David Autor on AI’s impact on jobs, expertise, and labor markets

26:01So, you know, if you wanted to eliminate a third of people without laying anyone off, you just wait a decade and they'd all be gone. And most labor market change for adults, it actually doesn't happen mid-career, right? It's at the choice of the entry point. And so it often occurs across cohorts, right? So in the areas that saw these big China shocks, right? The adults who are manufacturing have not primarily moved on to something else. Some have moved into lower paid services. It's their kids who never enter manufacturing. So it really does matter how fast this goes on. We talk about autonomous vehicles all the time.

26:39If autonomous vehicles come Labor Day this year replaced all long-distance drivers, that would be a very serious problem because there are more than 2 million, I believe more than 3 million people who just do their living in driving vehicles. So that would be catastrophic, not because autonomous vehicles wouldn't be a good thing, but because that would be so much job loss all at once. If it happened over 25 years, that's kind of a manageable problem. People wouldn't enter the occupation, people would retire out of it, and it will happen actually much more slowly because even if this problem were solved tomorrow morning, it takes decades to replace all that capital.

27:16You're not just going to throw away all your trucks, right? You're going to replace them slowly over time. And so the concern with AI, I think that a lot of people have is it's just going to boom, you know, and it's absolutely the case that machines can acquire skills much more rapidly than people can, right? Once you have a machine that does something, wow, then you have a lot of machines that do the same thing. And there are, we will see this. I mean, we should not be naive to think that won't occur, right? If you're a language translator, right? That's, you know, you're under threat. If you're an illustrator, you're under threat.

27:49I think a lot of people who do just sort of workman software coding, there will be fewer... Actually, it's not completely certain, but we do see a big decline in employment in computer coding right now and software development. I shouldn't say in the software engineering, but in the people who write programs. And so it's quite possible. Now, I think we alluded to this earlier, that it also depends on how much, what demand looks like. Right. So like if we, you know, got like really, really good and cheap and fast at colonoscopies, people still wouldn't be lining up their proctologist office to get more of them.

28:25Right. But it is the case that if we get better, cheaper, faster coding. Right. There is a lot of demand for software. Right. Like you can't buy an appliance that doesn't have a microprocessor and it doesn't have embedded software running in it. You know that I mean, I'm sure my toaster oven has that. I know my coffee pot does because it regulates the temperature and tells me what it is. So it may be that we'll just get a lot more software coding, but it may also change what we use it for, right? So, you know, when people start developing websites, you know, back in their mid nineties, right, that was, that was all about skill in HTML, right?

29:01Writing markup language, you know, those websites, if you go back and look at them, they're so incredibly horrible looking, it's hilarious how primitive they are. Now there's lots of people who build websites for a living, but it's not really a technical skill. It's design, right? It's how do you present information? It actually has a different skill set that's involved. So that's kind of cool, actually. So the rate of change is a concern. It absolutely is. And now, OK, so now let me come to the last part of your question. You say, well, how could this be good for anyone? Well, this is not a given.

29:32This is kind of a good scenario. But as I argued a few minutes ago, a lot of valuable work in advanced economies is monopolized by elites, right? Professors, for example. or lawyers or medical doctors or financiers. And we don't face that much competition, right? You know, there's huge barriers to entry. There aren't that many of us. You know, you can't print them that fast. And so, you know, we have this, you know, lock. And, you know, that's fine for us. Like, yeah, things are expensive. Healthcare is expensive. Education is expensive. Legal service are expensive. So, but that's okay because I get paid a lot too because I do that, right?

30:09But for most people, they don't do that. It's just expensive. So if we can enable more people to compete in those domains, if we can enable more people to enter software development, more people to do medical services, more people to be lawyers. Now, I don't mean that everybody can do anything, and I don't mean that we don't need doctors anymore because people have AI. But you could imagine more supporting roles for people who don't have as much elite education to do that type of valuable work. In other words, just instead of, you know, the last wave of technology pushed so many people out of the middle and down towards low paid services, it would be great if we could use this technology to enable more people to move up into new opportunities.

30:53That's the good scenario. you.

31:04Now, have you seen anything that that kind of is how other than just getting people into this, how they should start learning these tools in order to start kind of beginning to learn their own paths on what the new contours of how jobs will be transforming, how markets will be transforming, how industries will be transforming? And is there separately anything that you've been looking at as kind of a macro thing to say, you know, here is like a, you know, kind of call it a 30 ,000 foot or a 40 ,000 foot map by which people should start thinking about how these transformations are going to happen?

31:41Learning to use AI well actually is an important skill in itself. And it is, you know, the first, like the first instinct that you have to develop. I mean, I'm old enough. I remember a world before Google. I remember developing the instinct to Google things. You'd be at a dinner party or whatever, and you'd say, oh, I thought President Taft said this, and I think someone would say that. Then someone would say, well, why don't we Google it? Everyone would be like, oh, Google it. We developed this kind of subroutine or an instinct or whatever, this habit to turn to it. And knowing actually when to turn to AI for things is also not obvious.

32:20It's something you get better at. For example, I was talking with some of my research assistants and we were looking at this table and saying, could this be made into a figure? And we're trying to say, well, would it work as a figure? And we're saying, well, what if you did this way? And then I said, oh, I know. And I just took a picture of it. I stuck it into an AI and say, make a bar chart of this. No, now rearrange it like this. And did it like that. Or of course, five minutes we all did on the screen and we said, yep, this won't work. But that was a very time efficient way to do it. And so I always have a chat window open and I use it to sort of bounce ideas or look things up and so on.

32:51But another important thing to realize about AIs, and this goes to the distinction between collaboration versus automation, AI isn't really useful for things that you don't understand because it's not that reliable and it will misunderstand for you and lead you astray. So if you're using AI to do something you really don't get, you're kind of out over your skis. And that's not a good place to be. So that's why I say it's a good collaboration tool because it's complementary to, you know, if it's something you know about, then you can adjudicate, oh, this makes sense, this doesn't make sense. You can ask the right question and you can kind of, you know, filter and interpret that knowledge.

33:30If you're trying to get it to do something for you that you don't, you know, write me a paper about, you know, the currency of the Roman Empire or something like, you know, it might very well make up some Roman currency you've never heard of and you wouldn't know. So that also is part of learning to use AI is learning the instinct of when you know enough to know if it's doing something useful and when you can use it, you know, so you've got to have, you know, it's like, it's like I could use, tell an AI, you know, tell me how to do a, you know, a surgical procedure on someone. I shouldn't do that.

34:05Right. If I'm a surgeon, right, and this is an extreme search scenario and there's no other surgeon around, I can look at the AI, give me instructions, and I could probably do it. So you want to use it in the domains where it can collaborate with you and augment you, but it can't automate away, substitute for just fundamental lack of knowledge in some area. That's a dangerous place to be. So sort of thinking about the possible future we want to shoot for, like you're talking about AI being complementary. And that's one of the visions that obviously Reid spoke about in superagency. It is, OK, how can we have more people sort of moving up and being able to do before they could be a nurse?

34:44Now they can be a doctor before they were a radiologist assistant. Now they can be a radiologist because they have these additional skills. And it's actually we work a lot with this organization, Opportunity at Work, which is trying to increase the returns to skill based work as opposed to just degrees. If you have the skill, you should be able to get the job. So that's sort of one vision that in the future, everyone who perhaps is in a low wage job right now, or not everyone, but some of those people can move up into middle wage jobs. How fantastic would that be to add, you know,$20 ,000 to each job?

35:15Another sort of positive vision, actually, for AI that some people talk about is that less people will be doing jobs. Like we will have so much money, our government will have it or the big AI companies will have it or someone will have it, that these jobs are not necessary. And we're able to give out a UBI or we're in this new world of sort of freedom and only working 10 hours a week, which sounds a little fantastical. So I would love you to comment on sort of those two visions, both of which are sort of positive is positive visions from sort of the new AI future. Yeah. So the first vision, of course, I'm all behind.

35:50And it doesn't need to be, by the way, that everybody is doing middle or high, you know, skill work. Right. So if we just extracted half the people who were doing leisure and hospitality and janitorial services from that work, the half who remained would get a big pay increase because firms would have to compete for them more. The problem is there's too many doing it, and that's why wages are so low. And this is a well-known kind of economic parable. Why do the wages of barbers rise over time? They're not getting any faster cutting anyone's hair. And the answer is, well, they have to be compensated to be barbers as opposed to being something else.

36:23Right. So if there's, you know, in the long run of productivity rises and there's, you know, there aren't lots of people and you if you will need to convince someone to do, you know, food service or cleaning, whatever. And, you know, they may want to, they may not. But if you want to in a competitive market, if there aren't that many people available, you'll have to pay them more. So it doesn't have to be everybody. Just more opportunity benefits a lot of people, including not every and they don't have to all take that opportunity benefit on the the notion of, you know, we'll have all this income and therefore have all this leisure.

36:53the concern i have with that is not that we won't have wealth but they will have a lot of trouble distributing it equitably uh you know we are already an incredibly wealthy society right we're arguably the wealthiest society humanity's ever seen and we don't really have any real scarcity here and yet we have a lot of people who are quite poor and don't have access to health care and i don't have a safe housing don't have safe neighborhoods don't have good schools right that's not because those resources don't exist it's that we don't have a system where people that we really want to distribute that much to people who don't somehow earn it on their own through the labor market and i don't know that more wealth is going to solve that problem uh and i really worry about a world in which so much income is concentrated the notion that we are sort of reliant upon the generosity of strangers through the tax and transfer system to sort of make us take care of all of us.

37:50I just don't know if that's a reliable thing to do. It generally doesn't work that well. The U.S. is not getting more generous as a society, even as it's getting wealthier. We seem to be getting less generous. And so I like to compare two scenarios, what I call the WALL-E and the Mad Max scenario. So you've all seen the movie WALL-E. And, you know, it's a future where basically people, you know, sit around on, you know, kind of hovercraft armchairs, watching, you know, holographic TV, drinking big gulps, and they all weigh 300 pounds, right? And this is supposed to be some sort of future dystopia, because there's no work to do and everyone's bored.

38:32But I view that as the good scenario. because the more likely scenario to me looks much more like Mad Max Fury Road where everybody's competing over, you know, a few remaining resources that aren't controlled by, you know, some warlord somewhere. So you can have a world that's very wealthy and yet most people don't have anything. And so that's why I so, I like to think about work because I actually think the labor market has so much going for it. Two things. One is it's intrinsically a lot more equitable or equal than the capital market. Because everybody in a society that doesn't have slavery and doesn't have labor coercion, everybody owns no more than one worker, right?

39:13They just own themselves. And so we all start off, you know, at a kind of a relatively even starting point. And so, you know, 60 % of the income in the United States is labor income that goes first to workers. And so it just creates much more shared resources. Work also has a lot of virtues, I think. It gives people identity. It gives them structure. It gives them meaning. I mean, not all jobs are good. So that's a luxury for me to say work is all great. I don't want to say that for a minute. But the other thing is, in a democratic society, if most people are working, then it's easy for people to say, well, these are people who are contributors to our society.

39:48Of course, they have a vote, right? Of course, we're the co-owners of society. Whereas if we're in a world where we say, well, all the money comes out of a fountain in San Francisco, next to the OpenAI headquarters or something, then it's much harder to say that everybody deserves their share. I mean, I might agree to that, but I don't know that everyone else will. So that's why I'm not excited about a world in which the resources are mostly coming from machinery and capital and everybody especially supported. Now, let me say, Okay. Important to emphasize, you know, we do much, much, much less work than we used to, right?

40:28So at the beginning of the 20th century, you know, 120 years ago, 125 years ago, people worked on average in the United States about 3 ,000 hours a year. Now we work on average about 1 ,900 hours of the year, right? We now, you know, we've invented the weekend, you know, we have vacation and so on. Additionally, you know, people used to enter the workforce as soon as they were physically able, right? You know, 10 years old and they would work until they died. Right. And now, you know, our side people enter the labor force, you know, 16, 18, 20, 25, their PhD students, 40, 45. And then they retire when they have, you know, 20 years of health remaining.

41:07So we work a much smaller percentage of our healthy lives than we used to. So we actually have much more leisure. So we've handled that well. It's not that we've just become this kind of overworked society. That's kind of a myth. So I'm in favor of that. I'm in favor of us all working somewhat less, or at least those who want to work less. I'd like to work more, but that's very different from there being no need for people to work and that they just hope that the society will care for them. That I'm not as confident in. Well, one of the things that I think this discussion highlights in a really interesting way is there's kind of two issues that I think get combined in the inequality discussion, one of which I'm extremely sympathetic to and I think is very important to navigate, and one of which is complicated.

41:57The complicated one is like the, well, no, I want there not to be that much of a gap between me and you. Like I just think that a gap is an issue. Like, you know, you have two cars, I have one, and I think that's a real big deal, whatever that kind of thing is. And I tend to be a little bit more, you know, how do we really figure out what the right mechanism of the gap is? But a lot of people, that's the real driving issue in their rhetoric. but I think it's more complicated. Now, the one that's not complicated that I think you're highlighting that is extremely important that we solve is a notion of increasing quality of life across, you know, everybody and increasing and quality of life isn't just like, oh, look, I can, you know, I can afford the cheeseburger.

42:41That's great. But it's also kind of like, do I have meaningfulness and control and respect and personhood and, you know, place within community and society? And that kind of breaks down into two components. One component is, you know, kind of what are you learning to do that gives you kind of a unique position in your community and your workforce, you know, and your, you know, you get your kind of your tribal group. And, you know, that's part of where I, you know, super agency trying to embrace the future, learn, become AI curious, you know, step into it, don't get forced into it, but like jump into it first and foremost.

43:17But the other one's also reducing, this is the abundance thesis of reducing the cost of a whole bunch of things. So like, for example, part of how you increase quality of life is you say, well, one of the things that AI can create is a 24 hour, you know, seven days a week medical assistant where, you know, very, very few people, even amongst, except when you get to super wealthy actually have that in the U S has anyone gotten good kind of sense of, of both this, not just the, the, the thing we're talking about, like the jobs and the transformation of the industry, but also on the kind of quality of services and quality of life based on, you know, because with AI, I can see not just a medical assistant that can essentially one for free for everyone on a smartphone, but a tutor, a legal assistant, a set of things, none of which I think will take away actually jobs.

44:08I think there'll be a whole bunch of coordination, you know, kind of amplification there. I mean, they'll take away some jobs, but they'll also create a bunch, I think, in this. but in that kind of quality of life that can possibly come from AI based on, uh, helping people in all these ways. I mean, for sure. I mean, look, we, even people who are, you know, much, much less affluent in the United States, you know, in terms of the sort of physical quality of life or is much higher than it was, you know, even 40 years ago, you know, people, most people didn't have air conditioning, right? They didn't have private transportation.

44:49They certainly didn't have all the things that come from mobile telephony. And mobile phones aren't just about entertainment. They're about communication. They're about access to services and information. So there are many, many ways that there are a lot of things that our material standards of living have improved because we've gotten better technology for doing it. So people live in larger houses. They have more indoor plumbing. They have more electricity. They have bigger TVs. and again you know more importantly they have you know cars air conditioning and i do think yes ai will make a lot more service can be used to make a lot more services less expensive and and you know we use the web this way all the time right you know the amount of time we spend you know waiting on phone queues or trying to buy airline tickets or uh or dealing with banks and so on it's you know it's actually a lot more convenient than it used to be i i remember buying plane tickets on the phone or, you know, waiting in line to see a bank killer.

45:48So that's, I think that's very important, but, you know, I don't think low prices are sufficient because, you know, what are the things that are really defining for, you know, kind of a good quality of life in addition to the work you do? It's do your kids have opportunity, right? Are your neighbors, neighborhoods safe? Are these good schools? and also equally important, do people get a fair shake when they start? My problem with inequality, I'm with you. I don't care if I have two cars and some people have 20 cars. I'm still okay with that. But it is the case that inequality can lead to dynasticism where the next generation is like one set of kids starts so far ahead of the others that sure, that even if their family got wealthy on the merits, then there's no longer anything close to fair chance in the next round.

46:47And so I think that's something we, and those things are harder to deliver just through low prices, right? Just good schools, good opportunity, safety. A lot of that depends on basically having a level of affluence in your family and in your neighborhood that supports those things, maybe we'll get better at that. But so that's the key thing. So what matters to people is, of course, economic security, like from day to day, can I pay my bills, right? Am I going to eat? Do I have a roof on my head? But then like, do I have a job that provides me stability? And then do I have a way to ensure that my family is going to, you know, is going to do at least as well as I have done and get good opportunity commensurate with their own hard work?

47:33I do think what is important, actually about a lot of this is uncertainty. So if you didn't have the uncertainty that your rent would go up next year, if you didn't have the uncertainty that someone would get cancer and so you would go into medical debt and you declare medical bankruptcy, like those aren't really sort of price issues. Those are more uncertainty issues. And so one of the things that I think a lot of people talk about is declines in unions and collective bargaining. They leave workers more vulnerable to pass shocks. Obviously, there's also more uncertainty about your wages. Are you going to be fired.

48:03There are certainly some negatives about unions. Sometimes they lock in workers that we don't want, et cetera, but they do sometimes provide that certainty. So my question for you is, as we want sort of gains to be broadly applied, are there institutions, policies, collective bargaining? Like, what are the things that we can put in place to make sure that these gains are broadly applied? Certainly collective or, you know, kind of worker representatives are, you know, There might have been a time when we had too many, but now we definitely have too few. And the decline of collective bargaining at this point, I think, has left workers very vulnerable.

48:37So I would like to see more of that. I would like to see more investment in our schools, in our children. Those things would make a big difference. And then I do think people in the United States have a much greater level of economic insecurity than do other people in less affluent economies working the same jobs. and we tend to tend to think it's a it's a necessary factor of life and it just isn't if you work on a mcdonald's in you know in norway or denmark or even in france you're going to have vacation you're going to have health care uh you're going to have you know sick leave and we this does not have to be uh inaccessible or only accessible to people who are you know middle and upper class and that's a choice that we make but we tend to think it's inevitable and it's not You know, the U.S., we're so impressed with ourselves that we forget to make the right comparisons about, you know, and this actually, and the other way, too, people don't realize how affluent we are.

49:38Like, you know, people think that America has been in decline, but, you know, our productivity has risen 30 % relative to Europe over the last 20 years. We're much, much better off. Our labor markets actually work really well. So, you know, everyone's talking about making America great again, but, you know, actually we've done a lot of great things. We should recognize that. I mean, we're also, you know, the U.S. is an incredibly innovative country, right? You know, AI comes from here, so much of the community or the internet era, but we have an incredible culture of innovation that has been so important to us.

50:07So we should recognize both our strengths and our good fortune, but also recognize we can learn a lot from other models. And it doesn't, not everything that is bad is inevitable. School shootings are not inevitable. And people not having adequate healthcare, not inevitable at this level of income. Those are choices that we're making. I don't think we're making the right choices. So one of the things that I think, you know, is a kind of a question that we're going to, we're going to see happening that'll be a little bit different within the AI universe is, you know, previously kind of workforce transitions and so forth have happened to what I would think of as industrial timeframes, which is, you know, part of like when you look at our educational system, it's like, you know, train, then deploy for a lifetime versus, you know, kind of a constant recycling.

50:56And I actually think that part of what happens as we get into the new world of AI is that you'll need to have more constant adaptation. It's part of the reason why my very first book that I wrote, Startup Review, was how we're all going to have to be more entrepreneurial and how we think about our work and our careers. Doesn't mean start businesses, it means, you know, how to do that. And obviously, I, you know, part of my optimist is thinking about how AI can help with that. Is there any kind of good work, good lenses, good principles for people thinking about now these transitions are, call it within, as opposed to within a 30-year timeframe, you know, they're within a 10-year timeframe.

51:35And so that kind of moving along and adjusting is going to be one of the things that's going to be important throughout kind of a human life, a human career. And so have any principles or work been done so far in this? I'm convinced it's going to be very important. Yeah, I'm convinced as well. I would say the work is early. Like, you know, like, for example, I think everyone who looks at AI says, oh my God, there's so much potential here for education. It's amazing how little education has changed in the last millennium or so. And even, you know, if we walked into a classroom today from, let's say, you know, we all left school 30 or 40 years ago or 20 years, we wouldn't be surprised by a single thing in there, right?

52:23Or the way things are done, it's really not different. So I think we need to figure out how to use these tools to get better at education, at teaching ourselves and learning new skills. And I think, you know, one of the things we know about, especially for adults making transitions, is they learn much more successfully kind of experientially than they do going back to classrooms, right? It's shocking to me as a professor, but not everybody loves being in a classroom. And, you know, we sort of forget this lesson over and over again, right? So remember, like MOOCs, massively online open courseware, right?

52:57Supposed to just everyone was now going to be a, you know, a botnet herder or, you know, an ethnomusicologist or whatever they wanted to be. And they really weren't very successful. and people don't talk about them much anymore. Why aren't they that successful? They were like simulated classrooms, right? And it's like everything you hated about a classroom and worse, right? Like who wants that, right? At least a classroom is a social environment, whereas watching a video is not. So if we want to use these tools to make education better, we need to make what do better, what makes education effective.

53:29And that is kind of engagement and immersion. So I certainly think that there's a lot of skills that people can learn in simulated environments, right? So, you know, like we do this, right? If you want to fly a plane, you're going to spend a bunch of time in a flight simulator. If you're learning to do medical procedures, you're going to start off on animatronic dummies that bleed and scream, right? Why don't we do that for plumbing and electrical work? Well, it's clear, you know, we do it in a few places because it's so damn expensive. We don't do it everywhere else, even though we could, but we can now.

54:01That will be possible. So I think that's an important lesson. It's also the question of how do we get – there is a lot of research now on how should we interact with AIs? What should they tell us to help us learn? And one thing that a consensus that literature is what they should not do is just sit around telling us what to do. That's not how we learn. And in some ways, they need to interact with us in a way. Like say, there's one theory that says if you're coming to a choice, there's A and B. The AI could say, do A. But it could say, well, you could take A, and this would happen. Or B, and I predict this would happen.

54:37The contrast between those things is actually very instructive for learning. So if you want to help people learn, it's not sufficient to tell them what to do. You need to give them information that supports that choice and enables them to reason about it. So there's a lot more work going on now about what are the ways. And I'm doing some experimentation on this myself. I'm a Google Tech and Society visiting fellow. And one of the things we're trying to do is stand up experiments on expertise and to ask whether tools that are built to support experts, not do they just help them get better results, probably they will, but do they help them acquire judgment faster?

55:12Because in so many, if you're a lawyer, if you're a doctor, if you're a researcher, if you're an actuary, if you're a carpenter, you develop judgment over time. That's part of the expertise that makes you so valuable. It's not just like what you learn from a book. You learn how to make the right decisions at the right time, at the right moment. And so I would like to understand better what are the tools that enable people to do that faster, get those skills sooner. Because, of course, it takes a long time. Expertise, it's great, but it takes a long time to get expertise. It's slow, it's expensive, and even the best experts are fallible.

55:50And most people are not the best experts. So, you know, so that, so I think that that's the question we should be asking. And that's where the research is that I see is about how do you do these interactions in a way that makes people smarter. And I think kind of the key principle for me is automation versus collaboration. That, you know, automation is when you tell people what to do and that takes out expertise. And collaboration is when you harness expertise, that you give people the information. And collaboration is, like if two people, two experts look at the same problem and reach different answers, and then they put their heads together, the answer they come up with may not be the average of A or B.

56:29It may be C. It may be something totally they weren't considering, right? Two people collaborating could actually come up with a different answer than either of them thought originally, which is not something that can happen when a machine tells you what to do. So I think this principle of collaborative design, to me, seems like very essential for thinking about how we help people learn and acquire skills more efficiently.

56:58We'll now move to a rapid fire. Is there a movie, song, or book that fills you with optimism for the future? so i gave this one a lot of thought and i i came up with the answer that's not quite in any of these categories but it would have to be the tiny desk series of concerts on npr i don't know if you guys watch tiny desk but oh my god so you know this is started like 20 years ago bob boylan who was their music editor started inviting bands to come play at his desk uh and they would just sort of film those and over time this has become an institution so like major acts that you know so like, you know, Taylor Swift and not Bob Dylan, but, you know, almost everybody else you've ever heard of shows up.

57:38But the greatest thing about Tiny Desk is they're in an intimate space. So it's a small group and it's often people you haven't heard of. And the range of music that you encounter is so incredible. Things you would not see, like, you know, I go see Anderson Pack's Tiny Desk concert or go see the Tiny Desk concert of the Buena Vista Social Club. These like, you know, 15, 20 minute productions. I look forward to this like so much. And the amount of music that I've encountered that I never would have heard of that gives me so much joy. So tiny desk. David, what is a question that you wish people would ask you more often?

58:09You know, I wish people would ask more often about, and I ask people this all the time, like, what is your counter life? What is the thing you would be doing if you weren't doing what you're doing? And that often tells you about something else that they're really passionate about. And, you know, in America, especially, we always ask people what you do for a living. What's your work? What's your job? And that so much summarizes people's identity, but kind of too much. So yeah, asking people their counter life, I think, which people would ask me. Oh, so now you're going to ask me what is my counter life?

58:34Yeah, David, okay. Yeah, let's hear it. You know, I think there's another world I could have been a sailor. I love to sail. I still sail. In fact, I'm in a place where I sail. And I could have imagined, you know, doing around the world sailing, doing racing, crewing. So that would have been okay. Where do you see progress or momentum outside of your industry that inspires issue. People in the West, certainly in the United States, if they look back over the last 20, 34 years and they go, eh, it's been mid, it's not been a great half century. But actually, this has been the best 40 or 50 years that humanity has ever experienced.

59:15The amount of people brought out of poverty. We've never had a global middle class until now. And partly this is China itself, right? China has, you know, reduces poverty level from 70 % to, you know, effectively a couple percentage points, and that's more than a billion people. But it's also created prosperity in Central and South America, in sub-Saharan Africa. And in fact, you know, growth in sub-Saharan Africa has been really strong and a livelihood to improve. Like, you know, it's still very poor, but it's much less poor and health is better. And so it is, I think we overlook how much progress there has been in so much of the world.

59:55And so, you know, we don't appreciate our good fortune, but we also don't appreciate the good fortune of others. So I think that is overlooked progress. All right, our famous final question. Can you leave us with a final thought on what you think is possible to achieve if everything breaks humanity's way in the next 15 years? And what's our first step to get there? So if everything broke our way, if we really did this right, you know we would make it's not that we put ourselves out of work but we would give people more secure and fulfilling work we would give them more access to education and access to better health care everywhere and those things alone would kind of improve welfare in so many dimensions not just you know in terms of material standard living not just in comfort but investing in our kids creating opportunity for the next generation so I think that would be great and And that's feasible.

1:00:47I mean, that's the thing. Many of these things are feasible. If we think we're not going to do them, it's not because we couldn't do them. It's because we're somehow not delivering on what is feasible. And that's the kind of sad thing. Everybody knows AI could be used for all these great things. Everybody also knows it could be used for really terrible things. And your belief about what's going to happen is not really a belief about AI. It's a belief about what humanity will do with this opportunity. Will we squander it or will we make the most of it? And I think most people, I don't think anyone thinks we'll absolutely make the most of it.

1:01:22I'm sure many people think we'll totally squander it. But I think many people are really deeply, deeply uncertain. So, you know, in terms of breaking our way, this is, you know, as my friend Josh Cohen, a philosopher, you know, likes to say, you know, the future is not a forecasting exercise. It's a design exercise, right? We're building it. And so breaking our way is not just a matter of luck. It's a matter of making good collective choices. And that's extremely hard to do. And so that is what's feasible, but not easy. If we were going to do that, like, where would we start? I would say, look, healthcare and education, two activities in the United States, that's 20 % GDP.

1:02:01A lot of it's public money, actually. And this is where there's such great opportunity, where AI could be a tool that could be so helpful to us in a way that other tools have not been. And that's where we could be really investing. And investing doesn't just mean more treatment for rare diseases. It means things that make healthcare more available to everyone so people have longer lives and higher quality lives. That's where I'd like to get started.

1:02:58Special thanks to

1:03:07And last but not least, a big thanks to Abby Abazorius.