chatty in my original draft with my readers. I also want to say, Vasant, that anytime we consult a thesaurus, We're essentially saying, help me think, third-party aid, improve this text for my reader.

43:43So I personally don't have any problems. In fact, I encourage people to use ChatGPT as a copy editor, much as I also encourage people to use Claude or ChatGPT to challenge our assumptions and our dearly held beliefs. But I don't know if you have any thoughts back on that. I do. I mean, I completely see where you're coming from. But this is a very fuzzy kind of line, right? when you say copy edit this thing for me i guess where i would push back in turn is to say that it's okay to use it for grammar for spelling for specific kinds of things that you're concerned about but the moment you ask it to edit stuff for you i think you're entering murky territory because it can make the slightest edits that could completely change the sense or the spirit of what you're trying to say it might actually be better than what you wanted to say but it's not yours right ah yes it's not yours it came from the ai and so to me the line gets a little bit murky let me make sure i hasten to add that i would never and did never allow the computer the ai to simply do the work i would say suggest edits for this paragraph suggest ways to save or be more economical with this page.

45:02And of course, I use judgment with every single one. And I accepted probably the majority of them because in many cases, I'm like, you know, that is actually a more efficient or elegant turn of phrase. And in so doing, I think I was learning. I was becoming a better writer in some senses because I was seeing. It's not very different from handing my manuscript into, in my case at Harriman House, my very talented editor, Craig, who also gave me additional thoughts. In the end, I made choices on every single word and sentence in the book, but I don't even want to get carried away here with a pedantic discussion around what edits are legit or not.

45:40But I do very much agree that you shouldn't have had Chachamity write this book. I'm glad not. And I know you hold yourself to a very high standard where at the bottom of your newsletters, you say nothing here was written or edited by AI. And I know that you also are a proponent of that for your students. And I understand that. Yeah, no, yeah, fair enough. And like you said, we could say a lot about this, but I think the marginal value would be quite low. Well said. Marginal value, a good concept from economics. All right, let's keep going. Vassan has graciously accepted to play our game by seller hold in just a little while.

46:16But before we go, there are a few more questions and some of maybe our most important or deepest questions, even though we'll probably be economical with our conversation at this point. I've so enjoyed this conversation, Vassan, and I have to have you back just to shoot the breeze. You don't have to write another book, but we need to have another conversation in the year ahead. Done. Let's go with, will AI exercise my brain or make it lazy? In some ways, we just had that conversation, but you wrote at one point in the book, the key question before invoking AI is, will the answer exercise my brain muscle or make it lazy?

46:52So, yeah, I use it every day myself, Fassad. I love it. But I don't want to outsource the very thinking that makes me me. How do you personally distinguish between AI as an amplifier of human intelligence and AI as an anesthetic for it? You know, as I say in my book, that there's this potential for AI to bifurcate humanity, right? That it'll amplify people who already know a lot. And, you know, when I was talking to Claude and OpenAI about, you know, what are good investments, it got really deep. But I was like really scraping the bottom of my own barrel, right? To talk to it. So it was really challenging me, you know, and like I said, it doesn't, you know, it's no pushover.

47:34It comes back at you. And so it was taking me on, right? As someone who has depth in AI and in finance, it wasn't shrinking. It was exercising my brain. On the other hand, I can imagine that if I didn't know anything about finance and I ask it like for top 10 stocks and I don't have the chops to really tangle with it and really get into its thinking and push it back and stuff like that, I could end up just sort of trusting it blindly and making the wrong decision and making the wrong decision. choices. So I think it's doing both of those things. And, you know, the thing I encourage my students to do is to stay on the right side of this bifurcation, right?

48:14That to make sure that they're exercising their brain as opposed to like outsourcing the thinking to it. You know, I may have mentioned sort of on the side that I've graded a whole bunch of term papers this semester and the average quality was better than it was last year, but that's because Claude Cote didn't exist last year, you know? And then some of the people who sort of, you know, written papers that I didn't understand, I sent them a message saying, can you explain it to me in simple English? Some of them responded with AI, which was interesting. And so I asked them, why did you respond with AI?

48:46And they said, well, we trusted response more. And I said, we've got to talk, you know, because that makes me uncomfortable, right? You should always be able to hold your own in a conversation and be able to use the AI to sharpen your skills, you know, so you can do that, you know, hold your own in the conversation. So the answer is, I think it's cuts both ways. And that choice as to whether we are one side or the other is really a choice, but we need to get us our knowledge to a certain level to be able to be on the right side of this divide. You know, a lot of it, I realize you are talking about knowledge, but I know you also, I think you say this in the book, so I assume you agree with this edition of mine, which is that if we're being bifurcated, it may not be purely knowledge.

49:28Maybe it's just curiosity, intellectual curiosity, a desire to know, a desire to explore, a desire to learn. Very much. And so, so much of AI at this stage is about prompting. And I wish that I were Vasant Dar. I wish I knew how best or how most interestingly or generating trust out of it, the best ways to ask AI to help me out, because I know you and your students are doing it better than the rest of us. But a past guest on this show, and I'd love to hear him on your show at some point, Warren Berger, author of the book, A More Beautiful Question, at one point in his book, lionizing the concept of questions, question making, sense making through questions, brainstorming, he would say, is better done as question storming.

50:16So rather than be in a business meeting and all sit around trying to come up with an idea, he says, everybody around the table, try to come up with an even better question, an even more beautiful question. In a lot of ways, that's what we're all being challenged to do to make the best use of AI these days is coming up with a more beautiful question. One of the things I learned about in your book, among many, was I'm going to try to get this acronym right. R-L-H-F. Now, I know you know what this is, although I won't hold you to remembering exactly what the acronym stands for, but it is reinforcement learning human feedback.

50:55And could you briefly explain how ChatGPT uses human beings to decide for the rest of us what would be inappropriate for AIs to express? Yes. So there's two things I want to say, refer to something you were saying earlier, that absolutely it's about asking the right question. And the other thing I'll say is we are limited by the number of hours in the day, you know, to be honest, right? Because if I had like a huge amount of time, I would talk to the AI all day and learn all kinds of things, like I'm going back to it and learning about thermodynamics, right? Things that I studied in engineering school, which I actually went into because I had a conversation with a smell expert who has a, you know, a quantum theory of smell.

51:42And so I had to learn all of that stuff, but it involved sort of going back and learning all those things, right? Which is fascinating. It's so much fun to go back and learn these things properly because I felt like I didn't learn them properly. It was hurried, you know, you know, I was taking six courses and trying to, you know, handle the exam and have a social life and everything, but we're limited by the number of hours in the day, right? This thing is such an amazing oracle at our fingertips. And so I just want to say this because to your point, curiosity is absolutely essential, right? So if you're curious, there's nothing stopping you, you know, because you can learn, you know, virtually everything you were from a human being from the AI.

52:23Isn't that a beautiful thing to reflect on and to say? I just, I love hearing that from you. Thank you. You know, in listening to you talk about only so many hours in the day, Vassan, it just makes me think back to your mentor, Herbert Simon, because a lot of his Nobel Prize winning work was all about, I think it was bounded rationality, which is that for most of us as human beings, we do have limited time, limited resources and attention. And so we satisfy a lot of the time, a word that he coined, which is that we are making the best decision that we can given the very limited time and circumstances we find ourselves in.

53:01And most humans, that's good enough for you and for me. And so I think this is the right connection to make with what you just said, Vasant, because Herbert Simon was the one who really turned the world on to realizing that we're not all perfect, rational human beings doing what the economists before him were saying. Yeah. And David, thank you so much for actually bringing that thread in, because one of the things I hadn't explained was what Simon was actually famous for, which is that we don't have infinite attention, time, resources. So we're bounded, our rationality is bounded. And so we, you know, take the first acceptable alternative and go with it, right?

53:37And that was, you know, it seems so obvious in retrospect, but the entire field of economics is based on complete rationality, right? And so Simon was, you know, came from left field and said, you know, the assumption underlying economics is flawed. And economists didn't like that. They said, well, you're right. Thank you very much. And let's just carry on. And on the other hand, people in AI loved it, right? Because that's what intelligence is really all about, right? It's about learning as efficiently as possible and learning enough to sort of solve the problem, right? And like I said, if I had an infinite number of hours in a day, I would be at the machine all day learning, right?

54:16So we're limited only by time and our imagination and our curiosity. Well said. And my favorite conversations, especially for authors in August, end up being nested conversations where we go down a rabbit hole and then I want to pull us back to where we were and where we were. Vassan, I'm going to quote from your book a little bit just for background, because I didn't know this. So here we go. You wrote, one of the less discussed aspects of LLM applications, such as ChatGPT, is that their responses are shaped heavily by humans using a process called reinforcement learning human feedback, RLHF.

54:51Armies of humans have been employed worldwide to enforce guardrails around the LLM to ensure that it doesn't spew out things that are untrue, racist, sexist, or offensive, which violate our current social norms. The human enforcers channel the behavior of the machine to bring out the desirable parts about what it has learned and suppress the undesirable parts. End quote. That's from your book. Now, of course, there are many directions we can go. We're near the end of our conversation, so we won't go too many directions. But one of the things you contemplate near the end of the book is different cultures with different values will therefore surface truths that other cultures might not might want to hide and or vice versa.

55:38And so in some ways, that human factor is already implicit in the AI. Of course, the AI has scraped us and learned so much about us anyway. We're already there. But I was really interested to hear about what I imagined to be a tribunal or committee of people sitting around saying, well, I don't think chat GBD should say that. Yeah, you know, I mean, this is a great point, and it actually points to the biases that humans have that we actually impose on the machine, right? And we sometimes forget that, you know, that we're saying, no, no, no, that's not acceptable. But maybe that would have been acceptable 50 years ago, or maybe that's acceptable in China, or maybe it's acceptable somewhere else.

56:20It isn't acceptable to us, right? So this is a bias, a cultural bias, that we impose on the AI. And by the way, I don't know if you know this, but DeepSeek is very defensive about, you can't talk to it about Tiananmen Square. In general, DeepSeek doesn't like Taiwanese companies like TSMC. So there's those kinds of biases that are embedded in the Chinese LLMs. So that's something we need to recognize, that all of these LLMs are biased in a way that we find acceptable on average, right? And that's what these humans do all day. You know, they beat the AI over the head and say, no, no, no, thou shalt not say that.

57:04And you will always say this, right? And that's how we get the machine to sort of produce responses that on average, you know, we will find acceptable. Yeah. And in a sense, that's a limitation of the AI as well, a big one. It really is fascinating. And again, just as your book does, especially in the final chapter, we're just as much raising questions at this point in our conversation rather than trying to answer them. But being reminded of the inherent bias, sometimes conscious, sometimes unconscious, that means that one person's or culture's AI could be quite different or have different views of the truth from another person's or another culture's is worth reflecting on.

57:50Let me, before we go to buy, sell, or hold, let me ask the question I've been burning to ask most of the interview. And feel free to hold forth with all the wisdom that you have on this, if, in fact, this question can be even answered. And here it is, Vasant Dar. Let me actually suppose something first. You talked about how AI has been largely dedicated to predictions for the last few decades across many different fronts. So let's make a prediction now. Now, let's suppose that AI actually goes extraordinarily well. I know you're an optimist. At least you invoke the O word near the end of your book.

58:27I am also an optimist. I feel like we are outnumbered by people who live in fear of new technologies, especially such a plate tectonic shift, given artificial intelligence and what it means for the future of humanity and the world. But let's suppose it goes extraordinarily well. So it's not the Terminator, not catastrophe. Ravi, it's success. So here's my question. In that world, Vasant, what are humans for? Humans are for what they've always been for, right? Which is to exist, right? I mean, there is, I don't know, we're sort of getting philosophical here, you know, but this almost gets at like, you know, is there a meaning or a purpose to life, right?

59:09And I just think that there isn't, right that life exists for its own sake right that it hasn't been designed for a purpose you know we create purposes we create objectives for ourselves and we express them right and that's what it means to be human to be original to think to to be to exist to create right that's what it means to be human and i don't think that needs to change it can change right the fear is that that can change. It may make us lazy. It may make us feel incompetent, inadequate, but I don't think that's inevitable, right? I think, so as an optimist, I feel like, you know, if every kid growing up has access to ChatGPT, like, wow, right?

59:58Wouldn't you have been thrilled to have access to something like that, right? Tremendous power, but it also needs to be harnessed because it's so powerful that it can sort of, it's a double-edged sword really is the right metaphor to use. And the trick for humans is to avoid that other edge of the sword, to sort of build on the good one and avoid. I mean, that is the challenge facing us, right? But it doesn't really alter the purpose or the meaning of what it means to be human. I mean, to me, that remains unaltered. A lot of conversations these days are about jobs that will be lost, jobs that are being lost, jobs that we imagine going away altogether, often we're not as good as human beings at imagining what the new jobs will be.

1:00:41But I'm very confident many interesting, in many cases, better jobs than the ones that they're replacing will show up and we'll see what forms those take. But what human beings are uniquely valuable for? That is a question that we will dangle out in front of Rule Breaker Investing listeners in order that we might each come up with better answers, new answers in some cases, to help us understand a future that is so technology-fueled and filled. So it'll be interesting to watch. And Vassant, again, if I haven't already plugged Thinking with Machines, I'll do it one more time. I highly recommend this book to all of my listeners.

1:01:19Vassant, are you ready to play some Buy, Sell, or Hold? I am. Go for it. Thank you. So again, these are not stocks. However, if they were, would you be buying, selling, or holding, and a sentence or two as to why. Let's start. First up, AI companions, people forming genuine emotional relationships with artificial intelligences. This thing that's happening, are you buying, selling, or holding? I am selling. And why? So mental health is one of those areas where I feel that feelings matter. Feelings really matter. When you're talking to someone about something deeply emotional, there's an expectation of a certain kind of connection, right, that they understand and feel you and can respond with that in mind.

1:02:13AI doesn't have feelings. It can simulate feelings, but feeling is one of those things where it's not okay to be able to simulate it, like finance. Finance, it doesn't matter. Finance is not about feelings. It's about making money. It's about understanding markets. It doesn't matter how you feel about it. There's sort of an objective reality there. But feelings are just very, very different, and they're very inherently human. And to think that an AI can feel for you is very risky. And so I'm deeply suspicious about forming emotional bonds with AI with some sort of an expectation that they'd really care for you.

1:02:58They don't. They don't care for you. They only simulate that. And that matters when feelings are involved. A strong sell from the AI pioneer. This might be an all-AI buy, seller hold, because I'm just fascinated from many angles, and your book talks to many of them. I'm not sure you added this one into thinking with machines, though. Vassan, next up, buy, seller hold, an AI seat on the board of directors. So, you know, not merely advising management, Claude, but how about Claude as an actual AI board member? Buy. Strong buy. Why? Well, because being on a board is about understanding a business.

1:03:38It's about absorbing all possible information, analyzing it, and coming up with answers. And that's a real forte of the AI. Very different from feelings, right? This is cold, hard facts, thinking through scenarios, thinking through different kinds of assumptions, right? AI is great for that, for helping people think through that. So in my mind, it sort of extends the rationality of the boardroom in a sense, right? With humans, all the humans in the boardroom, we have 20 people with bounded rationality, right? And along comes an AI with, you know, anything but that. And that can only be additive.

1:04:22Now, I wouldn't want the entire board to consist of AI, but an AI member, absolutely. Strong buy. strong buy next one up ai generated art winning major human prizes buy sell or hold buy so you know it's like music art right different sides of the same coin right there's creativity involved but there's a lot of patterns as well right like i you know when i talk to my musician friends who are professionals right they'll say look it's all it's all about patterns right it's about all about stringing patterns in new kinds of ways uh and so there's an infinite number of combinations but the machine can explore them and actually find ones that resonate.

1:05:00So that's a strong buy. The four-day workweek. I mean, if AI is making us more productive, can we cash out a little bit more leisure rather than simply more output? Buy, sell, or hold the four-day workweek? Absolute buy. Again, and I think COVID set that in motion, right? Because the technology was good enough. We were able to work from home several days a week. That's become sort of a default in many workplaces, right? So people expect you to be more productive overall when you combine coming into work, dealing with humans versus working from home. So I'd say that's a buy. We didn't have time to talk about this next one, even though we spent a good hour talking to each other.

1:05:40There are just too many things. But healthcare. So, Vasant, an AI doctor as your primary care physician, buy, sell, or hold. Buy, strong buy. You talk a lot about this in your book, so I gave it short shrift in this interview, but health is just one of those areas that obviously is so important and so helpful, we think, for AI, right? Absolutely. I mean, health and education to me are strong buys, right? I mean, I might even see an AI professor in the future who can do a better job than I can. Great one. In that case, I'm going to skip my next one, which was AI tutors replacing most classroom lectures.

1:06:16Let's move on. I've got two more here. Digital twins. So, Vasat, you predict that major leaders may eventually have AI versions shadowing them and even conducting virtual strategy sessions with other executives' twins. So, I assume this is still a strong buy digital twins? Absolutely. Strong buy. Again, because you can, you know, bounce things off a version of yourself, right? You can even sort of bias your version and say, okay, be conservative or be, you know, be liberal or whatever, right? You can bias it and say, okay, now talk to me in that mode with the same knowledge base. So tremendous resource.

1:06:53Hassan, do you have a digital twin? I do not, but I'm actually considering creating one for giving exams and tests. Because, you know, I see that as a really strong use case because, you know, as it is, I'm thinking back to going back to blue books and having people write answers because taking exams with AI has become sort of completely meaningless, right? You don't give people take home exams anymore. That's absurd. So, you know, if you want to test how people will, you know, be able to hold their own in the conversation, for example, you need to be able to talk, right? So, you know, when I was in engineering school, we used to have a thing called the Viva, which was you show up and five professors would have a conversation with you about chemical engineering or whatever the subject was.

1:07:39It was terrifying, but tremendously useful as a learning tool. So I'm considering a digital twin that would be able to conduct exams, quizzes, things like that. sounds great to me all right last one here it is the turing test still an interesting benchmark would you say in 2030 or is this an increasingly irrelevant relic buy sell or hold the turing test sell so i i think i think the turing test is largely irrelevant at this point right i mean i would argue that machines have actually passed the turing test you know very often we can't tell the difference. So, you know, I think that ship has already sailed.

1:08:19All right. A bonus one, because I mean, this is rule breaker investing. How can I not ask? Buy, sell, or hold? Human, stop picking. Vasad Dar. I will still rule that as a buy for now. But as I'm about to write in my next newsletter, right, the mother and bought in my mind, right? So to me, that's the holy grail of investing is where the machine has ingested all of our wisdom. It now has access to all the data, the news, right? So to me, the holy grail is that in the long term, the machine should be able to do it, but that's a long ways off. So I think humans have a big role to play for the foreseeable future.

1:08:59Hassan, thank you. What a privilege to spend some time with somebody who's at a front row seat to artificial intelligence for more than four decades and who's still looking forward, still asking questions, still thinking about not just what these machines can do, but what we humans should do with them. Thinking with machines, by the way, just a wonderfully accessible invitation. I love how you expressed why you wrote it and who it was for earlier. I'm grateful that you've helped all of us think a little bit better alongside the machines this week. Thank you, Vasantar and Fulan. David, thank you so much for this conversation.

1:09:34I really enjoyed it. I'm super glad you enjoyed my book, coming from someone like you that matters a lot. And I would love to continue this conversation. It's always delightful talking to you. So thank you so much. Continue it, we shall. Fool on. As always, people on this program may have interest in the stocks they talk about. And The Motley Fool may have formal recommendations for or against. So don't buy or sell stocks based solely on what you hear. Learn more about Rule Breaker Investing at rbi.fool.com. You