Hannah Fry on AI, Algorithms, and Human Nature

What happens when we take numbers seriously—not just at face value, but in terms of their actual impact on our lives? This week, Reid and Aria are joined by UK-based mathematician and media personality Hannah Fry to explore this deceptively simple question. From cancer diagnoses to dating apps, Hannah makes the case that understanding the math behind our decisions—and the "game" we're really playing—is essential to building a better future. They discuss why regret minimization is often a better guide than raw percentages in assessing risks; Hannah’s advice on finding love in a sea of swipe-rights; and how a well-framed question can be more powerful than the right answer. Plus, Inflection’s Pi chimes in with a few Jane-Austen-themed math jokes. For more info on the podcast and transcripts of all the episodes, visit https://www.possible.fm/podcast/ Topics: 3:01 - Hellos and intros 3:15 - Considering hairdressing, instant feedback, and becoming a broadcaster 5:11 - Making math emotionally resonant 7:37 - Math as power and who gets to shape the future 9:10 - Understanding AI through probabilities and spectrums 12:01 - The emotional limits of statistics in medical decision-making 16:22 - Choosing the right “game” to optimize for 19:57 - How to build systems that self-correct 23:19 - Rethinking education and assessments in the AI era 26:42 - Updating dating advice for the AI age 30:03 - Real-life “Black Mirror” 36:11 - Storytelling vs. statistics 41:47 - Probability thinking, AI confidence, and useful heuristics 45:31 - Pi delivers math-themed Jane Austen jokes 47:15 - Rapid-fire questions Select mentions: Google DeepMind: The Podcast The Mathematics of Love TED Talk When We Cease to Understand the World by Benjamín Labatut “Women also Snowboard: Overcoming Bias in Captioning Models” by Kaylee Burns, Lisa Anne Hendricks, Kate Saenko, Trevor Darrell, and Anna Rohrbach Possible is an award-winning podcast that sketches out the brightest version of the future—and what it will take to get there. Most of all, it asks: what if, in the future, everything breaks humanity's way? Tune in for grounded and speculative takes on how technology—and, in particular, AI—is inspiring change and transforming the future. Hosted by Reid Hoffman and Aria Finger, each episode features an interview with an ambitious builder or deep thinker on a topic, from art to geopolitics and from healthcare to education. These conversations also showcase another kind of guest: AI. Each episode seeks to enhance and advance our discussion about what humanity could possibly get right if we leverage technology—and our collective effort—effectively.

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

• 0:00Aria Finger?

  Before we dive into this conversation, just a warning that this episode contains mentions of suicide. So please do take care.

• 0:09Speaker 01

  When it comes to questions of risk, human brains do this black and white thinking. I don't think when you're diagnosed with cancer, it's the time to have a statistics lesson. And I also don't think that we're getting informed consent from people who just shout numbers at them. But what I think that you could do is you could have somebody who turns it around the other way, right? So who sits down with you and says to you, okay, what is important to you in your life? What are the things that you value? And what percentage chance of it working would you be willing to tolerate? It's noticing how you feel and interpreting it mathematically, rather than trying to put the numbers on how you feel.

• 0:57Reid Hoffman?

  Hi, I'm Reid Hoffman.

• 0:59Aria Finger?

  And I'm Ari Fenger.

• 1:00Reid Hoffman?

  We want to know how, together, we can use technology like AI to help us shape the best possible future.

• 1:08Aria Finger?

  With support from Stripe, we ask technologists, ambitious builders, and deep thinkers to help us sketch out the brightest version of the future. And we learn what it'll take to get there.

• 1:20Reid Hoffman?

  This is possible.

• 1:25Reid Hoffman?

  Just over a decade ago, a charismatic mathematician took the stage at TEDx Binghamton University and delivered a bold thesis. Math can help you find the love of your life.

• 1:37Aria Finger?

  Her talk, fit with wisecracks and diagrams, wasn't just a platform for relationship advice. It was a portrait of how math is deployed in our everyday lives, of how numbers, theories, data, and algorithms can allow us to better understand ourselves and each other and build toward the best possible future.

• 1:58Reid Hoffman?

  Millions of views and hundreds of lectures and broadcasts later, Hannah Frye is a leader in a global movement to make math cool. She was a professor of the mathematics of cities at University College London before joining the mathematics faculty at Cambridge University. Hannah is also a bestselling author and host of many shows, including BBC's The Secret Genius of Modern Life and Uncharted, along with the Bloomberg original, The Future with Hannah Frye, and the podcast Deep Mind.

• 2:29Aria Finger?

  Put simply, Hannah finds and shares the many ways that numbers, algorithms, and data are at play in daily life, from dating apps to traffic jams.

• 2:40Reid Hoffman?

  Of course, math also forms the foundation of AI, providing the tools that enable machines to operate intelligently. Today, Hannah joins us to talk about how math moves us and shapes us, and how we can use technology like AI to elevate humanity. Here's our conversation with Hannah Fry.

• 3:04Reid Hoffman?

  Hannah, it is excellent to be here in LinkedIn London with you. Thank you for joining us.

• 3:09Speaker 01

  Thank you for having me. A delight to be here.

• 3:11Reid Hoffman?

  So apparently you've said that if you weren't going to be a mathematician, you'd be a hairdresser. One, why? And two, if you were a hairdresser, how would math play into hairdressing?

• 3:23Speaker 01

  OK, I remember saying this, and it is absolutely true as well. When I was 16, it was what I wanted to do. And my mom was like, OK, look, once you finish your GCSEs, just do your A-levels, and then we'll see where we are. And then I finished my A-levels, and she was like, OK, just go and do a quick degree in maths and theoretical physics. And it sort of went on and on and on, and then eventually the hairdressing has fallen by the wayside. But it was like a genuine ambition of mine, and I can still tap into that feeling of what I wanted, because I think that there is something, first of all, quite interesting about constructing a three-dimensional shape. You're on a sphere. There's sort of some interesting geometrical properties there. But also, I think what it is, is it's about doing something and then immediately seeing the value in it. And I get the same kind of buzz, I suppose,

• 4:06Speaker 01

  from doing Instagram videos or YouTube videos. You know, you do something, and then you immediately see the effects of it. It's not like, in the academic world, I mean, things are slow burn, right? Slow burn. So yeah, I think that was what it was about.

• 4:20Aria Finger?

  I was just gonna say, it's like when you go to the gym and you have a personal trainer and you want them to be fit, you have great hair.

• 4:26Speaker 01

  Thank you so much.

• 4:27Aria Finger?

  So, you know what I mean? It's like not a bad backup profession, is all I'm saying.

• 4:31Speaker 01

  Thank you so much, yes.

• 4:32Aria Finger?

  But you did end up, you call yourself an accidental broadcaster, which I love.

• 4:37Speaker 01

  Yeah.

• 4:37Aria Finger?

  And so are there things that you can't wait to focus on? Like, what's percolating in your head right now?

• 4:42Speaker 01

  I've been trying to get some stuff about artificial intelligence done properly out there for so long. I mean, it's been really difficult to persuade people that this is something that's worth time and attention, that can be told in an entertaining way. And I think that this switch has just happened in the last 18 months or so, where people are like, okay, no, we will really, like, address this. So I'm really looking forward to doing some of that. I also, I don't know, I'm in this quite philosophical mood at the moment, where I'm thinking a lot about what knowledge means and the edges of knowledge and how we can deal with the fact that there are things that we will never know.

• 5:19Reid Hoffman?

  You know, I think that most people don't see how math is so relevant to their lives. One of the things I think is really excellent about your work is to say, how do I make it tangible, practical? When someone starts from a, like, I don't understand math, or I'm a little alienated, what are the first things that you try to light up their world and their universe? Because, like, for example, on the AI point that you were making, part of what I've been doing with Super Agency is to try to move people from AI fearful, skeptical, to AI curious. And I see a similar arc, which is, you're trying to make people math curious.

• 5:54Speaker 01

  Yeah.

• 5:55Reid Hoffman?

  Right? And so what are some of the things that you do to get people to suddenly start becoming math curious?

• 6:02Speaker 01

  Okay, so I think the very first step is that it's not your job to change people's mind about how they feel about the subject, you know? I think a lot of people are kind of really traumatized, genuinely traumatized by the math that they encounter in schools. And I think it really divides people. Some people, like us, I imagine, you know, being really drawn to the subject, and I think a lot of people really turned away. And you're never gonna switch that. So I think it's about acknowledging where people are and using that as your baseline. But then I think it's about really doing it by stealth. That's maybe a...

• 6:35Aria Finger?

  It's the vitamin in the Twinkie.

• 6:37Speaker 01

  It's the vit... Exactly, exactly. It's the vitamin in the Twinkie, exactly right.

• 6:40Reid Hoffman?

  That's if you like Twinkies.

• 6:43Aria Finger?

  Fair.

• 6:43Reid Hoffman?

  Maybe vitamin on a chocolate chip cookie.

• 6:45Aria Finger?

  Done.

• 6:46Speaker 01

  Just vitamins anywhere, you know? Just like, force them in. Because I think that when you have had the luxury of really seeing the world through a mathematical lens, I think that you fully understand that there is almost everything can be viewed through that perspective. I think that it has incredible insights that it can offer you on literally anything. The explosion in productivity and everything that the world has seen in the last 15 years has been based on that, right? It's like the era of big data was the kind of mathification of industry. When you understand that, then I think that you can start elsewhere, right? You can pick basically any topic you like and then show the insights. I often make programs where I never even say the word

• 7:31Speaker 01

  maths, like I never even mention it. But it's just about providing these curious, counterintuitive, surprising ways to turn something that people feel like they already know, turn it on its head and show it to them in a completely different way.

• 7:45Aria Finger?

  I just think math is such a way to explain the world. And to your point, I think it's very different by country. At least in the US, people are math people and not math people. And that's so ingrained in our head. There's no growth mindset. It's just, well, I'm bad at math, I can't understand it. And you actually had a colleague say to you, people are scared of mathematicians, let's keep it that way. Like, why do you think people feel that way? And like, how can we not leave math to the pros?

• 8:09Speaker 01

  I mean, I think that you can weaponize it, actually. I think that when you have knowledge, I think it gives you power, basically. I mean, in short, if you are able to create mathematical models that can impact the way that things are run, and you understand them, actually, it's very easy to just like draw a wall around you and be like, sorry, you're not, you know, you can't come in. But the thing is, at the same time, you know, we are quite literally designing our collective future, particularly now. Everybody deserves to have a say in that, you know? And I don't think that people should be excluded from it. I'm not saying for a second that everyone's going to be mathematicians. Of course they're not. I would like to just move the dial a little bit on people understanding that

• 8:51Speaker 01

  there is this connection between a subject that they think is like numbers and textbooks and whatever, and actually this really living, breathing language that is allowing us to effect change out in the real world. I think I'd like people to understand that this is also maths, right? This is also maths. And be invited in on the conversation. I know you've spoken a lot about ethics and doing things safely. I think those kind of conversations, yeah, you should be drawing people into those.

• 9:18Reid Hoffman?

  In the AI revolution, which I prefer to as the cognitive industrial revolution, what are the ways that people should think about engaging with AI that's mathematically informed?

• 9:30Speaker 01

  So I think a lot of it is about critical thought. Historically, computers have been kind of deterministic machines, right? It's like you put the same sum into a calculator twice, you get the same answer out. And I think that actually we are moving away from that and more towards this much more sort of stochastic, you know, probabilistic space. And I think that people haven't yet adjusted their mindset to what that actually means. You see this with, you know, hallucinations from large language models, of course. But I think that you also really see it in the ways that people are applying mathematical models or, you know, artificial intelligence models to determine particular outcomes.

• 10:13Speaker 01

  Right? So for example, let's say that I somehow or other came up with an amazing new algorithm that could find your perfect partner in the entire world, right? But it did it with an 85% accuracy. I think that people are not very good at understanding what that means and what the wider implications are of that. And there are countless examples of that nature. I mean, more and more and more and more where these things fall short of perfection and will always fall short of perfection, which is fine. But that gap between sort of perfect and what you end up with can be sort of all kinds of potential problems that arise.

• 10:49Reid Hoffman?

  You're highlighting a particular thing. Ari has heard this from me before. If I had a mathematical wish for humanity, it would be understanding that everything is in probabilities, that it's almost never 0% and almost never 100%. And how you're configuring your navigation path depends on the intersection's probabilities. And yet people tend to collapse it into 100 or 0, which frequently, like if you have an 85%, you skate through it 85% of the time, fine. But then you're ambushed by the 15 when you shouldn't be.

• 11:21Speaker 01

  I mean, I tend to think of almost everything as sort of spectrum. So I completely agree with you about between 0 and 100. But I also think about when you're having Arguments with people, it's like right and wrong also exists along this spectrum. And I think the big kind of like societal debates that we've had where people feel so completely polarized. There's a mathematical trick where you deliberately sort of push something to an extreme. So you think of, okay, what would the case be if this particular variable went to infinity? Or what would it be if this was zero? And you kind of use that to give you information. And I think that the Jesuits have a similar philosophy, right? So when there's an argument about something, you sort of imagine an extreme version of the same problem to help you understand it a little bit better. That thing of like not seeing the world in black and white. It's not one hundred percent or zero. It's not yes or no. It's not true or false.

• 12:05Speaker 01

  Everything exists along a spectrum. I think that's a really helpful way to see the world.

• 12:08Aria Finger?

  I mean, that to me, besides like weeping alongside you in your documentary about cancer, that actually was the most illuminating moment. I mean, I was talking about it with Reed this morning. So often with health and medicine, I mean, especially as women, it's like, well, if you do that, you're 10 times more likely to get cancer. Well, the chance before was point oh oh one and now it's point, like your mind can't comprehend. And especially for people who don't sort of have a facility with math. And so, you know, in that documentary, you were talking about, you know, if a hundred women were diagnosed and 80 of them would have been okay without going through chemotherapy and what are the odds? Like, what was the response that you got to that? How do you think about that?

• 12:51Aria Finger?

  To me, especially with something so important as your life, the math becomes very important, but then also not important because you say, of course, I'm going to do this. Like, how did you think about that?

• 13:02Speaker 01

  Yeah, so there was one woman in the documentary in particular, this woman, Anne. I mean, that's a conversation that will stay with me forever, right? So she's, people who haven't seen it, she was in her late sixties and she'd just been diagnosed with breast cancer. And she'd had the lump removed, but the doctor was working out what future treatments she should be given. And they said, if we don't touch you again, you have an 84% chance of living another 10 years. But if we give you everything we've got, so chemotherapy, radiotherapy, you know, hormone therapy, everything, we can increase it to 88. I thought that was a really difficult decision, right? That like, do you go through it? But I spoke to her outside. And I was like, what are you gonna do? And she was like, I have to have the chemotherapy because otherwise I'll die.

• 13:45Speaker 01

  I was absolutely astonished that the numbers were not getting through, right? The numbers were not communicating the message. And then I really thought about it, you know, I went back through to the doctor and was like, she did not understand. Like you, you go to the doctor, they tell you the treatment, you take the treatment, the thing goes away, right? It's like exactly as you said, you know, 100%, 100%, 100% 100%. And, and the doctor was like, I think if she did understand, she probably wouldn't go through the treatment. And if that happens over and over and over again, more people will die, which is also completely true. What that started in me and has continued to the book I'm writing at the moment is about doubt and uncertainty. Is that I'm not sure I even know what those numbers mean. I'm not sure I understand the difference between 88% and 84%.

• 14:29Speaker 01

  Like, is the human brain really capable of that? I don't think it is. And so then it's like, well, now you've got these numbers that are applicable and very useful at the population level. And are kind of meaningless when it comes down to you as an individual. And so then, then it's like, well, what does probability actually mean? It really comes down to like how you feel about risk. You know, ultimately, I think you're quantifying how you feel about risk. And that makes sense at the population level because, you know, we can do it that way. But when it comes down to you as an individual, I think things get very, very hazy.

• 15:04Reid Hoffman?

  Well, there's a couple of things there. One, one of the things that happens frequently with math and most people's psychology is that they get false precision. It's like, really? 84? 88? Right? Like, how do you derive that? That's, you know, your area of expertise. The next thing is, what's the actual fitness function? What's the actual game you're doing? Cause actually, in fact, in this case, I think she think the answer is fairly obvious. If 84 and 88 are correct, because it's probability of maximum number of quality of life days. Right? And chemotherapy is brutal. So you kind of go, okay, actually, in fact, the higher probability of quality of life days is not doing it. And so frequently, I think one of the things that people mistake is what's the game?

• 15:49Reid Hoffman?

  It'd be interesting if figuring out which game, I mean, you mentioned girdle earlier and, you know, kind of incompleteness theorem. But, but like, one of the most important things is figuring out what game is before you even kind of get to, get to the thing is. And that's another part of this. And then, you know, the last part of it is to kind of think about, okay, exactly as you're mentioning, what, how does this apply to me? Am I a person who is willing to take some risk? And by the way, most people, this is part of the thing, reason I think they get to zero and a hundred, because most people want to imagine they're not taking risk. They don't realize that when they get in a taxi cab and go somewhere, there's a risk. You walk across the street, there is a risk. And they go, well, it's just zero, zero, zero, zero, zero, because I otherwise brain goes.

• 16:29Speaker 01

  I'm immortal.

• 16:29Reid Hoffman?

  Yes. And so part of the, the thing that I think is excellent is to get a little bit more fluid in the application of probabilities. One of the reasons I love the mission you're on. So have you thought about the heuristics of, like, if I were going to say something to one of my godchildren about, hey, think about math this way in your life.

• 16:52Speaker 01

  Yeah.

• 16:52Reid Hoffman?

  What would be like a heuristic, a principle, a, okay, I need to remember this as I apply to this.

• 16:58Speaker 01

  Yeah. Okay. So actually, can I say something about the game bit first? Cause I, I thought that was such an interesting point, because I totally agree with you. Something I think about a lot. You have to decide what you're actually optimizing for. And I think so often people don't. And one of the things I've been thinking about a lot recently is about prisons, right? And if you kind of look at the data, right? You know, why would you want to send somebody to prison? When somebody commits a crime, you need some way to rehabilitate them, right? You also need to kind of actually take them out of the system. You need some deterrent effect and you need some sort of sense of retribution for the crime. But when you actually look at the data, like on every single one of those, apart from maybe a feeling of retribution, prison is like the worst possible answer. It's like, if you want to reduce crime, is that the game that you're playing?

• 17:42Speaker 01

  I do think that actually people kind of go through a system without ever stopping to think about what the question is, what the game is exactly as you describe. And then in terms of how do you think about maths? How do you, how do you kind of translate it? So going back to that example about cancer, one of the things that I found to really noticeable is when you're diagnosed with cancer, you have somebody who will take you into a room away from the doctor, and they will sit with you as long as you want, and they will go through the procedure. They will talk, answer every question that you have. I mean, they're essentially a translator between you and the medical profession, right? And I do sort of wonder that when it comes to questions of risk, because human brains do this black and white thinking.

• 18:24Speaker 01

  I don't think when you're diagnosed with cancer, it's the time to have a statistics lesson. Right? I don't think if it didn't work before, it's not going to work then. And I also don't think that we're getting informed consent from people who just shout numbers at them. But what I think that you could do is you could have somebody who turns it around the other way. Right? So who sits down with you and says to you, okay, what is important to you in your life? What are the things that you value? And how can we design a treatment system that does that as well as possible for you? I spoke once to an intensive care nurse. Because of course, when you're in intensive care, there are all sorts of situations where these probabilities arise. Right? Like you can, you know, resuscitate somebody, but the chance of this repercussion is really high or whatever it might be, this procedure has these consequences.

• 19:08Speaker 01

  And she said that what she started doing with families, rather than saying this has this percent, she instead says to them, okay, this is what we're thinking. What percentage chance of it working would you be willing to tolerate? So it's the other way around, right? It's not you're taking a number and trying to attach a feeling to it. It's the opposite. You're taking a feeling and trying to attach a number to it. And that, I think, is a much, much better way to try and do things. So in terms of intuitively thinking about mathematics, it's switching it around. It's like noticing how you feel and interpreting it mathematically, rather than trying to put the numbers on how you feel. So actually with my kids, for instance, you know, if we'll walk into town, I'll ask them to come up with a route that minimizes the number of crossings of roads that we do.

• 19:54Speaker 01

  Like seeing the world in a way where you are kind of systematizing and critically thinking about things and noticing that you're doing it, rather than necessarily just trying to put numbers on everything.

• 20:05Aria Finger?

  Your point about pre-deciding, especially before the emotion takes over, I think is so critical. Most parents go through that during childbirth. You're faced with all these decisions. Should you get this test? Should you do this? And, you know, my husband and I would say like, well, will we make a different decision based on the information? If we get an information of 60% chance of this or 20% of it, will it change our mind? Well, then why do we need to know? One of the things you've talked a lot about is that perhaps because, again, of this sort of innumeracy or people's non-facility with math, that they tend to trust the outputs of math blindly, or perhaps of LLMs or computers. And so I'm obsessed with criminal justice reform and the prison system. One of the things I'm excited about with AI is that, you know, it's hard to wave a wand

• 20:48Aria Finger?

  and fix racism, but maybe we could wave a wand and make an LLM not racist. You know, it's hard to sort of fix system-wide things, but if we can, you know, sort of change a code, if we could reinforce, if we could do all these things. And you've talked about how, you know, with AI, there could be increased bias, but there's also ways to reduce bias with AI. So how do you think about that?

• 21:09Speaker 01

  Yeah, absolutely. There's a really interesting paper that came out a couple of years ago, and it was called Women Also Snowboard. It was looking at image recognition, where you can't tell the gender of people. But what was really interesting was that it demonstrated how, you know, these are not like stable equilibrium, right? So if you have a bias in the initial dataset, which is where the original bias came from in the labeling, where people were seeing pictures of snowboarders and assuming they were men rather than women, but it can be exacerbated once it goes through the algorithms. That's something that, exactly as you say, you have to be extremely cautious about and make sure you're putting in the correct safety procedures to minimize and mitigate against that. For me, the crucial point about this is sort of the one that you made, right?

• 21:49Speaker 01

  That you cannot wave a wand and fix sort of systemic issues or societal problems. And so then I think that the question changes. This is something that it doesn't have a finish line, right? It's not like, oh, well done, you did fairness, right? Like, oh, unbiased, congratulations, right? I was writing a book a few years ago, and I once spent like a week trying to research and look for any system in the world that has ever Ever been perfectly fair? Doesn't exist, right? There's nothing. You know, forget about algorithms completely for a second. And so then I think if you say this is not something that has a finish line. And instead, you accept that there will always be bias in your system.

• 22:31Speaker 01

  And therefore, commit to continually hunting for it and repairing it. I think that's the way that you have to approach this.

• 22:38Reid Hoffman?

  Your comment just made me think about, there are ways to make perfectly fair systems, but they will be very unjust systems.

• 22:46Speaker 01

  Yeah.

• 22:46Reid Hoffman?

  Because you could go zero percent all the time, a hundred percent all the time, or fifty fifty random, and it'll be fair, it'll apply to everybody.

• 22:53Speaker 01

  Yeah, you're right.

• 22:53Reid Hoffman?

  Oh, my God, would it be an unjust system.

• 22:55Speaker 01

  You're absolutely right.

• 22:57Reid Hoffman?

  So how has this AI revolution made you think about education? Because one of the things you do at Cambridge, obviously, is trying to make math education widespread, you know, impactful, et cetera. But let's generalize a little bit to education generally. And obviously, there's been a lot of turmoil

• 23:17Speaker 01

  Yeah.

• 23:17Reid Hoffman?

  within the academy when it comes to chat GPT and everything else. What are your thoughts on it? And how should universities be thinking about AI generally?

• 23:27Speaker 01

  Yeah, I mean, obviously, it's been a massive disruption. So thanks, tech guys.

• 23:32Reid Hoffman?

  Yes, we try.

• 23:35Speaker 01

  But I am really optimistic and feel really optimistic about it. And I think part of my optimism actually comes back to the point that you made about the game earlier. Because the thing is, the real disruption has happened in the way that we assess student's performance. But if you kind of rewind what the question is about the assessment in the first place, the real question that we want to answer is, how do we know whether our students are getting a good education? Whether they're understanding the concepts and are ready for the next step that they go on to? And you can't ever really answer that question. You know, you have to use a metric in order to get there. And the metric, you know, always falls short of precisely the thing. You know, you can't, you can't use numbers to like perfectly capture these things. I'm fine with the fact that like, you know, written essays have to be considered in a different way.

• 24:20Speaker 01

  I'm fine with the fact that we have to move more towards oral examinations, change the types of questions that we're Ask, I'm genuinely fine with that. I'm okay with it. But where I'm really excited about it is this. We've known for a really long time that different people learn in different ways. But it's really hard to do that when you're one person standing at the front of a room full of people. And I think just even from my own experience, using AI for research is just like on steroids, right? Like, it's incredible how much faster you can accumulate and assimilate and like critically think about knowledge. I think it's giving them extra tools, giving them extra learning, right? Like, I think they're learning faster and better than they were before. But I also think that the AI tutors that I'm looking forward to,

• 25:04Speaker 01

  which will be adapted for individual people's learning styles and can really clearly identify gaps in their knowledge and then, you know, appropriately construct questions to reinforce those. I really think there's a lot of really good stuff that's going to be coming.

• 25:17Speaker 04

  I agree.

• 25:18Aria Finger?

  I was thinking about the switch from written to oral examinations. And I used to teach and my students, no offense, were just horrific writers. And so even if they understood the concepts, like I would always ding them for their writing. But some of them were amazing orators. All of these things are coming in and we're never going to get it perfect. And maybe AI can help us actually get a more holistic picture of the person we're thinking about.

• 25:43Speaker 01

  One thing, just very quickly on that, you know, historically, every culture, every society has always really valued wisdom, right? And I sort of think of wisdom as an ability to take in a wide range of variables and come up with a very particular response to whatever that might be. And I think that historically, actually, we've sort of been at the exact opposite end of the spectrum, which is like one solution for everybody. And I think we're moving more towards AI, which is like much more individual.

• 26:08Aria Finger?

  Absolutely.

• 26:18Aria Finger?

  I rewatched your TED Talk last night, which for those of you who haven't seen it, it was all about using math to find love. And so I'd ask you, you know, in the age of AI, I mean, people are having AI friends, AI girlfriends. They're using AI on dating apps. To, you know, give them the best poem to send to someone, whatever it might be. How would you update your TED Talk in the age of AI?

• 26:41Speaker 01

  Oh, my gosh, such a big question. So I did that TED Talk over a decade ago. I should also tell you that when I did it, I was just engaged or like just about to be married. I was very excited about the world and I gave all of these bits of advice about how you can use math to optimize your own dating life and now divorced everybody. Okay. So basically don't listen to anything I say.

• 27:01Reid Hoffman?

  No, understand its probabilities.

• 27:03Speaker 01

  You're absolutely right. But in terms of updating it for the age of AI, I think that something that's really interesting has happened actually with dating apps. But I think it does again, come back to what is the game, right? Because the thing is, the hard bit about dating is like finding somebody who you can integrate your life with in an effective way, where you have these shared goals, where you support each other, you know, emotionally in terms of your career, all of that stuff. Finding somebody where you can do that with and the process of doing it, right? Communication ultimately is like the thing that's difficult about relationships. The thing that is not difficult about relationships is which of these 2D images of people do you think are better than others, right? That is not what it is, yeah?

• 27:45Speaker 01

  And yet somehow or other, like that has become what dating is about. And of course, it's because it's the bit where you can find profit. This is one of those situations where the technology has started changing human behavior. You know, just the way that we have relationships has dramatically changed because of the impact of these apps. So in terms of what I would do with AI, I don't know. Maybe it would be around what the question would be. Probably be something about improving communication between individuals.

• 28:14Aria Finger?

  I mean, my favorite thing about the TED Talk was about increasing your odds. Sort of to your point, understanding the game. AI can just help people understand that communication, relationship. You can talk to your AI to like, figure out what you're supposed to say. You can get advice. Like there are positive things that it can help you to do. But to your point, maybe looking at two static images and deciding which is most attractive is not going to get you to your future husband or wife.

• 28:41Speaker 01

  Yeah, I mean, that that whole point about like, you think that you're appealing to the masses. You're not, you're not appealing to the masses. You should pick whatever makes you unique and just go with that. Yeah.

• 28:50Reid Hoffman?

  So before we get to your new BBC series, which I have several questions about. I'm curious if you have a heuristic about how people can learn a good mapping between an emotional state and like a number or percentage. Because I agree with you, because it also is like, what's your aim? What's the game plays into the emotional state? But it's like, well, what percentage would be acceptable to you as a way of doing it? But of course, that requires practice and a reasonable mapping function. Have you had any insights about how people can learn that mapping function better?

• 29:24Speaker 01

  I think it practices the key. You know, the super forecaster stuff where you look at different future events and then you've put down a probability and then you check back and recalibrate your percentages that you're giving it based on what actually happens. And so I think it's that. I think it's you have to continually reassess it. The other thing, actually, the precise situation where you're like, what's the number I would be happy with? And what's the number that it is? I don't think those come up that often. I think the one that I use more often is regret minimization. So where I imagine being in the future and looking back and then choose the path which I would regret the least. That's the one I use almost all the time.

• 30:02Reid Hoffman?

  No, no. And again, depending on the game, a very useful tool. So let me move to your new BBC series. Start with a confession, which is I find it very difficult to watch Black Mirror.

• 30:14Speaker 01

  Yeah.

• 30:14Reid Hoffman?

  Because when I watch Black Mirror, I'm like, oh, I know how to fix that. Like, I know how to not make that be the dystopia. Like, it's not inevitable. Sure, if you're dumb and build it this way and your society somehow orients around making it dystopic, it can be terrible. So it was described as like real life Black Mirror.

• 30:36Speaker 01

  Yeah.

• 30:37Reid Hoffman?

  So I had a bit of an aversion response, which surprised me because I see you as a optimist about how we create the future. So what is this future coming and what is this series?

• 30:48Speaker 01

  I agree with you about there's dumb ways to design things. But I think the slight problem is there are dumb people designing stuff, right? And I think that there are some really astonishing stories of things that have already happened and are continuing to happen. You know, I saw, I went to go meet this company in California where, so now it's, new cars have to be built with an internal facing camera, right? And part of that is technology to check when the driver is falling asleep at the wheel in order to alert them, right? Which I think is really positive thing will reduce deaths on the roads. But what you can also do, if you are a dumb designer,

• 31:30Speaker 01

  is you can use an AI to determine the emotional state of the driver. Now, I probably should have put that in air quotes because the actual science behind it is just junk. It's, it's based on the idea that you're smile when you're happy and you frown when you're sad, right? Which is like, it's just not true at all. And yet, because there's nothing stopping people selling this stuff, there are companies who will take those feeds and then, you know, send it out to insurers that you're a grumpy driver or whatever it might be. And their sort of thinking is that it will change your insurance policy, but maybe also if there's like, you know, a particular emotional state that you're in, then your car wouldn't work. And so there are these stories where people have done things that don't make sense,

• 32:14Speaker 01

  that need correction. Part of that correction is also sort of shining a bit of a light on them, you know? I think it's about having those conversations in the public space. But I also agree with you that I am ultimately an optimist.

• 32:27Reid Hoffman?

  A hundred percent. And by the way, I agree with everything you've said and outside commentary and revelation is, is an important part of this. But I think like, one of the things that I'm curious about is going to do in the story, because if you go, well, it's a probability curve. And I'll give you an example of something that I, you know, encountered last year, which is there's a lawsuit against Character AI for a child, tragedy obviously, who was having interaction with a chatbot and committed suicide. And so there's a lawsuit. Now, as far as I can tell, you know, from appraisal of the chat manuscript, the chatbot wasn't doing any of the obvious things that would trigger a lawsuit, which is you should consider committing suicide or that kind of thing. It had some irregularities in the conversation, but nothing that was like persuasive, manipulative, et cetera.

• 33:11Reid Hoffman?

  But the problem that I saw, Lou, and this is part of how we as human beings take narration and make bad judgments because of it, is if you asked me to guess right now, would chatbots, as they've existed and been deployed, increase or decrease suicides across the entire population? My guess is it'd be decreased.

• 33:31Speaker 01

  Decrease, yeah.

• 33:31Reid Hoffman?

  Right? Because there's a sympathetic ear to talk to you at 2:00 in the morning. I know the vast majority of these chatbots are trained in a way of going, oh, are you unhappy? Well, let's talk to you, but let's try to help you get back to a thing. And so when you say, okay, we have this narrative where this bad thing happened, you also have to be like, where does it fit within the probability curve? And given you and the intelligence around math, I presume that's also part of this evaluation?

• 33:57Speaker 01

  Yeah.

• 33:57Reid Hoffman?

  Yes.

• 33:57Speaker 01

  Because it's nuanced, right?

• 33:58Reid Hoffman?

  Yes.

• 33:58Speaker 01

  I totally agree. But then I also think, in that example, I would probably take the conversation to a higher level, right? Which is about the ways in which we anthropomorphize these chatbots, right? And consider them to be human, where people are forming kind of genuine emotional connections and genuine bonds almost with these chatbots. And I think that we should be having public conversations about how much we want our chatbots, or whatever it might be, to sort of act as though they're human, bearing in mind that humans have this real habit of, exactly as you say, putting a story on something. But this reminds me, I think, of what was happening, you know, in the earlier days of driverless cars, when, yes, driverless cars were reducing the total number of deaths on the roads, but equally, there were deaths due to driverless cars going wrong.

• 34:41Speaker 01

  For me, the top level question with driving, right, is like, okay, well, humans are going to be in cars, right? So what is it that humans are not very good at? Well, we're not very good at paying attention, like, we're not very good at acting well under pressure, and we're not very good at being aware of our surroundings, right? Those are the things.

• 34:57Reid Hoffman?

  And self-assessment.

• 34:58Speaker 01

  And self-assessment, absolutely right. And so I think that when the design of those systems in those earlier days was, okay, well, we'll just get the machine to drive the car and then the human will step in. And it's like, well, hang on a second, what, humans aren't very good at being aware of this, right? They're not very good at performing under pressure, and then they're not very good at paying attention. So you're expecting the human to kind of step in at the moment when their attention is elsewhere, right? It just doesn't work. And then I think that there was like a reframing of it, which is like, okay, well, hang on a second then. If we if we start with what the human can't do, pay attention, you know, whatever, keep the human in the driving seat and then have the machine fill in the gaps of the stuff that the human can't do. So the car is the

• 35:40Speaker 01

  collision avoidance systems that you've had. Well, that's just kind of a much better pairing, right, of the two together. And I think that, you know, having had that now for a number of years, the technology has developed where you can go back to the other system. And I sort of wonder what the equivalent is for chatbots. I have an answer for this, by the way. But given that humans have this habit of like imposing personalities and characters on things that are inanimate objects, how do we create these systems in order to mitigate against the worst risks that can happen when they do?

• 36:11Aria Finger?

  No, I think that's really important. I also think there's all these second order effects. Like I was reading about the decision not to require child car seats on planes. Because actually, if you have a six month old, if they are in a car seat on a plane, they are safer. Mostly, nothing will happen, but it's, you know, twice as likely not to have a neck injury, whatever. But if they required car seats on planes, parents would just drive. And you know what's dangerous? Driving. So it's like, oh, actually, we can't just look narrowly at this math statistic that is happening on planes. We have to say, oh, bigger picture, let's look at parental travel and how do we keep our children safe? But I think there's a natural tension, sort of what Reid was saying, between storytelling and statistics, or storytelling and facts. Like, you see like every day on Twitter,

• 36:56Aria Finger?

  someone saying like, oh, silly me, I thought facts and statistics would change someone's mind. But we all know it doesn't. And so in your job, in your professorship, as sort of trying to explicate the world through math, trying to make it more intelligible, how do you see that disconnect between stories and statistics? Because people's brains, you know, parse them so differently.

• 37:16Speaker 01

  Oh my gosh, this is such a good question and it's so hard. So I did this programme during Covid. Essentially, the idea was that we would take seven anti-vaxxers. And for a week I would be with them and we would have all sorts of conversations. And then over the course of the week, we would see if anybody changed their minds. Now, the thing about this programme, I didn't like the cut that went out. I thought there were some problems with it. And I think that the issue was that, exactly as you say, right? We know that statistics doesn't change people's minds. You cannot just throw statistics, numbers at people and then be like, "Oh, of course, like, that's obviously I was right. It doesn't work." It's called the deficit model of public communication, which is like, if only people knew what we knew, they would see the world in the way that we do.

• 37:59Speaker 01

  And what I wanted to do with that programme was actually really sit down and understand where these people were coming from. And over the course of the week, I just found it so interesting and it changed my mind on so many things. For instance, there was one guy who was a nurse. I really got on very well with him. I think he'd had some issues when he was younger, where he had been put on medication against his will. And so he was like, "Look, I just believe in informed consent, right? Everybody does. And if somebody comes into the hospital and they have, you know, gangrene in their leg or whatever it might be, and they refuse treatment, we have to accept that. And this is a vaccine that doesn't have like a societal responsibility, because it doesn't, you know, change the probability of transition, certainly not after a couple of weeks. And so it's my decision to make and this is the stand that I'm making."

• 38:44Speaker 01

  And you know what? Actually, I agree with him. There was another woman who was pregnant. And she was a black woman from Lambeth, had a black husband. And at the time, the vaccination rates in black Londoners particularly was really down. And so they'd been targeting campaigns to try and increase their participation. And she was like, "Okay, well, for starters, right, I'm pregnant. I'm not going to take any unnecessary risk", which, you know, within the fullness of time, actually, I also kind of really see that. But she was also like, "Why, all of a sudden, the government have something they want to give young black men in Lambeth?" But she also made this really interesting point, which was about how, when you go to vaccine centres, honestly, it just feels like you're going into a prison.

• 39:28Speaker 01

  And like it genuinely had not even occurred to me that that sort of triggering experience for somebody. And so I think that like actually getting people to understand numbers, the first bit of it is you have to understand them. It's about listening and not listening while thinking of the next thing that you want to say. I think you can't really change people's minds, right? People have to change their own minds. And I think that the best way that you can do that is to approach a conversation with empathy.

• 39:54Aria Finger?

  And I think to your point, you have to understand what their point of view is. What's the game? What was their reason for not? And then, you know, we've seen so many studies that actually AI and LLMs are the best at combating conspiracy theories or whatever it might be, because they can understand where the person's coming from and then give some nuanced reasoned argument. And so it's not that people's minds are totally closed. It's that everyone has a different reason. And so when you just attack them with your one size fits all response, of course they close down because you didn't know it was about prison or if it was about this or whatever.

• 40:28Reid Hoffman?

  Actually, I think the way the LLMs work is less, I'm arguing with you.

• 40:34Aria Finger?

  Right.

• 40:34Reid Hoffman?

  And more, I am asking you questions because it's exactly, it's the you don't change their mind, they change their mind.

• 40:40Aria Finger?

  Exactly.

• 40:41Reid Hoffman?

  Yes.

• 40:41Aria Finger?

  Right. The Socratic method.

• 40:42Speaker 01

  They change their own mind. Do you remember that amazing study where they got people, I think this was in Americas, they were Republican or Democrat, and they asked them about their feelings about Obamacare, right? And then they asked them how strongly they felt about it. And then they kind of gave them a notion and they were like, oh, do you know how a toilet works? And everyone was like, yes, obviously I know how a toilet works. It's like, okay, how confident are you? And people were like, 10, come on. And then they were like, okay, here's a diagram. I want you to explain to me how a toilet works and label the parts. And I want you to give me a full rundown of where the water goes and exactly what happens in the whole thing. And then suddenly people are like, okay, uh, Ashley, maybe not, no, no, no. Yeah, yeah. Okay, fine, fine, fine, fine,

• 41:22Speaker 01

  like, very bad confidence. But what they found was that by doing that, then they asked them like how strongly they felt about Obamacare or whatever it might be. And just that act of like questioning themselves also made them question themselves more widely on other topics. So you're right. It's like it's asking people questions, but to find out the answer, not to sort of humiliate them or anything like that, but just to find out the answer, I think there's something in that.

• 41:47Reid Hoffman?

  Going back to the probability thinking in AI. As AI develops, it'll get higher and higher probability of accuracy of information. And I think that one of the things that we're going to need do is have an assessment of where will most likely be right, where it might be wrong, when you want to look at it more. So, for example, there was a research thing that suggested that AI, GPT by itself, was better than AI plus doctor. But I think the reason was is because the doctors hadn't yet learned how to use GPT, right? They didn't know where they should go, oh, right, that's different than I think, and they're probably right, right?

• 42:27Reid Hoffman?

  Or, wait, this case is where I actually want to do more investigation. And I think that's part of what we're going to need, like, part of the reason why, you know, I'm excited about your work and it's good, is that thinking about, like, okay, when is this likely to be right and when is this likely to be wrong, is going to be part of our AI future and evolving. And so I think part of it is we're going to have to learn heuristics, and the heuristics, as opposed to the, I just feel, it's like, well, you know, generally speak, like, for example, one of the heuristics I use in AI, if you ask it a general principled thing, like, what are the seven rules of entrepreneurship? It'll generally be pretty good. If you said, like, one of the things that I did, because I had early access to GPT-4,

• 43:12Reid Hoffman?

  I said, has Reid Hoffman made a knockoff of Settlers of Catan? And if so, what is it? Because I have, and it said, yes, absolutely. I was like, wow, discovered that, there's almost very little information on the, and then it said, what Reid has made is a game called Secret Hitler, right? And there is a game called Secret Hitler, that the Cards Against Humanity people have made a version, and it created a Wikipedia answer that was completely fictitious. And that was when, because I have these evolving set of heuristics, you know, principles, it's like, well, when you ask a specific question, or give me a quotation, I'm always a little bit more suspicious. Absolutely. It's the edge cases. Yes, or specificity. Yes.

• 43:55Reid Hoffman?

  Because it's trying to be helpful to you, and it fundamentally still doesn't recognize. That in a lot of these cases, error is extremely expensive.

• 44:04Speaker 01

  Yes, absolutely. I totally agree. You know, one of the things I think is absolutely amazing about AlphaFold, right, which is, you know, you had Demis on your podcast, is the way that it also gives you confidence, right? So it doesn't just tell you this is the folding. So then you can see when the model is in its comfortable zone and when it's struggling. And I think that that's really, really helpful, especially when you're talking about situations like doctors assessing data and information.

• 44:31Reid Hoffman?

  I think a lot of the actually training and meta prompting will be like, for example, you can get G P T four, even as it is, to be a much better medical thing when you do a meta prompt with how do you do Bayesian reasoning with medicine? Because then all of a sudden it goes, right, I'm going to give you a Bayesian answer, right? And then all of a sudden, it's much, much better because it's like, well, there's a 64% chance that this is saying, and there's a 30%, but it's giving you a list in order with probability assessment. If you do the Bayesian meta prompt the right way, which is like, you know, what I would do.

• 45:05Speaker 01

  Yeah, that's so interesting. I mean, I remember seeing there was a paper about chain of thought reasoning, right? And the difference that it makes. And now, of course, the people have started putting reasoning into their models. It sort of feels like magic. You know what I mean? Like, it does feel like magic. But but you're right. It's about just looking again, having confidence in the places where it's confident and kind of going over again. It's really, yeah. I think subconsciously, I've been doing a similar heuristic.

• 45:29Reid Hoffman?

  Yeah.

• 45:30Aria Finger?

  So on many episodes, we have an AI element where we bring AI into the chat. And so since I think I know that you're a Jane Austen fan.

• 45:40Reid Hoffman?

  Sure.

• 45:40Aria Finger?

  And you might hate math jokes, but we're going to bring them, we're going to bring them in anyway. And so we asked Pi, the personal intelligence that Reid co-founded with Mustafa Suleman, to give us some math-themed Jane Austen jokes.

• 45:54Speaker 01

  Amazing.

• 45:55Speaker 05

  It is a truth universally acknowledged that a young woman in possession of a large number of admirers must be in want of a better statistician to calculate her chances of finding true love.

• 46:06Speaker 01

  I mean, amazing is taking a quite famous line from Jane Austen and just stuck the word statistician in there, which is great. It worked for me.

• 46:14Speaker 05

  Mr. Darcy's pride and Elizabeth Bennet's prejudice may have been quite irrational, but it was their common interest in geometry that brought them together in a most acute love triangle.

• 46:25Reid Hoffman?

  Doesn't quite do the dad joke thing.

• 46:28Speaker 01

  No, needs to work on this sort of build up and release of tension, you know, and that drag a bit more, right?

• 46:33Aria Finger?

  All right, we have one more.

• 46:34Speaker 05

  When Miss Bates heard of Mr. Elton's engagement to Augusta Hawkins, she was quite put out. "Why, it's simply not fair," she exclaimed, "for everyone knows that three is a crowd and four is a quadrilateral."

• 46:47Aria Finger?

  So bad.

• 46:48Speaker 01

  Yeah. Okay.

• 46:50Reid Hoffman?

  I see the comedians still have a job.

• 46:52Speaker 01

  Yeah, I think this is the specificity there is where I'm really at the edge, aren't we? All right, so one out of three. One out of three was decent.

• 47:00Aria Finger?

  Decent show.

• 47:01Speaker 01

  It was decent.

• 47:02Reid Hoffman?

  Quasi one out of three. It was one kind of sufficiently crossed and locked. And the other two probably would have had tomatoes thrown at the stage.

• 47:09Aria Finger?

  Okay, we have some work to do. We have some work to do. Okay, great. Well, that was our AI element for today.

• 47:14Reid Hoffman?

  All right, should we do rapid fire? Is there a movie, song, or book that fills you with optimism for the future?

• 47:29Speaker 01

  I'm going to go for When We Cease to Understand the World because it's just, okay, so beautiful, but it's like, it's just, it really captures the, how exhilarating it is to be at the brink of new knowledge. I think it really makes me feel great. Read about six times.

• 47:47Reid Hoffman?

  And by the way, since we just did the comedic thing, Stephen Fry read that book and reached out to love it too.

• 47:53Speaker 01

  Oh, yeah.

• 47:54Reid Hoffman?

  Yeah, because he also shares all of our passion. It is a great book.

• 47:56Speaker 01

  Yeah, it's really amazing. Really amazing. Because they did the Hay Festival together, didn't they? Yeah, that's right.

• 48:01Reid Hoffman?

  And that came out from that reach out.

• 48:02Speaker 01

  Amazing. Amazing. All right. What is a question that you wish people would ask you more often? Do you want another drink? Done. I don't know. I don't know. What do people answer for this one?

• 48:16Reid Hoffman?

  Perhaps the funnest one was I asked a friend of mine's kid, and the kid looked at me and said, "Do I want to be here?"

• 48:24Speaker 01

  Amazing. I'm sticking with my first answer then. I think that's better.

• 48:28Reid Hoffman?

  All right. So where do you see progress or momentum outside of your industry that inspires you?

• 48:34Speaker 01

  Oh, I think the stuff that's happening in biological spaces is really incredible. Physics is lucky that it has equations to discover, right? You know, you can look at all of that data of the galaxies and then you can come up with E equals mc squared. Like, I mean, almost impossibly simple, right? And biology doesn't have that luxury, but I think that we're now at the situation, or almost, where you can take the unimaginable complexities of biology and extract a sort of working model for how it fits together. And I think that is really, really exciting.

• 49:06Aria Finger?

  Awesome. All right. Can you leave us with a final thought on what you think is possible to achieve in the next 15 years if everything breaks humanity's way? And what's the first step to get there?

• 49:16Speaker 01

  Let's go crazy optimism for a minute here.

• 49:18Aria Finger?

  Please.

• 49:19Speaker 01

  Because, because I think that actually, you know, the history of humanity has always been a story about scarcity, right? It's been about resources being divided. And I do think that actually there is a way for science to make a gigantic difference for everybody. There are so many different, you know, areas where if science makes a breakthrough, like desalination, or nuclear energy, or whatever it might be, right? There's a number of different areas. Good battery design, right? These kind of things where we just need like, a little bit of a breakthrough, and I think everything, everything, everything can potentially change.

• 49:56Aria Finger?

  Thank you so much for being here.

• 49:58Speaker 01

  Thank you. That was so fun. Thank you. That's great.

• 50:08Reid Hoffman?

  Possible is produced by Wonder Media Network. It's hosted by Aria Finger and me, Reid Hoffman. Our showrunner is Sean Young. Possible is produced by Katie Sanders, Edie Allard, Sarah Schleid, Vanessa Handy, Aliyah Yates, Paloma Moreno Jimenez, and Malia Agudelo. Jenny Kaplan is our executive producer and editor.

• 50:30Aria Finger?

  Special thanks to Surya Yalamanchili, Sayida Sepieva, Thanasi Dilos, Ian Alice, Greg Beato, Parth Patel, and Ben Relis. And a big thanks to Taylor Forster-Cornes, George Kingston, Irenia Alvarez, Jenna Antonik, Ayee Kano, Natasha Mainz, Joshua Balogun, KJ Arthur, and Sophie Claire Armitage.