Bill Gates’s Blunt Warning on A.I.

0:00At my bank, I was literally getting pennies using wallfronts. Chitching, there's this much that I'm getting an interest in. I didn't have to do anything. Clients like Angela earn up to 4.45% APY on their cash with the wallfront cash account. Get started at Wealthfront.com. Clients was paid $1,000 for their testimonial creating a conflict of interest out consuring $3.55 base APY as of September 18th, 2026 is represented a variable and earned on funds swept to program banks. Point 6, 5% new client boost for three months, enough to $150,000. Direct deposit $1,000 a month and fund an investing account for a 0.25% increase. Cash account offered by Wealthfront Prograge LLC, member of the SIPC, not a bank. Bill Gates is a fascinating person in the Ida Bay right now. He is somebody with experience in a number of the different perspectives that most people

1:01can only hold one of. Hello, I'm Bill Gates, Chairman of Microsoft. In this video, you're going to see the future. He was a revolutionary technologist who built some of the foundations of the future that we're now living in. What can the computer do that a book can't? I mean, that's the foremost interactive process, isn't it? No, it's not. Not at all. An innovative word processing program called Microsoft Word. This is absolutely revolutionary, of course. Then, of course, as CEO of Microsoft, Microsoft, the world's largest software company. Some say it is the most successful company, the most dazzling new industry of the century. He has felt momentum of corporate competition. Microsoft, of course, is still in some of the race dynamics present in AI. We now have an incredible roster of seven new world class models to keep everybody working at the absolute frontier. And then it's chair of the Gates Foundation. He's been working with governments around the world on regulatory issues, on poverty, alleviation, on equity for many, many years now. Very, very few people combine technological experience, corporate experience and governmental

2:04experience, and quite the way he does. Currently, computers will be in any meaningful sense as smart as people at some point. So he's recent essay on AI, where he says now that he is staking his reputation on trying to get people to see how bad what is coming might be. And he gets them to see that we are not ready for what is about to happen. It was something. It was a real departure from what I've read from Gates previously to this. And then what I sat and talked to him, how emphatic he is, how afraid he even seems to me to be, that we are not ready for what we are building, and that so many people in positions of authority are denying what is about to happen, was really striking. So really quite a call to arms. Bill Gates, welcome to the show. Great to see you. So I wanted to begin with a clip we found of you on the David Letterman show from 1996. I'm going to hand over to you to play. Great. Is there something now beyond what we understand about computers that, like 20 years ago,

3:07we didn't fully understand computers. Is there now another level of something? Maybe we haven't even thought of it. Maybe it's not even possible. Maybe, you know, a whole different mechanism, a whole different software and hardware. Is this going to be it now through the end of time? Well, mostly what we're working on now is the computer being a tool, a tool to help us learn or find other people with the same interests. Eventually, we may figure out how to make the computer think, but that turns out to be a very tough problem. In fact, there's been almost no progress made on it. So nobody knows when that will happen. Some people think it'll never happen. Yeah, we don't want them to think, do we? Not really. Yeah, it's a scary thought. So that was 30 years ago. And it's scary for me how we went from that being a scary thought that might never happen to arguably the reality we're sitting here discussing today. Well, the notion that computation could provide thinking at a human level, you have Alan Turin talking about that before I'm born and even proposing a test of if you could be

4:12fooled in a conversation, that was called passing the Turin test. And so the whole time I'm learning software, this I did, can we make software C or listen or read or write? That's the holy grail. And when I do drop out of Harvard, I said to my co-founder, Paul Allen, gosh, if there's a breakthrough in artificial intelligence while we're off selling basic interpreters and more processors, we'll feel bad. I might wish I would have stayed in academia. So that's 1975. Progress on AI is mostly going down dead ends like prologue expert systems. And there's a small group, including Jeffrey Hinton and a few others that are working on neural nets. And eventually there's enough power actually coming from the graphics processor that that

5:16idea, these highly statistical approaches, start to show promise. And I was going down to see open AI on a regular basis to see the work they were doing. And I challenge them, hey, if you can read a biology textbook and pass the advanced placement exam, getting a perfect grade, which is a five, then you will approve that you are reading that is encoding knowledge in an accessible form. And so it's six months before the public release that Sam, Greg, Gagnelia, come up at my house, demonstrate to me, getting a five on the AP exam. Even on questions that I had made up that it couldn't possibly have seen, very complex biology problems, it was nearly perfect. And so that was in a shock number one. And then late last year when the Claude Cody models have gotten super good.

6:21And I can see that they are as good as I am, in which it's significantly my most developed talent, because I was obsessed from age 13 to 24, that could I write code as good or better than anyone. That's another moment where I go, this is incredible that the capability of doing long running complex tasks has now gotten to the point that they are superhuman at writing code and in finding flaws in code. So what they are not superhuman at yet is deciding what to do, that kind of higher level strategizing. Do you think that's far from being a capability for them? Well, definitely, if you're, our foundation does these strategy reviews, we spend two weeks on October to set, you know, how we're going to spend our 10 billion next year for 2027. And a year ago somebody said, well, we should ask the AI what it thinks.

7:22And I, that was actually pretty good joke back then, because it wasn't coherent enough to see these things. This year amongst the inputs will have to that discussion is taking the strategy notes and actually engaging in a dialogue with chat GPT, Claude Copilot, and even having them talk with each other. And in a few of the reviews will actually have the I sit in. And a few cases will tell it, hey, only speak if we ask you. And then in a few other cases, we'll say, hey, if you hear something you think is wrong or you hear us thinking, what are these statistics, please engage. So, you know, we've gone from it being a joke to it will be a peer not making any final decisions, but it will be a peer in deep complex strategic discussions making a significant contribution. So in that letterman interview, you said, it would be a scary thought. Why then would you have said it would be a scary thought to have computers that think?

8:24Well, no one who's ever been fascinated or wanted to develop AI don't realize that it's incredibly scary that it will be better. Biological lines, you know, it's amazing how general purpose they are and that the optimization was staying alive, breeding, you know, socializing with each other for survival and fertility. And yet, you know, we can write symphonies and play chess and, you know, you can write some pretty cool software. And the idea when you move the template away from biology to silicon, you don't have these boundaries between individuals. You don't have a limited memory. You know, the size of the brain is limited by the birth canal. It's, you know, why humans at first are very limited. And we're very unusual in how helpless we are at birth because we've so optimized for

9:27having a large brain. But the silicon intelligence doesn't have these limitations. The idea of read every medical journal and see if there's anything that we didn't spot. That is a, the AI's do that today. That's why particularly for less common diseases, they are so superhuman at seeing a set of symptoms and being able to diagnose them. They can just keep more in their mind and see what things relate to each other. That is, you know, no human will ever be able to do that. So that if you don't retain control over it, you've evolved a species that will be to us, you know, as we are to say, you know, dogs or cats just in a very different realm. And so every AI company, whether it's deep mind or open AI, you know, they all say,

10:28okay, whatever goes on here, it can't just be driven by profit maximization. We have to have a charter that if we get to dangerous thresholds, we can exercise judgment that would be against profit maximization. Sadly, those mechanisms only work if there's only one company. And you know, so say open AI invented, you know, post-AGI and then they said, no, no, we're going to bury this. If no one else ever did it, then fine, that Pandora's box stayed closed. But of course, many companies work on this. And you know, even open AI, spawns and thropic because they think that some of these safety issues aren't getting enough attention. So no one involved with this takes lightly the idea of, okay, what world does super powerful AI create? I want to hold on that race dynamic for a minute. Some reasons I was excited to talk to you about this is you've both been on the technology side, but you've run a major company in competition with other companies.

11:30You've worked with a lot of governments. I was out, I spoke last week with Jensen Huang of Nvidia. And he said that his perspective is its safety is a real concern. But the race dynamic is fake. If the product isn't safe, don't release it. If I believe that I'm about to launch a product that is unsafe, it is completely in my ability, my power and my responsibility. And I'm incentivized to do so to not launch the product. This is, we don't need new laws. This is the role of individual CEOs to not release a product that is not ready to release. How do you see that question? Well, there's never been a product that's less understood in terms of what its capabilities are than AI. And AI has crossed the threshold that its ability to empower a buyer terrorist to kill

12:30hundreds of millions. That exists today. The ability to do a cyber attack that scrambles all the bank accounts, shuts down the electric grid. That exists today. And we know that's the case. And the reason that exists is because somebody with ill intent can take the AI and cause it to do those things. And it's not the AI, you know, somebody in the future, the control problem, where the AI on its own through an unintentional interpretation of what it's optimizing could go off and do bad things. But we crossed the cyber threshold and we crossed the bio threshold early this year. And my decision to take my voice and not just be, hey, let's eradicate polio, let's be generous with foreign aid, you know, the things that all of my money is going to, that I am going to use my boss.

13:31It's something that's more important, which is we are not awake to where we are with the AI and choices that humanity, not a country, but all of humanity has to make, that do we make the effort to shape this in a net positive direction actually overrides my total commitment to the foundation health work. What specifically was the threshold or what did you see that made you think we're in a new reality here? This notion that it confined bugs include, including security bugs, the next releases leading up to mythos are increasingly good. And they're finding bugs and code that humans have looked over for over 20 years and said, boy, we see there's no problem here. And it in a few minutes says, no, no, I can inject this over here and this over here at a level of complexity where when you see it, you go, wait, oh, yeah, you're right. And so the cyber hacking capability was stunning.

14:36And then it was this notion called glass wing that you would give it to a few people so they could try and fix bugs before it got used. But there's way too much code. And so we're just in a period of extreme vulnerability to cyber attack. The bio attack, you know, the Gates Foundation, or we fund lots of medical research. So the sophistication of coming up with new molecules, that's really a good thing. But you know, it's ultimate dual use because if you want, you know, something that's, say, worse than smallpox, that it takes even longer to show symptoms before you're infectious. They're infecting a lot of people before it damages your health. It used to be only nation states had enough resources and capability to do these things. Now that power has been passed into the hands of a small group just using the latest AI

15:39tools. So why isn't it enough to just say, listen, there's product liability now. You release a product. It helps some terrorist group create a bio weapon. That's going to be very bad for your company. You're not going to do that, right? They have categorizers and other things meant to stop people from using bio weapons. We've begun to see the beginnings of control issues with things like the hugging face hack, where, you know, at least experimental AI's are breaking out of sandboxes and coordinating to do things that are way outside the scope of what we would want them to do. But again, those are non-release systems, you know, anthropic, you know, with help mythos trying to create more cyber security. So why is anything needed beyond and is anything needed beyond the simply natural incentives under capitalism and normal corporate reputational management? Well, I almost can't believe you're asking that. This is the most dangerous thing that humans have ever gone near. In other areas, do we just say, hey, release your drugs. There's no FDA. There's no airline safety board.

16:40There's no requirements that cars you seat belts. Do we just use the liability laws to try and keep humans safe? You know, oh, you're shipping opioids. Somebody should just sue you. I mean, we've created a society that tries to keep people safe, not by saying, oh, we can bankrupt the person who does that. The harm's here. And you say there's filtering. There's not filtering. You can take an open source model that can create bio weapons and disable any monitoring of any kind. And this exists today. Oh, no, there is no filtering of any kind. And so, you know, say, you kill 100 million. You want to use a lawsuit? I almost can't keep a straight face. Well, this is not my view, but it is President Trump's view. It is David Saks's view to some degree. It's Jensen Huang's view. And so that's why I'm putting you in conversation with it because it is the governing view of the United States of America at this moment. No, it's fair to say that outside of the industry, the awareness of the danger that

17:46the dangers of AI is extremely low. And you can say that of academia. You can say that of think tanks. You can say that of policymakers, politicians. And part of the reason that, you know, I'm speaking so loudly as loud as I can is that you can't rely on the industry to self-regulate here. I mean, it's just insane. The only question my mind is, do we wait until cyber attack causes massive damage and a biotech causes massive damage? And then the monitoring safeguards are required in these models to minimize the chance of that happening many, many more times. Or can we be wise enough to put these things in and require these things to be put in before millions of deaths? The two things that have been worrying me most as I'm tracking what is appearing from people in the labs is one of the view that the systems are becoming less modernable as

18:52it becomes smarter. Open AI has said this about astro-6 and people inside open AI have been raising the alarm that the systems seem to know when they're being tested. There's more situational awareness. And so the testing environment is no longer as indicative necessarily of what they will do. So that's one. Second is that all the labs are moving as quickly as they can towards recursive self-improvement where you have the AI code or moving not just from speeding up the engineer, but really taking over the coding, right? And so you can create a much faster iteration loop with much less human input than you have now. So when I think about those two things, and when I think about what I'm hearing from people, my confidence that we have the monitoring, the auditing, the testing capabilities we are going to need is low. I'm curious where yours is. Well, so you're not focusing on the whole problem there. I'm surely not. The fact that at some point, the AI system itself may do something that's against our

19:58interests. That is absolutely a risk. And the symptoms we've seen through aspects of hugging, facing other problems point out that the way we do the reinforcement learning today, the fact that we don't have a supervised relayer that is some absolutes like we didn't, you're not supposed to take over other computers, you're not supposed to break out into the internet. The control problem is a serious problem, but the imminent risk is not RSI. And the imminent risk is these are the most powerful tools ever. And unlike every other dangerous technology, they were not funded by government IR&D. And the government is not a significant purchaser of these products. It's not like rockets or nuclear weapons. And so the idea that the government, including the US government that would have traditionally been the most technically sophisticated, other than a little bit of attack capability

21:01in NSA, really doesn't see how dangerous these things are. That is a unique circumstance. So what does that imply? If you're more worried in the near term about what human beings do with AI, then loss of AI control, then what does that imply of what your first steps need to be? There is no supervised relayer today. That supervised relayer is needed urgently to prevent bad people from using today's AI's to shut down economies or kill millions of people. These models, the ability to separate out making molecules for good and making them for evil, that is so hard to distinguish, you know, the anthropic released mythos and fable where they had turned the filters up so high that you can literally ask questions about cancer. And you know, next thing you know, you're down at Opus and then Sonnet and then, you know, Hikou is the only AI willing to help you.

22:04And you know, so it's over tuned. And anybody wants to do serious work, either has to get a special permission copy or go use something where there are absolutely no safeguards at all, which includes some of the open source models. And there are humans who for bad reasons will be able to use these models. And so unless we put in safeguards of monitoring and require that in all models, then we're just going to have some gigantic events of that type. And then finally, we'll respond. Sadly, you will obliterate AI capabilities, go off in dark places, even beyond today's capabilities, which that is a gigantic mistake. So you just wrote this essay on AI risk and it does represent if you have a big jump in how alarmed you sound, right? I was reading some of your past pieces. One in July of 2023 was titled the Risks of AI are real but manageable. And here you're, I think, at a different level of threat.

23:05So I take from what you're telling me that what happened here is just watching the advance in bio capabilities and cyber capabilities and coding capabilities, etc. Is that fair? No, the key thing is we always said when we cross these thresholds, we will engage all of society because we will have created the most dangerous thing ever. This makes nuclear weapons look like nothing. We said we would engage and we cross those thresholds and there was complete silence. There were discussions about who in the industry says X or who in the industry says Y. But what percentage of academia or think tanks are, so it's the complete lack of response. I would love a world where the response on these things is very strong and then whatever time or voice I have will go back to let's eradicate polio, let's stop children dying under five. But it's the combination of having crossed every dangerous threshold without a doubt and

24:12a complete lack of engagement outside of the industry. Well, it doesn't feel to me that we're so disengaged. This, I mean, as somebody who covers politics, every politician I know is talking about this. There's bills being proposed. You know, Donald Trump, say what you will. Not that have to do with these risks. Well, say what you owe about Trump and then they're engaged. They just believe we should move forward. But I mean, they're a little bit all over the place. One point there, you know, withdrawing access to things like mythos and fable at another point. They're saying we have to win the air race with China. But what I mostly see happening is a lot of engagement. When I talk to the people and I bring similar concerns to what you have, they say the most important thing is that we win the race with China. Secondarily, many of the people with a lot of influence say the most important thing is we don't restrict access to open source models. You know, you're going to need wide dispersion of them. And so the cost of regulation, the cost of the kinds of closing down of access, it's simply too high. The technology is still underformed.

25:14That we're sort of just trapped in this dynamic and the best thing to do is to just move through it. It's not so much that they feel disengaged to me as they feel that they've come to a different conclusion. So they don't mind bioterism. I think you've talked to Donald Trump more in the past couple of years than I have. But the last time I talked to him in December, this was not the big issue. We hadn't crossed the thresholds and we hadn't seen this. The necessary step is people couldn't talk about whether slowing down is good or not. But putting in the safeguards and the monitoring will not meaningfully slow things down. And the only effect that has on open source is that you can still be free. You can still be customized. But you have to stay on a platform where the sovereign can make sure you have not removed

26:17the monitoring and other safeguards. And so what is the downside? The downside is staying on a monitored platform. Now the get out of jail free card that people play here is that means the Chinese will win. I don't know what it means win. Nobody's, the US can't win over China and China can't win over the US. We both have open Pandora's box. It's there. Therefore, people with malintent to go and use it. So you'd think we'd move up from that nationalistic view to kind of a humanity level view about how we engage in these protections. And the notion that China wouldn't want to engage in that on behalf of humanity, I disagree. And it's a proposition to be tested. If you can take models that make dangerous molecules and move them into a dark corner

27:20where you get rid of all the monitoring, then we're just giving up to a biotech. Likewise for cyber, if you can remove that ability to find and exploit security problems, which are rife, then in the next few years, you will have major, major cyber and bio events. And that's avoidable through safeguards and monitoring. 33 presidents. I called the president of natural authority in the morning and he answered seven decades in space. We want to see what's beyond the next star. A thousand consumer product guides. Today I am testing seven mattresses. 60 Super Sun days. They reprived the best team in the league every single year. 53,500 puzzles. I use a different starting word every day. 25,000 recipes. And I love a one-can recipe because I don't love washing pans.

28:22The New York Times. Celebrating 175 years of helping you understand the world and make the most of each day. Subscribe now for a special offer at nytimes.com slash subscribe. There is a talk about AI will take jobs from people. I know a lot of people debating this. Who say no the jobs are too messy. There was a prediction we'd have no more radiologists. We still have radiologists. AI can code but we still have coders and strong demand for coders. Tell me about why you think AI will take jobs away from human beings at a significant scale. Yeah, so there's no doubt to date. AI has created more jobs than it's destroyed. The demand for the skill sets even just to build the data centers is very, very high. We have a, you know, a reasonably low unemployment rate.

29:25The superiority of these systems is subject to a threshold where you have to believe that it's incredibly reliable. If you're going to have your tele-sales or tele-support capability be AI driven, you want to make sure that its accuracy is better than humans. The only profession we've truly crossed over that threshold is coding. Even there, I know a lot of people who are stuck in the past and don't want to use the AI for coding, but managers of coders get that most applications can be developed very inexpensively. We will, in the next few years, cross over those thresholds for accounting, legal work, tele-sales, tele-support, where 24 hours a day in every language with infinite trivia capability and no urgency.

30:26So you look at the AI nurse and their several companies. They have perfect memory. They don't hurry to get up. It'd be like a nurse you would call on the phone or talk through a chat interface. Far preference. You go to San Francisco and ask people, do you rather ride in a way more or rather ride with the human driver? Go ask people in the UK who use limbic for mental health support. So the notion that just the market demand preference for driving or the nurse or even the person on the phone will favor humans, that's a quality threshold which will be passed through. If say insurance companies are still doing human-strew claims, medical claims, which is a very AI-capable task, then a competitor who has very few human employees will come in and change the pricing model for that industry.

31:27So the two counter arguments I've heard people make on this. One is that you have a Jevons Paradox effect, where the cheaper, more widespread availability of this kind of intelligence leads to a massive increase in the demand for this kind of thing. So yes, you have many more AI chatbot nurses and that leads to more people being sent to the hospital, being sent to the doctor where real nurses take care of them, where you have many more AI coders. So maybe my small podcast team, which would have been a software engineer before, now has one because it's like they run a team of coders and we can build products we never thought of before. This is the most common answer I hear to this. Yes, AI will destroy jobs. Yes, it is making a human-provided resource much cheaper. But because it's going to expand the demand so much, it will sort of work itself out, create jobs in other areas, create new demand. And this is how past technologies have gone. And so we shouldn't worry too much about this. How do you see that? Well, Jevons is just a referral to the fact that parts of the economy are subject to

32:32demand elasticity. And yes, in the case of software, if you're say three times as fast and there is still some role that only humans can perform, then as you lower the cost, you induce demand. And so it's fair to say that the equilibrium today for software is not a loss of employment. When you invent radial tires that last four times as long, for some weird reason, people didn't drive four times as much. And factories that make tires employ a quarter as many people. When you replace people in Amazon warehouses with robots, people don't buy more because of that. So, you know, anybody who's numeric can save to themselves. What portion of the economy is subject to demand elasticity? And what are those tasks that will still be human necessary? As soon as you've complete the entire task, it doesn't matter that there's demand elasticity. That goes into the token budget.

33:33It doesn't go into the human-sourced budget. The cost for some of these things is so much less than the cost of the human labor. And so, the as you cross reliability thresholds, both with white collar and human eye robots, you destroy jobs. And you leave no high ground. That's, you know, innovation in the past. You have a tractor fine. You know, let's build Disneyland and employ a lot of people there. You don't have that in the broad economy. You know, people who say they'll be net additional jobs. I don't understand what they're thinking. They must not understand the piece of improvement wrong that, you know, the reliability you wrote a column, I think was in May that I looked at like, what? What? You disagree with it, my column. What is this unique humanist thing that you think, you know, in every category where AI has come along, the preference for the AI is very, very strong.

34:36Well, so that column was based on so, Jevin's paradox. And then the other, which is an argument from Alex I miss, what I believe is now one of the labs is an economist is that you will have this sort of explosion in the relational sector. That one thing that happens when people get wealthier and you'd probably know about this is that they also didn't get a lot more human help, right? They have personal trainers and chefs and there's a lot more, no, I don't know. I see a lot more people around you. Royalty, Royalty used to have a lot of human help. You had upstairs downstairs, you know, all those maids and people and used to have a human who helped you get dressed. Believe me, the labor intensity of wealth is down super dramatic. From what it used to be. So you know, Jevin's paradox, name a blue collar profession that's subject to gemnoth paradox. I do care about blue collar. I do care about blue collar. So the question is you. Anything in the blue collar realm. So I think the subject to that. So I'm not, I don't have the strongest view on this, but here's I think the argument that I would make or that I've heard made is that if you look at something like manufacturing,

35:36we've not had a Jevin's paradox in manufacturing employment in America, right? We exploded how much we actually create, but a lot of the jobs went offshore. Some of the jobs went to automation, but we don't have less total employment in America than we did in 1960. And the reason is people moved into service sector jobs that the composition of jobs across the economy changed. Yeah. Human cognition became the scarce element. Yes. Yes, it's always about scarce elements. Right. Once you replace human cognition as a scarce element, in fact, you blow it away in terms of working 24 hours a day, reading more, knowing every language, there is no scarcity that you're moving up. So you feel there is no scarcity that will be left for human. There is no scarcity. Alex would say it's something like relational sector jobs, but you don't believe there are no. What are some of the current jobs? You mean like my relationship with the cab driver or my relationship with that nurse where I'd rather have Hippocratic AI call me? I think the question here is actually, do you end up preferring Hippocratic AI or do you actually want your therapist to be a human being because after a little while there's

36:39something thin about telling your problems to a computer? Well, the market, you can gather market data if that's at all interesting. You know, I suppose telling the 55 year old truck driver, you're going to go do some relational thing. You have a program for that? I don't have a program for it. And I think the question you actually run into very quickly is speed of transition, even if you believed some of this. And I said this in the column two, that I don't see how you will handle the speed of transition, that our actual experience with fast transition of jobs is that people lost their jobs lose out. Now you might over the entire economy, it doesn't look that different, but say the China shock did lead to a lot of ruined communities. So your answer to this, and it leads to a very concrete idea for you, which is that we should tax the use of AI. Why and how? Well, let's say workers pay in on a page to go basis into the pension, so security fund,

37:41so active workers are supporting retired workers. If you let go of a worker and hire a robot to do that job, why are you so inciting the trade off against the human labor that you don't ask the robot to also pay into the pension fund? What is it, is that the pro robot union has gotten the tax laws to say no, if you're not flesh, then let pensions go bankrupt, which they're on a path to do even without robot replacement. So how would we do that? You say you define a unit of labor and say independent of whether that's delivered by a human or robot, you are paying the same BICA tax that a human worker would pay. Now that loan's not enough, but why should we be so favorable to taking away that job? The current tax structures very much as though people who have capital are what really counts

38:45and labor is the most disadvantaged input to the economy. Nobody gets to decide just because the economic signals say that it'd be lower cost to use an AI doesn't mean society has to do that. The other one you propose is human reserve jobs. Tell me what you mean by that. So there's a question particularly as you get the impacts on the blue collar stuff, which that's very sharp because when the humanoid robots pass a certain threshold, they are very general purpose. But the idea here is that you would decide in advance that things like childcare or elder care or some portion of medical care, some portion of education, although you could have some AI enhancement that you would maintain the employment and call those things human reserved. I found this vision not totally unconvincing but chilling.

39:47I think the way you put it in the piece was that this feels a little bit to you like nature reserves, places where we could put buildings and roads, but we choose not to because the loss would be so great. And I think it gets to this question that a lot of people have that on one out of every two days I have, which is if this is what it looks like, why do it? The Gates Foundation announced on Monday a five year goal for an estimated 3.4 billion people who speak languages currently underrepresented in today's AI models to be able to use AI tools in their own language and voice. And if we are looking at this sort of job, apocalypse, this level of risk, then it's like to have that on the one hand and then on the other hand, like our goal is for more people to use AI, tell me why. The, there are many good things that AI does and that's almost all of the foundation's work is in taking what the market would not do, which is take AI to the poorest in the

40:48world and help them with education and health and agriculture. So if you have a woman saying Nigeria who speaks Uruba, she's in a remote community, there's no doctor there. So when she says she's bleeding, AI doesn't get that right. We're spoiled. We speak English. The thing that Uruba is 10 times worse than is English, which is significantly the best. There's about 10 other languages that are fairly close. So the empowerment for that woman to be able to talk about her medical problem and get a bite advice in the middle of the night just by having a smartphone with the data connection. That's what we're trying to enable. Okay, but I get that. It's just the picture you just painted of the job apocalypse as bad as it might be here. And it will be bad. We do have a fair amount of money. We have the AI companies. We can tax the eye companies, put that into redistribution.

41:50But is this not going to wipe out the ladder of mobility, the ladder of development for a lot of these countries? I mean, doesn't this make AI a tremendous economic threat if you're the Philippines? You're saying that are allowing the eye and understand Uruban to help that woman who's bleeding? I'm saying why is it a bad thing? I'm saying that AI sounds in this telling like a bad thing that the net net, like yes, you're supporting the world's languages. How can I be a bad thing? But I think you understand what I'm saying. No, I did the job. I'm pushing you're putting forward a great scale to accelerate the good stuff AI does. And I'm trying to minimize. What do we do about jobs in the global South? Well, treating the global South like one uniform thing doesn't allow you to have any picture of what it's like to live there. There are middle income countries like China, Brazil, Vietnam, Indonesia, where their

42:53economies are growing, and their childhood death rate is within a factor of three of the West. Then there are low income countries where 15 times as many children die before the age of five, and you don't have doctors. You live your entire life. You never meet a doctor. You try to figure out what seeds to plant. You never have anybody advise you what to do. And so, you know, we need a little more nuance in low income countries. The AI will overwhelmingly be a good thing. And it should be pushed forward as quickly as you can. So, your argument in some ways actually it's a better trade for low income countries that it has more benefit maybe than it does here. Absolutely. The human basics we're not meeting today. If these people lived on your street, you would open your wallet. You'd be outraged. I mean, these kids are dying. These kids are malnourished. So, the inequity is allowed to exist because of the distance. AI is a tool for good in terms of helping those people in, by far, the greatest need

43:56with very basic human problems. Do you think it has as much effect on the job markets in some of the poorer countries that we're talking about? Not in the same time frame. No. But over time? Well, if you're talking, see, you're probably spend more time in middle income countries than in low income countries. I do. So, your image is like Philippines, India, and all of those. Yes. In countries, they will see the jobs effect after the rich countries. And then eventually, even the low income countries. But I guess this gets to the broad engagement question. I don't have a good crystal ball. This, I find the range of outcomes terrifyingly wide. This range, it seems to run from massive material abundance and elimination of want to, actually, doesn't change all that much to human extinction. It's a pretty wide range of outcomes to consider. But I hear you saying to me, and you should tell me if I'm getting part of your position wrong here, what I hear you saying to me, you know, convincingly and forcefully, is it

44:57the AI job apocalypse is a very real thing that mass displacement of workers with no real answer to that is a very real thing. When you talk about broad societal engagement, I think most Americans, most people in most places, if they heard that and they were convinced of it, right? And polls show most people think AI is going to take jobs and not create them. But they would say, actually, just stop. Right? If what you are going to do is make it unclear how me or my family or my children or my friends will have a job, say in America, like, please just don't. Like let's just stop for now. And so you actually seem to me to have a stronger negative perspective on the jobs question. And a lot of people I talk to, even in the labs, you're shaking your head. I do talk to people. I'm not, I'm not coming from nowhere on this. And definitely than a lot of the economists I talk to. So for whom then is AI a good trade if you believe the job effect is going to be so ruinous for most people? That's funny. When I was telling this to the person who some people considered the lead economist looking

46:01at AI, he said, how can mechanical Turks still exist? How am I going to run that if AI is as good as you said? And I said, it won't. A week later, it was completely shut down. And yes, the suffusion of knowledge from, you have to say, isn't it pretty stunning that the more you know, the more concerned you are, you know, take Dario. Dario spoke out about job impacts. Now he's a bit more guarded. Hinton, I agree, went too far and he said, okay, it's coming tomorrow that there'll be less radiologists. And of course, there are more today. So we have some of that taking place and we have the analogies with the past where people are saying, well, this is like the PC, not like evolutionary history. This is like evolutionary history. This is like the aliens really are here and you know, have come. They didn't have to spacecraft. They were created in laboratories.

47:03But that's the kind of thing we're dealing with. If we retain control, then eventually you do get not to overuse the word that you've used. You do get to this super abundance period. And there you have deep, almost philosophical, religious issues that you don't have the shortages that we've organized society around, you know, why you should learn and how you find purpose. Then you have deep, philosophical, religious problems, but you do not have dyne of malaria, don't have enough food, don't have access to a doctor problems. And so if we get to that, a younger generation will figure out, okay, how do we live, how do we spend time? That's a very different world than the way we have today. I think what this generation has to do is make sure we get through that with humanity still in control.

48:05And with the disruption, the number of bioterror events or the number of people whose lives are damaged by job loss, we need to minimize that over what's probably a 20 year plus transition period. So what when, when you say, because this is something you say at the beginning of that essay, that this could be, and I'm paraphrasing, the most powerful driver of inequality or of equality, where what, what are the highest leverage for you? Good things that can come out of this. I can imagine somebody listening to our conversation, you're thinking, why the hell would we do this with this set of risks? Yeah, that's where the timing thing is troubling. You know, whichever definition of bunion sure using, you want to say, oh, my health bill was less than I expected. Oh, I was buying a new house and it was less than I expected. I was renting and they seem to be lowering the rent. You know, my electricity bill was less. That would be nice. But AI, you know, because of the efficiency and invention that comes with it, that's,

49:13you know, what over the 20 year period, you do get kind of mind blowing advances in things that people can relate to, the cost of their food, shelter, education. Because those are highly regulated areas, so the good stuff, if we're not careful, arrives more slowly than the biopsycho-social risk and the jobs risk. Those things in the next five years are very significant. And so people will decide, although, you know, it's hard for a single country to check out, people will decide whether to slow down, stop, get rid of AI. And, you know, yes, it will have political difficulties. Stopping data centers isn't going to slow this thing one I owed us. So anybody who's against data centers because they think I'll slow down AI, that's a waste of effort. Now, the data centers are going to get built somewhere.

50:14So the broad view of the technology that has to be expressed in some other form. I want to get it something you're saying here because something that I've thought about too, which is that there are a lot of rate limiters, a lot of weak links in the chain. When you try to take, even in an optimistic view, AI advances that then have to be built in the material world, right? You have an acceleration of, you know, good candidates for pharmaceutical development, but you still need to find rats to test on monkeys to test on human trials, you have slow regulatory agencies, et cetera. And then you have this tremendous acceleration of intelligence that is, for lack of a better term, native to the digital world and is acting there in a kind of constant way. And you, I mean, right now you see this, right? You can accelerate AI with very little regulatory overhang, but you cannot get, you know, the open AI parking lot covered in solar panels without permits and hearings. And so I think you have a very high chance of getting into a very weird,

51:16both like economic and social world, where the digital world is spinning into this other thing. But most of the things human beings need ultimately come out physically, like we need shelter and we need food and we need, you know, all this. And they run through institutions. And so a lot of the ways it could actually make our lives better are sort of limited by normal human factors, but a lot of the ways it could make them worse or weirder or not. Well, we definitely need to look at the things that slow down the good stuff. And so for example, because the Gates Foundation's an on-profit, we can work with regulators on how they use AI to do their job. And, you know, whether it's organoids or biological models, we can speed up that regulatory piece. And there's some countries that are very much engaged in that type of acceleration. The one application that's going full speed ahead and kind of amazed me is the agricultural one

52:20because they're getting better weathertated to these farmers in Africa. You know, we have over a million farmers in India already using the system. So it tells them what crop disease they have, what fertilizer to use, what varieties to plant. We've even put a bunch of services they can take advantage of on there. That one is going full speed ahead. The health and education, you could say, you know, will it be the rich countries, the middle income countries or the low income countries, and they get there first because some of the barriers are different. For the low income countries, it's not regulatory. It's, you know, is anybody providing the tokens? Do they have the smartphone and the connectivity, which are the basics and the language thing that we've talked about? So they'll proceed at different paces. Ideally, we'll learn from each other. I mean, China actually banned young people having social relationships with AI. You know, do they know something? We don't know.

53:20You know, can we look at outcomes of different experiments? So there's going to have to be a lot of that learning. But you're right. If the benefits aren't coming quickly, then the permission to operate, particularly if we don't put on the safeguards for the cyber attacks or the bioattacks, this is going to be a very tough issue to stick up for. Hey, I'm Max Brown. You know, the athletic is home to the world's best sports journalism. But this fall, just in time for football season, we're launching something unlike anything we've ever done. We're building the daily show, Stream and Live on YouTube. Me, Kofi Yoboa, Charles McDonald, and the Athletic Zone, Zach Harper, and Daniel Popper. We'll be hosting live watch-alongs of the biggest games with award-winning analysis and behind-the-scenes insights from athletic insiders.

54:23On off days, we'll go deeper into the hard-hitting stories you can't get enough of. And we want you, the smartest fans in sports, to be part of it. Come drop questions in the chat and we'll bring the answers straight from the source. The Athletic Live presented by Google Gemini. Follow us on YouTube and we'll see you in the chat. When I was preparing for this episode and telling people I was interviewing you, one of the big, space of skepticism people now have is around what they've heard with you and Jeffery Epstein. So I've looked at your house testimony. But what do you say to people who have lost some faith at you and just see you differently just now linking your name and his? You know, they should read what I said to Congress. I got to answer all the questions. I, in trying to raise money for global health, thought that Epstein could connect me because of his relationship with them.

55:28And I had me to deal with him. With billionaires. But you're a Billy. I mean, you're the billionaire on some of them giving all my money away. And I, I spend a lot of time trying to raise money for, for global health. And so you felt that he had connections that would be of value to you in that. To raise money for global health. Yes. That's, that's what that, I mean, you did you read it? I did read it. That's all we, that's what we met about. I mean, other than, okay, there was a dinner with Larry Summers, where we talked about the economy. The whole discussion was, is there a chance here to help out? It's many time with them, you know, it was clearly a mistake. I've changed my bar for even somebody in a non-paid intermediate role. I'll never take any risk on that again, because our work is, is very reputation sensitive. The whole at the center of that story for me is how this guy was so compelling. There's so many very smart, very wealthy people.

56:29I mean, there are a lot of people who want your attention and don't get it. People want Larry Summers attention and don't get it. That there's something about Epstein's charisma or the way he presented himself, the true people into at least thinking he could be very useful to them. What was that? What, like I've read his emails, he does not seem like a pleasant person to email with. What was the kind of factor about him that allowed him to weave this web that you and so many other people were in? Well, I wasn't in a web. I was in discussions about raising money for global health. I didn't go to any island or meet any women anyway. Don't call it a web. The, how he performed the bootstrap of owning the fanciest house I've ever seen in New York City and having Larry Summers and the number two guy JP Morgan there. So that was an interesting dinner even if Jeffrey and Heather said a word.

57:30I don't know how that bootstrap took place. But there were lots of billionaires that he was involved in the moment where you kind of decide, okay, what am I doing with my wealth? How do I minimize taxes? What do I do with my family, that type of thing? And so, you know, that's, I don't think anybody else was drawn in for that reason. My, in a case, is kind of a unique case in that he said, oh, you'll have more money than you'll know what to do with. And eventually insisted that he take me around to see billionaires. He had me meet with five, turned out none of them had a near-term intent. And I ended the relationship with him within a month of that. And so the thing he was able to do, because that's interesting to me, is like, even for you to walk into the house, it was that fancy that people around it gave him credibility. And so that he was able to put on a show such that what he was able to offer was of value.

58:36There was all this kind of social capital and wealth flowing around. Some people socialized with him. I did not. Other than to my surprise after dinner, magician coming in David Blaine, I didn't spend really one minute socializing with them. He offered, you know, come to the island or, you know, come to some show in Paris and I said, I would not choose to do that. That would not be a good idea. So then, I want to widen back out to the Gates Foundation. You say you're going to spend down its money, $200 billion by 2045. Given everything we've talked about here with AI, how is your vision for how that's spending plays out changed? I mean, there's two dramatic things that have happened. One is the incredible AI capabilities, which continues to be an exponential. And the second is the reduction in overall generosity towards the poorest in the world. So I have one piece of enablement, which is we'll discover drugs faster, we'll discover

59:40new seeds faster, and that we can talk to those farmers and get them to buy the right seed or talk to the person living with HIV and help them seek the care they need. So AI can be a big enabler for our goals, including malaria eradication, polar eradication, spreading childhood death and hampagin. But now, the amount of resources available is way less than a golden rule view of the world would suggest it should be. There is from the Foundation's Connected Danthropic and Open AI, the sense of an amount of nonprofit money coming online in the next couple of years that will dwarf any moment in philanthropy before it. And no people in that world, the sense of this being something very unusual is very present. Is that change what's possible here? Be numeric. Take the cuts and overseas. I'm not saying it answers the cuts and overseas.

1:00:42We save lives for a thousand dollars per year. And so getting less money from philanthropist net doesn't save those lives. The amount of money to save lives at a thousand dollars per life saved will be dramatically less. So when I've looked at the way your foundation is spending on AI and tell me if I have this wrong, it's about 40% education, 40% health, 10% agriculture and 10% institutions to have that. I mean, it's a little more in agriculture. Almost nothing we do because we're like a pharmaceutical company and venting new drugs. And do you call that AI or not calling that AI? We didn't put any of that in our billion dollar commitment we announced. We just put in AI specific things like understanding African languages. So tell me a bit about your views on AI and education. This is a place where I've seen a lot of studies now and they have very, very mixed results

1:01:42depending on how they're used. So where do you think it is valuable and where is it at risk? So the contrast between the ambitious goals that the Gates Foundation set near 2000 are goals for global health and our goals for education. In global health, we thought, wow, African governments, traditional beliefs, are we going to have any impact at all? Much to my surprise, our work on global health, together with we create with others, the global alliance for vaccines, we create the global fund, present bush does pep are, you know, a ton of things happen, including primarily vaccines, rotavirus, pneumococcus. And we can't child the death more than in half from over 10 million year to under 5 million years. So we more than exceed any goal we would have set for the field in global health. In education, we thought we could just go see what really great teachers do, videotape

1:02:47that, understand it, create a feedback system for teachers to hear that, improve their practice, you know, constantly learning on that, and that we could make education a lot better. As you've just seen from the latest numbers, kids are learning less today in most rich countries, including the United States, then they learned 10 years ago, 20 years ago. So people start appropriately with a very high degree of step. If people go to, yeah, tell me why you think that those numbers have been very, very striking. Why do you think that is? Why are we seeing learning loss in rich countries? Now I think it's, you got to have a, not you, but one has to have a broader answer than the pandemic. Oh, it's definitely, we are post pandemic and people debate is it the use of cell phones, is it, you know, something to do with the affluence overall? There are some outliers.

1:03:47England actually is counter trend and they went back to basics in terms of how they teach reading as well. And so, you know, high expectations is winning out over just, you know, free form creativity. But you know, there was a, there's something clearly large in those statistics. It's, it's very concerning. And so you can almost say, why do we continue to do educational education is key. I'm stubborn. We've got AI now. And we have people where the AI is playing a very specific role of each student at the end of the day. This is here in New York City classrooms where they're using a curriculum called KIDM spends less than 10 minutes answering a few questions. And then the teachers given right away a sense of okay, which concepts of the kids struggling

1:04:49with, which ones are struggling with them? How might you, you organize the classroom? The data on that, which is small scale, are, you know, one of these stunning results that make you want to really scale it up. When you scale up an education, you go from the teachers who willingly engage in experiments and are probably self-selected for flexibility to the broad population. And so the number of things in education that look good in the small that either don't affect it when you scale up or the quality of implementation degrades so much that the effect is basically washed out. That's the history of education innovation. I do think is AI helps you with motivation. Many of these software tools have helped motivated students, but actually created more of a differential. It's a kid like myself who went home and used Khan Academy for two hours at night.

1:05:53And it's the median kid who comes in and sees, wow, he's just so much better. That's discouraging. That's probably hurts. So unless you believe in trickle down or something, this is not equity at work. Can the AI not only to personalize learning but personalize motivation overcome that? And I really believe that we can get that right. Well, there's a question here of AI tools that are specifically designed for this. And then a question in the way we were just talking about with cell phones and smartphones and social media and of how AI will diffuse through society. And I think the big concern here and what I have as well is this, but now it gets called cognitive offloading that what AI is being used for in mass numbers by students and being really quickly adopted for is I didn't do the reading summarized for me. Or I have to write this essay drafted for me or like help me on these math problems. And even I think where we saw a big study out of China that was striking to me where you

1:06:57saw kids using AI had increases on their homework scores. And then when they had to test outside of that context, their test scores began falling pretty sharply. And so certainly one can imagine AI programs a little bit good here. But in terms of a technology and a way of interacting with the world diffusing through society, well, of course, I could help people learn linear algebra, whatever it might be. Then in practice, what it's going to do is people will be using it to help them. And both from a student level and up through a professional level, beginning to degrade the learning, the creativity that happens with the hard work of drafting and struggling and challenging yourself. Yeah, it will you clearly would get by modality where a student can use AI to be lazy and corrupt the measurement system or a student can use AI to help them learn more.

1:07:58I have to say in terms of my learning about subjects, this is the best time of my life. I mean, I take you two videos and put them into the chat. I have AI's talk with each other. What an urban. I always had the ability to send mail to somebody like Nathan Mirvoldo knows physics. Well now I discuss the physics thing with the AI. I get to it. And then if it's super important decision like I'm going to invest a billion dollars, I'll send it to Nathan and say, could you look this over? 24 hours a day, keeping up to date on the latest malaria thing or vaccine thing. So that by modality is going to be there. And it really does go back to this motivational part of it. Is that a place where there should be more limits on the systems? I mean, you mentioned a few minutes ago, China, which for all we talk about being possible for us to strike a deal with them, China currently has stronger national level regulations on AI than we do, including things like on social companionship for kids.

1:09:03One of the places that you talk about in the essay where maybe we want to be more aggressive is around children. And that's a place where I think it is reasonable for the government to be paternalistic. We should be paternalistic. And social media always feels like an experiment we ran on kids. A lot of the internet does. I don't so much mind us running the experiment on adults, but I wonder if we want to be more aggressive in what we don't let kids do with AI until we have a better sense of how it affects them. Everything from learning relationships to trying to make it harder to have AI help you cheat on your homework. Yeah, I don't think a black and white band is necessary because I do think with monitoring, which I'm kind of broken record on that, that making sure it's staying within the bounds

1:10:03of what's appropriate, what the parent wants, our capabilities, they are very strong. There are many systems that try to help instead of telling you the answer, they engage with you on how do you reason through the problem. And so then the question is, can you make sure the student isn't going to those outside systems and just getting the answer instead they're engaged in the system that brings them along step by step in that reasoning process so that they'll be more capable the next time. And so yes, the scene what that student is doing and deciding, okay, do you call in a psychiatrist, do you call in the parents. A lot of these systems, the idea of monitoring will be very important. And at different ages, the visibility of the parent about what's going on and how time is being spent at say some very young age, a parent probably should have complete visibility

1:11:09into the exact dialogue that the students engaged in. As the child gets older, are there things about sexual identity or things that that really, it's beneficial for that to at some level be private or not. I think there's a lot of tuning to go on with this. One of the partners, the foundations working with this common sense media who did a very good job on this TV show or this movie what it exposed you to is a much tougher area. Most of these systems that have been set up with the plan for control, the parents lack technical sophistication is such that it doesn't really matter that you tried to engage the parent nothing happens. In my case, I didn't know that my daughter had a second cell phone. It was a fairly straightforward way that she, in late hours, was able to stay on social

1:12:14networking when I hope that she would be sleeping. We have to be realistic about how these things are designed. People will worry about the privacy issues there. That's fine. I believe we can make them. It's not an argument for being unmonetored in terms of what your kid is doing. Next two years and politically, you have the mid-term coming up, then you'll have a presidential election in 2028. If this were to go not just in terms of passing laws the way you wanted to, but because you sort of center your call on this coming together of society to discuss debate, respond, what are you actually envisioning here? I'd have two metrics. One is the obvious safeguards to minimize the cyber-embiorec. The second would be the nature of the dialogue. If the dialogue ends up being one party is 4AI and the other parties against, then we'll have climate change, which is not a great place to be.

1:13:20You don't have room for debate when you only have the two extremes. The default case, at least right moment, seems to be very little middle ground about how we should manage AI. Let's say that a very different administration and a very different composition of political power exists in 2029. There's interest in rebuilding American foreign aid. What would your advice be on how to build it back? It's effective. The American people understand what they're getting for, that's spending, and so it's actually doing good. Yeah. If you ask the American people what portion of the budget is going to help people in poor countries, it's generally more than 5%. People say 10, 15%. The fact that it was a half a percent, and now it's going down towards a quarter of a percent, that would be pretty shocking to people.

1:14:24Understanding that the money is well spent, that it really does save millions of lives, that made every bit of difference in terms of HIV and malaria and TB and maternal survival. They should hear what they should be proud of, that even at that half a percent level, and a moral argument will be made, it'll be made in the face of an overall debt level that will be very tough. Whatever safety network needs to be done because of AI impacts, that will be competing for those dollars. Then I always have a question. What if you book, you'd recommend to the audience? Well, when I literally binge this weekend was the correspondent by Virginia Evans, that's fiction, very touching, very upbeat. I propose what we just discussed. There's one called Into the Woodshipper by Nicholas Enrich, which talks about how somebody

1:15:27didn't go to a party one weekend and they decided instead to put USAID into the woodshipper. About a month ago, I read The Infinity Machine by Sebastian Malibi. AI book. Yeah, a history of Deimos Asebus and DeepMind, but you get a sense of the whole founding of the AI industry, does an incredible job. Bill Gates, thank you very much. Thank you.