Alex Imas and Phil Trammell – What remains scarce after AGI?

Today, I'm chatting with Alex Emas, who is Director of AGI Economics at Google DeepMind and Professor of Economics at University of Chicago and Phil Tramble, who is Head of Economics at EFOC and Research Scholar at Stanford. In general, in this interview, what I want to understand is what economics tells us about what we can expect in the world with more and more automation, more and more advanced AI, what that tells us about what will happen to wages, to labor share, what the best way to tax and redistribute the wealth that we generated as a result of AGI will be, and what kinds of things will be scarce because what a scarce kind of tells you where the value will accrue. So I want to start there. What are some plausible candidates of what will be scarce? Something like the relational sector, which is what I defined as, you know, basically services and goods where the fact that the human was in the loop was actually part of the value of that product. So because humans are naturally scarce, if we have automation where a lot of other things stop being scarce, we will still have scarcity and things that humans are kind of involved in in the loop for. I'm curious to understand whether humans doing services for other humans can never be a big part of the economy, and here's maybe one intuition pump. So in a world where AI can physically do anything humans can do, you know, there's this whole machine economy where they're like building factories and doing research and coming up with new ideas and humans may or may not be involved in the physical production of those things, but probably not, given that in the ultimate limit if robotics is solved. If you don't care about humans being involved in that process, why would humans be involved in that process? But then there's these other things, which you point out, well, we actually maybe in some cases do want the ballerina or the barista or whatever to be a human that's part of the value of going to a cafe or performance. But only humans have that preference. So there's this human economy where like humans are doing services for each other, and part of their wealth is flowing to other humans, but part of their wealth is also like they will want some of the automated goods that's like machine only economy is creating, and so part of that wealth is flowing out. And so if you just think of this as like this is not a closed loop, but a lot of things that the machine only economy are closed loop because the machines don't care about like getting the human barista to make them a coffee. And so within that model, isn't it intrinsic that like the human only economy will become a smaller, smaller share? I would like to pitch kind of a rephrasing of that question. So I think my view is that kind of forecast that economists like us would make are not necessarily as individual forecasts like me and Phil are talking right now are not necessarily very useful. The reason I think that so there was this blog post by Andre Fredkin, Brian DeBerry, and then Andrew Coe that came out yesterday, actually, that looked at like kind of people's forecasts, economists forecasts about the labor market. And what they found is that there's a ton of disagreement like in every single direction. So what they advocate for and I think I'm an agreement here is rather than thinking about individual forecasts like what me and Phil are going to do rather looking at kind of like basically generating prediction markets where you get aggregate forecasts where you get like kind of wisdom of the crowd effects. And kind of the reason that I think this is because we have been famously terrible at forecasting. And so let's let's take let's go all the way back to 1820. This sort of debate that we've been having actually is like 200 years old. So David Ricardo is one of the classic economists, not new classical classical economists. And he when industrial revolution started happening, he was wrote a bunch of stuff saying like look this is going to be great for everybody prices are going to come down. But then he turned around and he's like wait, I can actually see all of these jobs that are creating value. They're going to be automated by these machines. This is going to be really bad that everybody's going to become unemployed. And there's going to be political unrest and things like that. And if you look at Ricardo's predictions, they're actually right. If you look at all those jobs that made money in Ricardo's time, they got automated. So if I was David Ricardo and I woke up and somebody told me all those jobs did get automated. And you asked me, David Ricardo, like what do you think the prime age employment rate is in 2026? I think he would be surprised if you told him it was the highest that's ever been other than 2000. We have the highest number of employed people that could potentially be employed since 2000. That was like the peak and now it's like the second peak basically. So what David Ricardo ended up missing is the fact that essentially you have these economics of structural change where basically everything that got automated became cheap. People had more money to spend on things and then they started spending money on services. And this is kind of like the lump of labor fallacy. That's what they call it. They Ricardo didn't think, hey, I should have considered the fact that new jobs would be created. But it's kind of not obvious that money would go to services. Why wouldn't they go to more automated goods or something like that? And I'm not saying that like I'm not using this anecdote as to say like this is what's going to happen now. We're going to have full employment. I'm using that anecdote as to say it's really hard to make predictions. And what I think maybe a really useful tool that economists have is instead start with the premise like maybe we'll start it today. Look, labor share is zero. Like labor share has gone down. What could possibly explain this? Let's write down an economic model of what happened. Phil will talk about this later today. Or you can start right down a model to say, hey, what if labor share just stays the same? What can make that happen? And here's my me. If you don't take anything out of this conversation for me, we don't have any data. I've been kind of saying we need a Manhattan project for data. We don't have data on basically consumer demand elasticity. We don't know what they are. We don't know. We're not really tracking what jobs are getting created or destroyed like the own at database with all of the tasks and different jobs. That's been rarely updated at super low quality. And so what I think is really useful is to think about like what are the potential scenarios and we'll be talking about a lot of these scenarios, mapping them out and to say what dimension of scarcity will generate that scenario. So if there's full employment, we could talk about the relational sector or something like that. If there's very labor share collapses, we can talk about other sorts of scenarios. And then that will tell us what data we should be collecting. It's probably worth the defining labor sharing capital share real quick. So the whole economy, like the total sum of goods and services sold, is either paid out to people in wages or it's paid out to capital, which is to say that there's like rents on buildings and then there's shareholders of companies that we get paid out and for many hundreds of years in the economy, 60 something percent of the economy or all the things that are sold in a given year basically gets paid out to humans and wages and the other 30, 40 percent gets paid out to people who own machines and land and claims on companies and whatever. And the question is, well right now 60 percent is going to wages. Does that shrink as automation or as EIs gets smarter and smarter and better and better? And it's like it really, this is a called or a fact like right? So it's incredibly, we should stress this. It's incredibly surprising that it's over 60 percent after the investor revolution, after all of the automation we've ever seen, the fact that it's almost like some people are worried it's an accounting error or something like that that it's kept being been so constant. And the fact that it's like been over 60 percent. And you know, there's there's even a controversy right now. So some might say like, you know, labor share has been falling in the last 20, 30 years, but you know, depending on how you there's been a lot of accounting changes in the last 30, 40 years. So for example, Andy Atkinson has this paper showing that actually if you keep the accounting constant over the years, labor share hasn't even fallen ever. But it's not, it's not that surprising, right? I mean, for you made this point that if labor and capital are compliments, you need both to do anything. It kind of makes sense that you kind of need to pay both of them to get something done. You have had stuff can be completely automated. Although you had the post where you were pointing out that actually, sorry, oh yeah, well, it's going to say there's a sense in which nothing's yet been completely automated. If you look at the network adjusted factor shares of a good, which is to say you look down the supply chain and say, not just like the final step. How much of that is done by capital and labor, but what went into the machines that can automate that final step. You'll find that labor's adding a lot of value down the supply chain. So like, you know, a computer and electronic products in the U.S. have a very stable capital share network adjusted capital share of around 50 percent. So I do think there's this qualitative shift that we, I think we agree is coming, which is that there will be at least some goods whose network adjusted capital share goes to work, right? Because the whole supply chain can be automated and there's no partner that we care intrinsically about having a human do. So that'll be, you know, that'll be a qualitative shift. Interestingly, the implications of that shift for the overall capital share are ambiguous because if we, let's say that we've got the two sectors, the human intrinsic sector with the ballerinas and everything else, right? Right now, everything else has been scarce because of the lack of labor in it, right? But if we fully automate the supply chains for everything else, right? And we satiate and everything else really fast, then the quantity of everything that's not a ballerina, say, goes to infinity, but are the marginal utility and that stuff goes to zero faster than the quantity's rising? Yeah. I also kind of want to move, if you don't mind, move away from the ballerina example, because I think like the kind of point that I was trying to make in my post, again, and the point of the post was like to work backwards from a particular scenario, was that, kind of the ballerina and the kind of performer, that's the wrong reference class. Right now we have a lot of jobs where you have different tasks, so this is the task-based model of jobs where you have like a lot of different tasks, so like a doctor, what is their job? They're filling out insurance documents, they're going and like calling different pharmaceutical companies. And one of their tasks is to actually see the patient and talk to them, but that's like actually not the main part of the job. So you could have a job and a service are a good, be a product of different types of tasks and you can automate a ton of those tasks. And if the consumer's willing to pay more for a product or service, where every single task is automated, versus every single thing except for that one part, where the doctor's actually delivering the diagnosis, providing support and things like that, we would call that job a part of the relational sector, right? Because a human is, people are willing to pay more for the human to stay in the loop in the job, right? So I think we don't have data to say, like here are relational jobs here or not, because you literally need to collect data of the following sort. Do a conjoined analysis of like here's my willingness to pay for this service, this good, here's the counterfactual, everything is pursued to spy machine, here's the counterfactual where this one task is not produced. What is your willingness to pay? What is your elasticity? For that, for the human to not be in the loop. And like literally if I don't have that data, what prediction am I gonna make in this story, right? - Right, but I guess isn't there another point, which is that there's a lot of fully automated goods that don't even exist yet. And you can't collect any data right now about, say how much people will want to keep buying more and more of some drug that makes you healthier. - Absolutely. - That's fully produced by DEI's. - And that that's kind of Phil's point, right? And you can make it is that look, you know, you could have an increase in variety and capital where you don't get the satiation, right? So you're increasing varieties, so you're not hitting that really diminishing marginal utility point where you're, you know, you're basically most of your income is going to the human sector. If that increasing variety is fast enough and there is no such increasing variety in the human sector, then you can get all of the relational that you want, but it doesn't matter for labor shift. It goes to zero. Phil, I like your analogy to some Mongolian economist sitting around 1400, thinking about what will be scarce and the limits of that kind of analysis. I think you should talk to that. - Sure, yeah. So if you just looked at the goods available to, you know, a Mongolian of the distant past, no expert on this society, but I know that they didn't have nearly the variety that we have now, and they looked at the jobs that were sort of intrinsically human, like being a singer, say, and they looked at the things that were not intrinsically human, like, you know, the transportation services provided by their horses or the different kinds of food they had. If they just kind of help the varieties fixed in both categories and ask what will happen once we have a lot more automation, they might have said, well, we'll just satiate in, you know, horse-like transportation and in yogurt and in yurts, those shares will all go to zero and we'll be left spending all of our money on singers. But of course, that's not what's happened because as we've accumulated more wealth and, you know, more advanced machines and so on, we've expanded the range of things other than singers to spend our money on and the share spent on singers that stayed sort of negligible. So likewise, that sort of my central prediction about how future unfolds though, it could go either way. - I was gonna make a point and I realized it's a fallacy, but the reason it's a fallacy is interesting. So I was gonna say, I mean, it's just hard to imagine a world where there's trillions upon trillions of robots, but there's only some billion out of humans. And then like the cumulative amount we're spending on robots and like building more robots and whatever is less than what we're spending to like pay, you know, Magnus Carlson and-- - Or financial advisors or doctors or tutors-- - Or podcasters or whatever. - Or podcasters. - But then I realized that it's a fallacy. The number of transistors in the world has like literally, certainly trillions X, maybe quadrillion X or something. And your colleague, Chad Jones, has a very interesting result about how the share of the economy that is going towards paying for computing basically like paying for the transistors has been decreasing. The point that you made is that one way to think about Moore's law, you know, what sets price? Well, the price is a supply and demand. And so not only are we producing more transistors more cheaply, but also we're like the value of the marginal transistors decreasing, right? So as you were saying, another way of saying Moore's law is-- - Sure, you should say-- - Yeah, I like the pessimistic framing of Moore's law is every 18 months, the value of computation has, right? Like we're just running out of uses for computation so fast that it's sustaining Moore's law. - And this is in fact like literally relevant to a conversation about AI, where maybe for the first time, this is no longer true, right? So the famous fact here is that in age 100 costs more to rent now than it did three years ago. Even though we have much superior technology and we have much more compute in the world because as models get smarter, the opportunity cost of compute gets higher. - But this is Phil's point about increasing variety, right? What we have done is increased the types of things that people demand from capital. Now all of a sudden you have a new variety that you could be using capital for and all of a sudden you jump back up. - Yeah, you could imagine we just never satiate demand for compute and as long as that stays the case, then the share of the economy that is going towards compute would keep increasing. - And that's the big question, right? It's like that is the ultimate question that we need to be kind of looking at is like, what number of new uses are we figure finding for that commute where you have the demand for these uses? So what I kind of want to emphasize is that a lot of models in economics, especially in this space that we're talking about, take demand is almost kind of exogenous and they don't unpack like what is the psychology of what people actually want. And so what got me kind of also thinking about this the idea of the relational sector's work that I was doing on the fact that there does seem to be this value, this intrinsic value that is, it's not just because it's scarce, it's because there's some intrinsic preference that people have for like empathy and connection and getting interacting with another person. So like one of the experiments that we ran was like, there's an art print, right? And we actually have an incentive compatible way of like basically saying like, how much are you willing to pay for this art print? People actually paying a real money for it. And then we say like, look, there's only one, one of those art prints and it's either made and these are between subject conditions by AI or by a person. So with one, you get the effect that the person produced art print is valued much, much higher than the AI version. And that what we do is to say there's in a set of other conditions, there's 500 of these being produced. So for the human made one, the price goes down a lot because it's no longer seen as like, you're not like making a connection with this one artist versus with AI, there's no difference. AI is already viewed as like a commodity. And you know, we need to do a lot more research on this but it seems like that's kind of like the key difference between you know, something like let's say a horse, right? There's no, a horse was an input into an output where you can replace the horse with something else. You only care about the output. The only way this relational story works and this is what we need more data on is if it's not a human is not a horse in the sense that it is providing value from the output where if you replace the human, the value of the output decurses. And if that's not strong enough and if it doesn't hold for enough sectors, if it doesn't hold for enough jobs, then this kind of story doesn't work anymore. - There aren't that many institutions that have thought as hard as James Fury and would have turned smart people into some of the most confident researchers and engineers in the world. This relies in part on an apprenticeship model where new hires are paired with senior mentors. But James Fury also runs a bunch of classroom style lectures and hands-on boot camps. These courses cover a range of topics and they go pretty deep. There's one lecture that focuses on reverse engineering systems with tools like S-Trace and GDB and another that teaches you how to profile code down to the cache hierarchy level. Importantly, James Fury designs these courses not just to teach the relevant object level skills, but also to impart the relevant task and knowledge. For example, their week-long neural net boot camp starts with general theory but then quickly progresses to how to apply neural net works to trading. And here they cover the specific obstacles that James Streeters tend to encounter and the work around they've come up with to get around them. James Fury takes this sort of learning incredibly seriously. Every office has dedicated classroom space and courses are prioritized as part of regular work. If you'd like to work at a place like this, James Street is hiring. You can check out their open roles at JaneStreet.com/Dorkesh. - There's one possibility which Molly Condor has written something about this messy middle scenario and that possibility made me think about whether it might be better to have at least as far as wealth distribution and redistribution goes. It might be better to have much faster AI take off. And I want to ask you whether the following possibility is at all likely. Or there's any set of assumptions that this can make it so, which is that AI makes it possible to automate jobs such that like many people are losing their jobs, but it doesn't create enough wealth while the process of automation is happening to pay off basically the people who are getting laid off such as there's like a pro-do improvement. Everybody's getting better as a result of AI automation. And of course, there's a trivial sense in which that must be true, because whatever money you're saving, whatever money the company is saving by not paying the humans instead of just paying the AI's, those resources still exist in the economy and they can just be paid off to people. But there's gonna be some allocative inefficiency, like the government doesn't know exactly who got laid off because of AI. There's some political problem of like if the meta worker gets laid off first and they're making 200K a year. Is there a politically sustainable situation where you give them a 200K check a year when there's many people who are working who are making much less? - So, do you at all find this inero plausible where AI is actually automating a bunch of things, but there isn't enough wealth creation as there is automation? - I think it's, is that plausible? - Possibly, to me, it does seem like a pretty narrow window. My guess is that if we have the technology to automate so many jobs, it becomes like a new kind of political problem and the pipeline will all speak growing really fast. - Well, in all of those professions that it's automating, it's just a hair more productive. So like the cost of all the capital to replace all the software engineers is just a hair less than the cost of what we can think is off-engineering. - And why is it implausible that it's just like a company can save money by laying off a bunch of software engineers? But in the long run, there's a chevon's paradox thing and we can't participate in advance what we do with more software and surely there's gonna be more uses. But in the short run, the fact is just that a lot of people are laid off and they still need to figure out how they can use a million X more. - I think the thing that is in either Phyllis, Phil and I have been writing about these things and we have mathematical models in the back of these things. We don't have any political economy in any of our models. Andy Hall wrote a really nice blog post about the politics of AGI and he made a really interesting observation. If there's a 2% increase in unemployment, the political winds completely change. Like unemployment, it has a huge effect on what happens politically. So Tamali's excellent essay, by the way. I think in some ways, one of the worst scenarios is a drip scenario because of the political economy piece. Because people, essentially what you might see is people not really being unemployed in mass but kind of moving into sectors that pay them less money, kind of basically getting what happened with phone operators in the mid-century, between 1920 and 1940, phone operators were completely automated, right? But it took 20 years, even though it's a technology existed. And therefore there was this drip. It wasn't like this giant sector just disappeared. And when it ended up happening, there's a really nice QJ paper on this, basically showing that they got reabsorbed into the economy but at lower salaries and they were mostly under employed. And I think that's the scenario that Tamali was writing about this kind of messy middle where things aren't a disaster because we saw with COVID, the fiscal response can move quickly if there's an emergency. And an emergency is a quick uptick in unemployment which could even look like two or three percent. That's like a national, that becomes a national emergency if it becomes fast. The concern is that suppose whatever you're saving on those white collar workers, if that's not growing the economy but it's just creating some saved resources that can be allocated elsewhere, is that enough to do a broad-based redistribution scheme? 'Cause then you have like the money you've saved up a couple of people. Yeah. And unless you can figure out exactly how to get into them specifically, you have the problem of can I do like, can I do a UBI off the money I saved by basically? Yeah, so you're basically saying like look, the pie did not grow that much. You're just basically, you're just basically displacing a bunch of people, but that actually didn't grow the technological frontier of what the economy can produce. And so then there's a question of like, well maybe every, I don't know if this is a case, maybe every time this has happened in history, the technological frontier has expanded a bunch and so. I think that's the case. I think simply in history, the technological frontier has expanded. So it's kind of, I think Philip made the same point. Like it's hard to imagine that sort of scenario where you are getting like intelligence that's kind of just enough to replace the software engineer, but still costs a lot of money. Like it's just a hair less, less expense of the software engineer. So you're not getting this abundance effect. Right. And so where is the redistribution going to happen because the pie didn't grow? Yeah, yeah. Okay, so this is very helpful. So there's a, many different things out of each year for the scenario to come to pass, each of which seem unlikely. One, it has to be the case that it is possible to automate entire white collar jobs, but only in a piecemeal way that is to say that you can only automate software engineers, but that same program can't also automate an accountant and an analyst and whatever, where I think at least my model of intelligence is such that both of like the breadth of task that requires to do something like software engineering and what intelligence is is such that, you know, if you can really just like lay off all the software engineers, you've got enough in the bucket there that you could like automate all kinds of white collar work. So yeah, you're saving, there's huge amounts of potential savings that have happened as a result of these layoffs. And also that AI is going to be cheaper than human labor. And if both of those things are true, this mess middle scenario, where we literally don't have the wealth to go around, seems unlikely and the question is like, what is the best way to tax it and redistribute it? Yeah, I have some thoughts. I think it's just really important to outline the costs and benefits. Like it's also important to know that they're so first, there's differential complexity and like implementing these things. To they differ in the timeline of like being actually helpful. So like something like universal basic capital, that's not like that's not gonna generate returns for something that happens in six months. So you probably are going to end up with a layer of things. So like for example, like a negative income tax. Like you implement it. And the day it turns into law that is already, you already have this sort of insurance that like, you know, there's a floor for which, you know, everybody gets a certain amount of money. And then, you know, if you earn more money, you get tax more and things like that. And, but, you know, there's positives and negatives to negative income tax. With UBI, the, for example, the, I worry a lot about like the political economy implications. Like for example, like if people are just kind of dependent on a check, it really matters who's in power. Like right now we're in doubt with labor that can turn into, that can turn into income when that is no longer the case. And we are now at the mercy of the, of the elected official for like basic needs, right? So that to me feels like a power sharing arrangement that's really dangerous. - But wouldn't that be true of any sort of government redistribution program? - So something like university, basic capital where you have like an ownership share and you have property rights for capital, then you just, you're just, you're normal. - You're just a normal person. - But this goes back to the question of indexing, because if indexing is hard, then universal basic capital is hard. - And that's the, that's the problem of universal basic capital is targeting, right? What do you target to put into people's portfolios? - Like what if inthropy goes to zero but some random robotics company takes all the success? - Exactly, so that's the risk of universal basic capital. With the negative income tax, you have the same sort of issues with UBI, where like, you know, somebody comes into power and says like, this is, we're not gonna do that anymore and people can't work. And then, you know, you have the issue of the floor being there. - What you're concerned with the world tax is that, you know, there's no political, it says politically sustainable equilibrium at like 0.5% world tax. And, you know, I mean, this happened with the income tax supports, right? You'd start slow, it's like four war or something and then it slowly and slowly escalates until the marginal tax rate in the US is probably on the order of income tax rate is like 40% or something. And in certain states, upwards of 50%. With a capital tax, is there a reason to worry? Would that distort investment because people would just be like, why would I invest in anthropic rental? The government's just gonna take larger and larger shares of it and dilute my share. - Well, hold on, so I think it's worth separating like how the revenue is raised, like what's tax and then how it's distributed. It could be that the government hands out shares of anthropomorphic to everyone. But by fraud, they tax and then buying anthropic. - Yeah, okay, great. - Which would probably be the right thing to do. I mean, hopefully some like populist proposal doesn't interfere with that and like expropriate some like particular company that everyone happens to know about. - Well, so you're suggesting there could be a tax that is some sort of optimal tax. It's retaxing externalities or retaxing land or we're, I guess, we probably need to tax something other than just those two things. But that tax-- - Work consumption? - Okay, so a consumption tax, like a European value out of tax type thing, that allows the government to go buy a bunch of stocks. And then they just distribute those stocks to everybody. - That's David Otters. - Yeah, I mean, that's not gonna be that different from just like redistributing the stocks, but it'll be a little different. - Yeah. - That's what social, that was the proposal for Social Security by the way. That was privatizing Social Security, right? So it's like you turn this sort of weird, not weird, but it's been working, it's worked so far, but there's questions for how long it's gonna keep working. Like basically privatizing Social Security was giving everybody about-- basket of stocks. Right. All right. I'm curious to understand people talk about whether there's a white color apocalypse already. Is there any evidence that suggests that there is mass automation or unemployment as a result of AI already? I think there's a lot of people are looking at it. So this is an area where there's like a lot of eyes and a lot of data being produced. So the budget lab over Yale is doing really good analysis on this. They just recently released a report. And I think like you really have to squint to see anything happening. Like basically if you want to take kind of like a approach across the entire economy and looking at even looking at like software engineering, like the most exposed sort of sectors, there's just like not really anything going on. There might be a little bit of a signal about like junior developers getting jobs less than before. Rather than a level shift as then there's actually an increased demand for senior manager for senior software engineers if anything. And so if you look at trend, it's kind of like for junior managers, it's a bit below trend. So as in you're seeing the growth is slower than before. Yes. But there is still growth even on entry-level software engineers. Yeah, exactly. And what do you think is going on with the anecdotal evidence of graduating college students saying that they're finding it harder to find CS jobs or something? I think that's anecdotal evidence. You think it's always been hard to get jobs for some people and now it's getting turned into an AI narrative. Same with the layoffs where it's probably just normal layoff and they turned into an AI layoff. Yeah. I mean, you have to be careful with all of this. I think like there are these like there are these like coordinate public coordination devices for like let's say we get into an narrative where like if you're a firm and you're not laying people off, then you're seen as like not adapting AI enough. So like then you're going to just get a cascade effect. Right. A firm's like just needing to keep up with the Jones in terms of like starting to lay people off. And that's kind of like that's super worrying. We're like actually the firm might be actually worse off after the layoffs than before the layoffs. But it's just doing the layoffs to have the perception that look look we're not behind the times where we're where you know using AI like you have the you probably heard these anecdotal stories of like these token counters that like you have to maximize tokens and things like that. Again, like right now we have we don't really have any evidence of a way colored blood belt. And is that surprising at all? I feel given the fact all these things they asked me to do is just like this is a story is all this time. If you automate some complimentary task, the overall bucket of things that the the human labor which compliments the automation. Yeah. We'll increase in value. So this is one of the statistics that's really important for that argument is elasticity of demand. Yeah. You take the O-ring model of jobs. So like again, jobs is a series of tasks. Let's say the AI automates like nine out of ten, a nine out of ten tasks. One task is not automated. If that person can now kind of focus in on that task connect that the job will become more productive. If that translates into a price effect where the product is actually cheaper. If the demand responds enough or loud there's it's being bought more it's being used more the service is being used more that could actually lead to more higher right. And a lot of people on the internet have been like kind of making that argument kind of very generally saying like look we're seeing if anything in the data we're seeing an uptick in software engineering. Right. Yeah. Which suggests that at least for now, given the way the jobs work, it might be less. But I think this elasticity demand argument is incredibly important both for for a lot of arguments that people make or just a lot of labels that people use without understanding what the underlying causation is. So people often talk about Geven's paradox. Yeah. This is this idea that as something gets cheaper, you will want so much more of it that the total amount you spend on the thing increases. And so famously this happened to call in Britain 200 odd years ago. But really this only happens if there's the demand for something is highly lasting. There's many things where there is not super elastic demand if oil, for example, gets super cheap. It's not like magically, right? Yeah, exactly. Uh, magically there's going to be so many more cars that now we're going to be using way more oil than before. It's not in the short run. Exactly. So long right now elasticity is higher than short run elasticity. But even the long run, so agriculture, famously is an example where we can produce way more food if we dedicated the same portion of the economy that we dedicated to agriculture. We're already producing more food regardless, but we could produce even more food if the same portion of the economy that was producing food a hundred years ago was currently producing food. Um, but you know, you eat enough and then you're done. And so the claim with software is that it is a, it is not some inherent property of markets that as it gets cheaper, you'll just keep wanting more of it. Absolutely not. It is the thing about software is this is the particular kind of good, whereas it gets cheaper. We'll want more and more. But it is also highly relevant and you are messy about this. A lot of this, a lot of this podcast is me summarizing your assays back to you that there's this very viral scenario planning about the future of a, uh, citrini where they're predicting as a result of automation, as a result of very powerful AI, there will be a recession because white collar workers will get automated. There are salaries, which we're, you know, paying for a bunch of things will no longer be available. And so there will be a slump. Do I want to recapitulate why this might be implausible? Well, I mean, so part of it is plausible, part of it's not, not plausible. So like the, the part that's kind of like within the, this is something that we started the conversation with is the idea that there could be unemployment. A lot of unemployment is if the speed of automation is quick and things like that, people could get laid off and they may not find work very, uh, uh, very quickly. So that part of the centrini essay about the unemployment, you know, we, we can quibble about that. But that's, that's not the issue. The issue is that they talked about negative economic growth, right? And so what I did in the, in the piece that actually Phil and I had a back and forth on was to say like, let's start with the, with the proposition that there's negative economic growth. What conditions do you need on the economy to get negative economic growth? And it turns out the conditions are pretty in problem. So one thing that you need is like for, uh, the, the holders of capital, like rich people basically, like basically what you have in this, in those sorts of scenarios, like you have a reallocation of wealth and income from, like lower income people who are working who are using their label towards head capital owners. So what you need is that basically demand to be bounded, like a hard bound, not even like a soft sort of like diminishing sensitivity. You need for them to eventually say, I've had enough. I don't want to spend any more money and for that money to not enter his investment, right? Right. Which is, and then you can get negative growth, which is like, and the crucial thing is even if we don't want more shit, the world in which there's a singularity and we don't want to invest more money is crazy, right? Where we're not like, let's build more data centers, let's build more fabs. Even though we have AGI, we're not like investing in more data centers to run the AGI. Yeah. And that's like driving more economic growth. Yeah. And so I sent the essay to Phil and Phil actually wrote back being like, this is pretty dumb. Yeah. Like my essay, say, like you're trying to say that there's going to be negative economic growth. These are very implausible conditions and I was like, actually, that's the point of the essay. These are very implausible economic conditions. So that's where I think like scenario planning really shines is you have the centrenia essay, which I think is like, I think it was great that it's written because it kind of started a conversation. But it's just like, you, it's so intuitive this idea that like, look, if there's demand collapse, we can get the economy to shrink, but it's actually, you could get that with the depression, right, where in the depression, the technological frontier didn't expand. Right. Here, the technological frontier is expanding. You actually have abundance and for abundance to generate negative economic growth. That's really hard to get. Right. Exactly. Google recently announced Gemini Omni and its video editing capabilities are incredible. You can upload a video and then tell Omni to do things like change the background or adjust the lighting or add or remove elements. All while keeping everything else consistent, but Omni is in just a video editor. I got a chance to sit down with the research and product team behind Omni and I learned that it's a preview of how future frontier models will be trained. It can take in any kind of it, but whether that's text or audio or video and while it doesn't currently do so, architecturally, it's capable of just a seamlessly outputting images or text. So it's really a bet on the multimodal data transfer hypothesis. The model becomes better at predicting one data type by seeing the others. For example, Omni is really good at accurately rendering text on video, even though Google didn't specifically target that capability in this model. And Omni is the next step towards more accurate world models. Because in order to predict the next frame of a video, you have to have a deep understanding of physics and spatial dynamics. As Omni progresses, it'll be interesting to see whether it can close a sim to real gap. Because it's much harder to collect data in the world than it is in simulation, robotics progress has lagged other applications of AI. But if you have really good video models, they can simulate reality. Only that stops being the case. In the meantime, if you want to try Omni, you can check it out in the Gemini app at Gemini.google or use it in Google's AI Creative Studio flow at Flow.google. We're talking a second about why there isn't more automation as a result of our elements. And one plausible mechanism could be that, as you're saying with the O-ring, O-ring theory refers to this fact that the challenger shuttle blew up because there's one component that malfunctions and it destroyed the whole thing. And maybe that's a more general model of how goods are producing the economy that you've got to make sure everything is reliable and works well, and you can't automate entire job to an AI right now. Even though it might be able to perform it at some probability, you need extreme reliability In order for it to not destroy the they finish good. I think this is, yeah, this might explain why there's less automation now than there are the rights could be, but I think it works in the other direction once AI's get advanced enough that integrating humans into the production flow of future goods, even beyond the arguments about how humans will be more expensive or dumber or whatever, even beyond that, just there will be whole production flows that are organized for AI labor, where they're talking ignorantly, they're thinking many thousands of times faster. So even if there's some comparative advantage where it makes sense to hire a human, there will be like transaction cost and more is of a reliability that will actually make it hard to integrate humans into future production flows. Yeah, that seems right to me. In particular, I just wanted to distinguish between the point that if you automate like nine tenths of the job, then people might kind of shift over to the last tenth, but like there might be ten times more work demanded of them from the model of owing automation from like Gans and Goldfarb recently, which was that if you can only automate nine tenths of the job, but you can do it to a lower standard of quality than the human could do it, you might not want to automate even those nine tenths. And that's the thing that could totally port over to like symmetrically, it could be a reason why we don't use a human for one path of the job anymore, because a human just can't perform it to the level of quality that the AI can form the other parts of the job or the level of speed or whatever. And they end up pulling down the quality or speed of the finished product. By the way, the model you're talking about seems extremely plausible to me of why more lawyers or accountants or whatever are not automated. Like there are cases and or even software engineers where there's a pretty good probability that the thing worked as you expect, but the thing you're paying the lawyer for is like, no, really, my company's not going to go under because you're also paying for a lot of like regulation stuff, right? So like with lawyers, particularly you need some entity to back up the product. You need kind of like an ownership of the product. You need somebody to be able to fire or hire licensing issues. There's a lot of like sort of like regulatory layers that are like also going to be keeping even if there's no relational element human in the loop that have nothing to do with like the ability of the human to actually perform the service. Yeah, I mean, you know, all of these frictions on the political type decisions that we are accustomed to only trusting human, you know, only having humans for like legislation and being a judge, being a jury or all the licensing that keeps certain professions human. That all strikes me as transitional, right? I mean, what we expect to come from a human and like how we organize our politics, that's changed so many times throughout history, right? From little hunter-gatherer bands to empires of whatnot. And yeah, once an AI run political system is much more efficient than the alternatives, then those will probably tend to compete the others. So speaking of which, we've been talking about what preferences humans currently have and what impact that has on what kinds of goods will be scarce in the future. But of course, we'll have different kinds of entities in the future, AI's, right? There's a time when there were no humans on the earth, but evolution selected for agents that have specific drives and preferences because those tend to survive the most and those preferences now basically determine how a $100 trillion world economy what it produces. And so why not expect the same thing of AI's in the future? This is not even a world with catastrophic misalignment that is to say they just kill everybody, but there will be evolution of even if not individual AI's than firms, which have AI's as part of them. And what will that evolution favor where it will be favor probably firms or agents that grow, right? This is like a selection argument that things which grow will be more prevalent. And maybe just based on that, you can make some predictions about what their preferences will be. But it is the kind of entity which prefers to have human intrinsic goods going to be the kind of entity that accumulates resources the most probably not, right? Probably it like saves more. It like has unsatisfiable demand for things like whatever the relevant resource happens to be compute is an obvious one. And can we use that to make some prediction about the non-human preferences that will be guiding the future? Yeah, so I think if there's like an AI that's like has its own welfare and it's fully autonomous and it's like making its own decisions that are wealthy relevant, to be honest, I have absolutely no prior that it would like at all prefer other to like deal with humans. There's no reason. But let's but let me take like the other side of that argument will humans preferences to be interacting with one another and to trust and empathize and all of these sorts of like things with other humans versus a simulated AI? I think it's a really important question whether those will change, right? So I've heard a lot of arguments saying like look, you know, right now we're just not used to the technology. And at some point like what you're thinking of relational or something like that, people are just going to see like an AI therapist as a superior product and they're not going to need the sort of like empathy or whatever that the human is providing. I think this is actually a really complicated question. Here's one argument for why it's not going to go away and that that has to do with evolution. So let's say there's two types of people. One person doesn't really have this preference. They can just interact with other AI, whatever can simulate better. The other one has almost like a like a moral emotion like from the using Jonathan Heights framework, moral emotion against interact like offloading those sorts of social interactions to an AI, which of those two people are going to reproduce, find a mate, all of these sorts of things. I think the answer is kind of clear, right? It's the second one that has the preference for other people. That's how the reproduction is happening. Fair. But if we're in, you know, the world where like reproduction is still happening the way that it's happening, I think, and this is a big question. I'm not even like, I'm not making a prediction again. I'm just saying like, if we're thinking, you know, do you have David Reich on the show, like his point on the last podcast was that, you know, we're buzzing with natural selection. Right. So even if like you get some sort of indifference now, you might get selection to point into like an even stronger preference for all humans. Here's one way to think about it. How is the wealth of the richest people in the world instantiated? Of course, they can, as you were hiring a call earlier and you're getting the point that their consumption is more geared towards relational goods, like Mark Zuckerberg is hiring MMA instructors and dancers for his wife's birthday and so forth. But most of his wealth is just stock and meta. And he has a controlling shareholder could say, Hey, meta, just give me all this income or turn all this wealth into dividend income. And I will just spend on a consumption. But instead, he rather would have his wealth compound and meta to build more data centers, basically. So you don't even have to change humans for this to be the case. It is just the case that the humans which are wealthiest and are growing wealthier because their wealth is compounding. Just have this like almost Nick Landian preference for like accelerating capital. And that does seem to suggest that, yeah, is that an important determinant of what kinds of things are produced in the future? Yeah, I could kind of just say like, there's two ways you could get the two kinds of people, one of whom prefers a human therapist and one of whom is fine interacting with the AI. If they both satiate equally quickly in capital, right? But the one who likes the human therapist just also likes having some human intrinsic services. And the marginal value, like how the marginal value of capital in the future, for comparison to the marginal value capital today for each of them, they start out equally rich, should be basically the same. I mean, there could be interactions and whatnot, but basically that should be the same. If what's driving the difference is that one person just doesn't satiate in capital because they're engaged by the prospect of, you know, exploring universe and returning their head into a galaxy brain or whatever. And the other one satiates. Yeah. Then the person who doesn't satiate in capital is going to have, if they're being actually going to have a higher savings rate. Yeah. Okay. So in the long run, they're going to have most of the well. And the overall capital share will basically be the capital share of that person's betting, which is going to be one. It's important that this is, we're not talking about a hypothetical future. Yeah. Like Elon Musk is talking about mass drivers on the moon. Right. And he's like, by far the wealthiest person in the world. I mean, obviously, currently his investments are going towards humans as well as machines. But I don't think he cares, particularly, that is like future researchers and engineers are humans versus. And he managed to reproduce fast as well. So, yes. So anyway, so I just think it's worth drawing that distinction. Yeah. There are currently some rich people that don't seem to satiate quickly in capital. And so maybe in the long run, they'll save the most. Right. Yeah. That does seem sort of right to me. And I would just also say, even if they do reproduce more slowly, like biologically, that might just not matter that much the long, right? If they can live forever and, you know, the living forever is key. Yeah. Right. So I think, I think, again, like, and we're scenario building here. Right. So I think if you could live forever, like a lot of stuff changes for my story as well. I think it's to your point about, you know, rich people just consuming not consuming a lot and investing, I think this will all depend on the returns to capital, right? So like right now, the returns to data centers are super hot, right? But if we get into a situation where people are satiated with capital, then the returns to accumulating capital are going to be lower. And so then these rich people are going to be consuming more, right? So because they were the incentive to invest is smaller. So basically, you kind of think about this in general equilibrium, the general equilibrium of this sort of process, like we have gotten tremendously more richer since, you know, 1820. We've gotten many more people are investing. But you're still getting a consumption response, which keeps, you know, people employed in labor share high. And that's because-- Wait, it's not necessarily. I think you're probably making the same point. But I mean, they could just, it could be that they're investing, it has to be chitrated through actual laborers. But to go like do things where they're investing to work, which like would not, in the future, only the consumption is human mediated, right? Because the investment can just be done by the robots. But if the returns are, if you, so we're in the scenario with, with like how you can keep high labor, right? Let's take that scenario. In the scenario with high labor share, for whatever reason, the returns to capital are going to be lower. Yeah, that's right. And I mean, to the earlier thing, we're in the messy middle, we're saying why this is implausible. I feel like we can do a similar thing here. Where four of returns to capital to be lower, the growth rate has to have be lower, right? I mean, it certainly has to be lower than what we're expecting through the period of transformative AI. You know, if there's explosive growth. Yeah, yes and no. I mean, so the capital stock could grow quickly, but the price of capital goods relative to consumption goods could be falling fast, and the capital stock is growing. Oh, interesting. Yeah. It's the difference between like the potential frontier of technology and like what the realized prices of these things, because you have relative prices. That's really important. So you're saying I could be putting my money towards, you know, earning 30% interest in investing in data centers, or whatever, there'll be something in the future growth rate is high that earns higher returns. Or I could, as a result of all the technological breakthroughs or some cool product that I really want to buy right now, and both of those will be compelling options. Yeah, it doesn't have to be a new product. It could be a human intrinsic product. Right. Although, if it's a human intrinsic product, we would want to have it much more in the future than we want it now, because the sort of the thing it compares against is, so we might want it, the same as we want it now in the sense that like the marginal utility in a ballerina performance is exactly the same as now, right? But the marginal utility in a robot might just be a lot lower than now, right? So in units of robots, we wanted a lot more than we want it now, right? So with the interest rate be 30%, it depends what you mean by the real interest rate, okay? It might be that every robot now can turn into, you know, 100 robots next year, right? So in units of robots, the interest rate is 10,000%. Right. But if the price of robots is falling really fast, prices adjust. I mean, that's the whole, I think that's the whole point, is that? Yeah, but here, price, they're adjusting this interesting way that too many macro models don't allow for, right? So what's happening is what would be called investment-specific technical change? Where, yeah, the price of capital is like falling relative to the price of consumption. Instead of like the standard doing the standard macro thing of saying it's just output, it's like kind of a thing called output, which is one for one can be allocated to capital or consumption, right? That's not going to be true in this world. Every unit of capital next year is giving up weightless consumption. They need a unit of capital this year because like the just one robot now turns into many robots next year, but, but the number of values is the same. And again, we're going to go back to the increasing varieties thing where like if all of those extra robots next year are actually different varieties of robots that I'm not getting satiated on those robots, then it's a very different, different story. Yeah, right. But now we're talking about the consumption world, whereas for the investment side of things, there could be just some greedy Titan of industry who keeps wanting more and more robots. And that alone would be enough to increase the marginal value of robots and therefore decreased labor share. Yes. Yeah. Okay. But why are we not expecting greedy Titans of industry to keep existing? I mean, greedy Titans of industry historically have like built libraries. But that's because they die. And they're like, they all die. Everybody dies. Well, we'll see. But I mean, like conditional on people dying, I think like, you know, his like, again, you had a guest on the show who said, like, you know, to understand the future, you should think about the past. And I think like I you could have new types of Titans being born, who's where they're entire reason for accumulating wealth is just to accumulate wealth. Yeah. But a lot of the time, you know, at least historically, I'm just talking about historically, the wealth accumulation process is part of a large social sort of like social interaction amongst peers amongst the community where you want to be admired in some way or something like that. So then people end up like the stylized fact of Titans of his of industry is like, you accumulate the capital. And then you like buy a bunch of stuff. Yeah. I mean, I guess it's sort of a historical question. But it does seem to me in a lot of cases, what is happening is that as a near the end of their life, they either hand it off to their children who are worse stewards of capital than they are. And they don't even manage to grow their wealth at the rate the economy grows much less fast than the economy grows, which their parents are doing. And also, they're like, well, I care less about my children having it than me sort of playing this game of accumulating wealth. And so I'm just going to give it to some trust. And if people are living longer or if they can figure out some way in which to align their trust to this wealth accumulation process, it just feels like the evolution here is so strong where you just need a couple of agents that think this way for this to be the dominant thing determining the preferences of the whole economy, because this part is growing much faster than the other parts of the economy. I think you just like the part about satiation and diminishing marginal utilities, I think it keeps coming up, but I think it's really, really important. Like, you know, if a person has an intrinsic preference for accumulation, that's just like that's what they want. I think your story is totally right. But that's just like not how usually preferences work. Right. Like you have enough whatever you hedonics in your life. And then then like the social status, all of the sort, you know, we're so rote about this saying Augustine wrote about this. This is like a kind of like a basic part of preferences. Now two, you guys are arguing about something else where like you could have such high concentration that you could just have a couple of exceptions to the rule. And that's going to be enough. And I have nothing to say about that. Yeah. Yeah. I mean, I think that it claims a little strong. You're not just like you could have some exceptions for that. It seems that historically and today, we see the exceptions and they just haven't really taken over the economy historically because they've, they've been these dissipation shocks as they're called. So they've like given it to their kids who's wanted it or they put it in foundations which, which spent it. I mean, it's not really a shock, but I mean, as people want, people might have liked to, you know, fill the universe with monuments themselves and sort of whatever lived forever. It's very wealthy. And it's like a weird preference, but it's not a hypothetical preference. I think that's that's the way. But who knows what's going on in their heads. I think even without though like the kind of intrinsic preference for accumulation, there are some instrumental reasons why people, some people might value accumulation, which is also worth bringing up. So there's the desire for a political or philosophical or religious influence, right? So people get this sort of an arms race over like what, you know, what society looks like and what people believe. And then similarly, but differently because it's not an arms race. There's just a total total utilitarian philanthropy, right? So when I think about why it might be good to have a lot of wealth in the future as a good classically utilitarian, to me, the values are at least one way you could have a kind of almost unsatiating utility function in having wealth in the future is to create new happy beings, right? They just add to the total welfare of the world. You know, I mean, this society goes at least as far back as like Boston's astronomical waste point that we could like put Dyson spheres around the stars and turn all the energy into really happy simulations and whatnot. I think the particular greediness of this optimizer doesn't matter what they're greedy for. I think forgetting about utilitarian philosophy or whatever, like it's just a pure von Neumann probe has, I don't know what the, is this an accurate to say yet? They just have a high marginal value for like the random solar system they will occupy because that turns into like more solar systems or turns into more solar systems. But like a von Neumann probe is a thing that will can exist, right? And that's like a very greedy optimizer. Yeah. I mean, if we're talking about like whether they'll dominate the economy, maybe this is a technicality, but you know, we only count final consumption goods and investment goods as GDP, right? If there's just this phenomenon, how does a von Neumann probe show up in GDP? Yeah, exactly, right? So if it's like, if we recognize it as a person that like owns itself and it's like sort of, you know, optimizing on the margin between like spending a bit more on a baby von Neumann probe that colonizes another star system or like a ballerina or something and it's just like it doesn't value the ballerina very much. Yeah, when we're talking about like AI beings or like like it just it just completely depends on how we're doing the accounting there Right. Yeah, but it's just like what does the world look like in a world where like one norman probes are possible is a possible labor shares high Anyway, yeah, I think it's possible that the labor shares hide the way we usually account it One of the biggest problems in our all right now is credit assignment because you have these extremely long rule outs And you need to know why they succeeded or failed one of course our researchers Sasha rush Give me a blackboard lecture on how they use targeted rl with textual feedback to deal with this problem and shrink composer 2.5 I filmed on my iPhone so apologies for the camera work. So we've generally this output. Yeah, it's just a sequence of tokens Um, we're going to send our sequence of tokens to this model that's going to read it. Yeah Um, and then it's kind of isolate a specific state that it says is problematic. Yeah Then we're just going to do text manipulation. We're just going to take that trajectory and we're literally just going to like Smash in some extra tokens after cursor inject these hint tokens They run another forward pass the trajectory itself doesn't change But the hint causes the model to assign lower probability to the error tokens cursor Then trains the original model to match those probabilities basically teaching it to downway these specific mistakes There's a lot more nuance that we couldn't include in this literal if you want to watch the full thing I posted it on my twitter and if you want to try out composer 2.5 had to cursor.com slash dorkhash Do economists have any advice or countries which are not in the eye production chain if you if you're not either producing the AI models You're not producing The hardware that goes into a models if you're not Korea making hbm or tywan making Um with the fuzz or not um The Netherlands with a sml Like what is india or niger what should they be doing right now? If you're talking to mody right now What do you say? I think the biggest lack of resources that we have allocated in the economic profession is thinking about middle income developing countries in the age of AI And I mean, this is this is my fault, you know, this is something I fault myself with as well There's not enough people thinking about this question like there are scenarios where, you know, you get like AI technology um, you know being allocated and dissipating to to nigerian in developing countries and things like that and like that leveling the playing field like essentially like giving them a like a level up as far as capabilities Um, but there's another world where like because they don't have enough resources. They're not making in uh, they're not training the models They don't have the hardware where they just completely get left behind and because of you know Automation we can produce commodities in developed countries now right then we don't even have you know the consumer market And then that that world looks pretty pretty bad. Yeah, this seems to me like an extension of the messy middle case, right Um, one of the ways in which the messy middle might Uh, only be bad in a narrow range of scenarios Isn't just that like it would be easy to redistribute because it would be bigger but because um The interest rate would be way higher and or sort of equivalently the price of everything except the Human intrinsic goods would be would be falling really rapidly It's sort of two sides at the same point um a little bit of savings would turn into a lot of consumption next year, right So things have to go really wrong for us to like just get over the threshold of uh, you know capital being productive enough to Automate lots of work, but not be productive enough that that the interest rate is high and or the price of capital produce goods is falling a lot Okay, so even without redistribution a little bit of savings will save a lot of people And sorry, you're saying that the developing countries have some savings yeah in the developed world that will be enough to produce a lot of surplus That they can bet they will now be able to consume a lot right using their say so so but but I mean uh, the messy middle could be Like wider in this case. I mean they're starting from such a lower level in terms of like how much They say they haven't and how how much it's like actually indexed to the global comment yeah um And I think it's important for them to get on it now and I don't have strong feelings about whether it should take the form of like Sovereign well funds that invest in right the right supply chains or uh or just you know subsidies to their own citizens to buy a little bit of This is actually I think a crucial point We were talking earlier about why the Rockefellers are world up over the world by their descendants don't control everything If our argument about the selection of these kind of greedy optimizers hold and one argument is just that It's like very hard to index the economy and maybe they would have just decided to have their ears indexed the economy and have it grow at the rate of I cannot have their wealth grow the rate of economic growth and they would be you know trillionaires Their ears would be trillionaires by now but It just is before index funds existed. It's just very hard to just get um Get a represent it just a very small fraction of the economy going back a hundred years Accounts for majority of the value created now and if you missed those particular things you would have basically Your wealth would have just kind of stagnated Um, and maybe there was a brief golden window from the creation of index funds up until I don't know five years ago We're actually you could index the economy and you could have your wealth grow at the rate of the economy grows but Now that we're in this world with very concentrated returns especially two private companies Which is capital that is as we were making a point in our blog post um, the average person has disproportionately less access to Uh, as opposed to you know, most of their capital is like having a random house at least in the u.s Or a part of a house. Yeah, which is as as we were saying is sort of unique A capital that is uniquely ill suited to be complementary to the production of AI or the serving of AI or to robots Or the kinds of goods that the rich will bid up the price itself exactly right because what is the value of a house currently? It is really the land is close to other humans and Modular relational stuff that is just not going to be the main factor of production and this is where Georgian tax would would not Raise enough money for for the sort of programs that that we were describing. Right, but stepping back The point I was trying to make is it would get harder to index the economy now And that is supposed to be the main way in which both one and normal people are supposed to Modular and sort of use an universal big income in the developed world Are supposed to have some leverage on or have some purchase on the wealth for me. I And it's also the way that developing countries are supposed to have some purchase on the wealth gains from AI But it's very hard. I don't know is is like a rich is Nigeria own a lot of SK high necks and like and drop it I'm guessing not right. It's not enough for them to just own the S&P 500 So actually this brings up a really important point like is AI going to be like electricity or social media right If it's so think about comment or a commentess and whatever whatever the electricity provider here is it's a monopoly it provides a Resource that everybody uses but do we think about electricity is like generic Creating concentration of power and it's comment like having like this Huge amount of political power social power or something like that Know because a lot with electricity a lot of the downstream benefits actually came to like the users of the electricity rather than the Rather than the actual entity producing the electricity on the other hand with social media was the opposite case right social media You know, it was everywhere everybody uses social media, but the rents went to the platform But that's a really interesting point The more you think I don't endorse this take it. I'm gonna talk talk about loud the more you think agi is going to be It's um our economy is going to be run on agi the way our economy currently runs on electricity This is a broad fundamental transformation of the entire economy the more looks like electricity and the more It's like every company in the S&P of the future exactly if it's gonna make it to the S&P 500 It is because it has leveraged AI exactly and then you're indexed again. Yeah, exactly But then again, I guess it is totally If you just look at how concentrated the S&P is over time, you know, just like these big tech companies much more so I guess this is a good so fundamental point that it's hard to reason about about how much of the Gains for may I these individual private companies will be able to control and I think like the open model thing is going to be a big big Thank you, right? So like if if we're indeed like sit we're in a we're in a world where it's like the open miles There's models are six months behind the front you nine months Then you know will hit agi will hit whatever and like in six months Like everybody has access to this to this resource and it this goes to show you that every question is connected to every other because Then that question about whether there's runaway gains connects to questions about recursion some improvement And even have recursion some improvement then continue learning which or online learning Which lets them auto learn on the jobs if it's deployed it gets to learn more and these are just sort of like Technical question or forecasting technical questions Which then impact I guess whether you're gone that will have any purchase on yeah, the returns of agi But it sounds like your answer really The reason I'm emphasizing the question is I think both for the messy middle and for developing countries A recommendation that is often made naively is you got to do some kind of retraining you got to do some kind of like Jobs program or you got to have them build data centers in our country And I think you guys are suggesting something closer to just by by the index of agi That's like a probably much more cleaner and much more likely to succeed Strategy it. We it's really good. They're these are the two scenarios, right? So I think there is a world where it is concentrated. Yeah, in which case it's going to be really hard to index agi There is another world where it is not cut its electricity Then like basically every company is access to agi so you just buy you use buy the index So like you know Nigeria just needs to buy the index right and they and Nigeria has access to agi. Yeah, right like because of the open models? - Yeah, so just to get back to the question of like, about whether to go with retraining or just trying to index, I would prioritize trying to index, but just giving how fast I could hit the world. But I definitely wouldn't just rely on that because the sort of messy middle type cases, or they're just the long timelines cases on which like, we don't get anything like AGI all that soon. We'll still, it'll just be like leaving a lot of value on the table if you could have like, we trained to be a bit better, you know, like educated to how to use the latest wave of computing. And yeah, so I don't think there's that much of a, and either or there, like, I mean, maybe the reason to be pessimistic about this is because one of the reasons the country's pours that is a bad education system, and so becoming the best in the world or retraining people using AI, it doesn't seem like a particularly promising strategy for the, that for country. - Although there are cases where like in developing countries, you had this like leapfrogging effect, with like, for example, like mobile banking or something like that, it's much more prevalent than like Nigeria than it is in Germany or something like that. Like everybody is doing mobile banking, they have it on their phones, they're constantly doing this sort of thing. So, I mean, I, again, I'm not putting probabilities on this, but like with a transformative technology like AI, you could get leapfrogging, where, you know, you skip the step in the middle, and you can get like really astronomical growth. - Maybe. - Just about the ease of indexing, can I just quickly say, I think it's definitely something to worry about a bit and keep an eye on, but as discussed in our own essay, and as other people pointed out, it's already not that hard to index. So, it's not, there's been a bit of an increase in the privatization of returns, but it's still like, you know, well under 20% of the total market cap of non-tiny companies in the US is private. And, you know, everyone thinks about open AI and anthropic, and then if that's where all the wealth will accrue, then yeah, like all these questions about whether open models will stay only a little bit behind. You know, those are important. But, you know, even they look like they're going public before too long probably. And the frictions that have been keeping companies from going public might themselves be alleviated by AI a lot, right? Just all of the disclosure requirements and whatnot. They want to get access to more potential investors too. And if I had to guess, I would guess that the kind of long kind of general trend of just like lowering those frictions and making it easier for more and more people to index more and more will continue despite the recent bump in the other direction. - This actually makes me hope even more so than before that the labs do get commoditized. Or at the very least they go public as soon as possible, but hopefully they just get totally commoditized because I think AI will be much more popular and more importantly, it will be much more likely to lead to broad increases in prosperity if the gains are just not particular. It is as hard to capture the gains of AI as it is to capture the gains of electrification. - Yeah, exactly. So I think like everybody, there's no anti-electricity people out there, right? - I mean, no electricity doesn't take your job, but to some people's job they are. - Yeah, yeah. And I think it's I, you know, this is maybe a tangential to the conversation. I think like there's like a really narratives matter and there's this like really negative narrative around AI right now, but that's because people are not putting out a positive narrative or because, and there's a reason, it's more difficult to imagine something that doesn't exist that's a good thing than losing something that exists. - Right, yeah. - Right, so it's very easy for somebody to go on a podcast and to say like, these jobs that you like, they're going away than to somebody to spin up like a utopia which doesn't exist. - Right. I hope this isn't too out of left field, but I think I would be remiss if I didn't point out one big cost of having commoditized Frontier AI models which is the tech race dynamic, right? That like for safety purposes, you might want fewer Frontier companies so that each one has a buffering case. They want to slow things down to make things safer. And the way this relates to our point before about the kind of widespread access, you know, of the returns, is that I think there's a lot less of a trade off there than some people imagine where, you know, some people think either Frontier AI gets commoditized and we all enjoy the benefits but there might be some risk because like it's, the market's really competitive and cutthroat or things are safer because there's a big gap between the leader and the laggard but that means that the leaders get fantastically wealthy. No, like you could just have a relatively big gap but it's a public company ownership and it's widely distributed. - Yeah, yeah, yeah. More recently I have been thinking that the risk of commodification, which is that it sort of diffuses the, it diffuses the ability to use AI to harmful ends is worth the benefit that I just feel I worry that not only having these concentrated labs makes it so that the sort of surplus isn't as widely distributed through society but also it creates a very tangible, clear political target for the government to, I mean, we saw this with the Defense Production Act right against Anthropic. If there wasn't one lab that is, or a couple of labs that are clearly ahead of others, this kind of threat would be much harder to make. Then yes, we're doing this. - Yeah, thank you. - Thank you. - I feel like there's a lot of unresolved questions but it is helpful to know what the relevant, at least like what is the first branch along all these important dimensions. - Great, thank you. - Okay, well, thanks.