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

“We have an incentive-compatible way of asking, 'How much are you willing to pay for this art print?' People are actually paying real money for it. Then we say, 'Look, there's only one of those art prints, and it's either made by AI or by a person.' These are between-subject conditions. With one, you get the effect that the person-produced art print is valued much higher than the AI version. Then, in a set of other conditions, we say there's 500 of these being produced. For the human-made one, the price goes down a lot because it's no longer seen as making a connection with this one artist. With AI there's no difference. AI is already viewed as a commodity.”

“The only way this relational story works—and this is what we need more data on—is if a human is not a horse in the sense that they are providing value from the output, where if you replace the human, the value of the output decreases. If that's not strong enough, and if it doesn't hold for enough sectors or enough jobs, then this story doesn't work anymore.”

“What got me thinking about the idea of the relational sector is work that I was doing on the fact that there does seem to be this intrinsic value. It's not just because it's scarce; it's because there's some intrinsic preference that people have for empathy, connection, and interacting with another person.”

“You could have a job and a service or a good be a product of different types of tasks, and you can automate a ton of those tasks. If the consumer is willing to pay more for a product or service where every single task is automated except for that one part where the doctor is delivering the diagnosis and providing support, we would call that job part of the relational sector.”

“Do a conjoint analysis of your willingness to pay for this service or good. Here's the counterfactual where everything is produced by machine. Here's the counterfactual where this one task is not produced by a machine. What is your willingness to pay? What is your elasticity for the human to not be in the loop? If I don't have that data, what prediction am I going to make in this story?”

“Look at the network-adjusted factor shares of a good. Look down the supply chain and not just the final step and 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 is adding a lot of value down the supply chain. Computer and electronic products in the US have a very stable network-adjusted capital share of around 50%.”

“I do think there's this qualitative shift that I think we agree is coming, which is that there will be at least some goods whose network-adjusted capital share goes to one. The whole supply chain can be automated, and there's no part in it that we care intrinsically about having a human do. That will be a qualitative shift. Interestingly, the implications of that shift for the overall capital share are ambiguous.”

“if we fully automate the supply chains for everything else, and we satiate in everything else really fast, then the quantity of everything that's not a ballerina goes to infinity, but the marginal utility in that stuff goes to zero faster than the quantity is rising.”

“If they just held the varieties fixed in both categories and asked, 'What will happen once we have a lot more automation?', they might have said, 'We'll just satiate in 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 happened.”

“What's happening is what would be called investment-specific technical change. The price of capital is falling relative to the price of consumption, instead of doing the standard macro thing of saying there's just output, this chimera of a thing called output, which one for one can be allocated to capital or consumption. That's not going to be true in this world.”

“If what's driving the difference is that one person just doesn't satiate in capital because they're engaged by the prospect of exploring the universe and turning their head into a galaxy brain or whatever, and the other one satiates, then the person who doesn't satiate in capital is going to, if they're being rational, have a higher savings rate. So in the long run, they're going to have most of the wealth, and the overall capital share will basically be the capital share of that person's spending, which is going to be one.”

“Most of his wealth is just stock in Meta. As a controlling shareholder, he could say, 'Meta, turn all this wealth into dividend income, and I will just spend that on consumption.' Instead, he would rather have his wealth compound and have Meta build more data centers. So you don't even have to change humans for this to be the case.”

“There will be evolution of, even if not individual AIs, firms which have AIs as part of them. What will that evolution favor? It will probably favor firms or agents that grow. There's a selection argument that things which grow will be more prevalent. Maybe just based on that, you can make some predictions about what their preferences will be. Compute is an obvious one.”

“historically and today we see the exceptions. They just haven't really taken over the economy historically because there have been these dissipation shocks, as they're called. They've given it to their kids who squandered it, or they put it in foundations which spent it.”

“having these concentrated labs not only makes it so that the surplus isn't as widely distributed through society, but also creates a very tangible, clear political target for the government. We saw this with the Defense Production Act threat against Anthropic. If there wasn't one lab, or a couple of labs, that are clearly ahead of others, this kind of threat would be much harder to make.”

“If we're indeed in a world where the open models are six months behind the frontier—or nine months—then we'll hit AGI, we'll hit whatever, and in six months, everybody has access to this resource.”

“The Budget Lab over at Yale is doing really good analysis on this. They just recently released a report, and you really have to squint to see anything happening. If you want to take an approach across the entire economy, even looking at software engineering, the most exposed sectors, there's just not really anything going on.”

“There might be a little bit of a signal about junior developers getting jobs less than before. But that's a 'less than before' rather than a level shift, as in there's actually an increased demand for senior software engineers, if anything. If you look at the trend, for junior developers, it's a bit below trend.”

“There's even a controversy right now. Some might say labor share has been falling in the last 20 to 30 years. But there have been a lot of accounting changes in the last 30 to 40 years. For example, Atkinson has a paper showing that if you keep the accounting constant over the years, labor share hasn't even fallen ever.”

“We don't have any data. I've been saying we need a Manhattan Project for data. We don't have data on consumer demand elasticities. We don't know what they are. We're not really tracking what jobs are getting created or destroyed. The O*NET database, with all of the tasks and different jobs, has been rarely updated and is super low quality.”

“Phone operators were completely automated, but it took 20 years, even though the technology existed. There was this drip. It wasn't like this giant sector just disappeared. There's a really nice QJE paper on this showing that they got reabsorbed into the economy, but at lower salaries, and they were mostly underemployed.”

“What I did in the piece, that Phil and I had a back and forth on, was to say, let's start with the proposition that there's negative economic growth. What conditions do you need in the economy to get negative economic growth? It turns out the conditions are pretty improbable. One thing that you need is for the holders of capital, rich people basically… You need demand to be bounded, like a hard bound, not even a soft 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 as investment. Then you can get negative growth.”

“I like the pessimistic framing of Moore's law: every 18 months, the value of computation halves. We're running out of uses for computation so fast that it's sustaining Moore's law.”

“One of the ways in which the messy middle might only be bad in a narrow range of scenarios isn't just that it would be easy to redistribute because the pie would be bigger, but because the interest rate would be way higher, and/or, equivalently, the price of everything except human-intrinsic goods would be falling really rapidly. They're sort of two sides of the same coin. A little bit of savings would turn into a lot of consumption next year.”

“With UBI, for example, I worry a lot about the political economy implications. If people are just dependent on a check, it really matters who's in power... When that is no longer the case and we are at the mercy of the elected official for basic needs, that feels like a power-sharing arrangement that's really dangerous.”

“Maybe there was a brief golden window from the creation of index funds up until five years ago where you could actually index the economy and have your wealth grow at the rate the economy grows. But now we're in this world with very concentrated returns, especially to private companies. As we were making the point in our blog post, this is capital that the average person has disproportionately less access to. Most of their capital is having a random house, at least in the US.”

“But really this only happens if the demand for something is highly elastic. There are many things for which there is not super elastic demand. If oil, for example, gets super cheap, it's not like magically—... It's not like magically there's going to be so many more cars that now we're going to be using way more oil than before.”

“The claim with software is that it is not some inherent property of markets that as it gets cheaper, you'll just keep wanting more of it. The thing about software is this is a particular kind of good where as it gets cheaper, we'll want more and more of it.”

“Your colleague Chad Jones has a very interesting result about how the share of the economy that is going towards paying for computing, paying for the transistors, has been decreasing.”

“That's the big question. That is the ultimate question that we need to be looking at. What number of new uses are we finding for that compute where you have the demand for these uses?”

“What they advocate for, and I'm in agreement here, is that rather than thinking about individual forecasts, we should be generating prediction markets where you get aggregate forecasts and wisdom-of-the-crowd effects. The reason I think this is because we have been famously terrible at forecasting.”

“All of these frictions on the political-type decisions that we are accustomed to only trusting humans for—legislation, being a judge, being a juror, or all the licensing that keeps certain professions human—that all strikes me as transitional. What we expect to come from a human and how we organize our politics has changed so many times throughout history.”

“If you can only automate nine-tenths of the job, but you do it to a lower standard of quality than the human could, you might not want to automate even those nine-tenths. That's the thing that could totally port over. Symmetrically, it could be a reason why we don't use a human for one-tenth of the job anymore, because a human just can't perform it to the level of quality that the AI can perform the other parts of the job.”

“My model of intelligence is such that—both the breadth of tasks it requires to do something like software engineering and what intelligence is—if you can really just lay off all the software engineers, you've got enough in the bucket there that you could automate all kinds of white-collar work.”

“Integrating humans into the production flow of future goods will become difficult. Even beyond the arguments about how humans will be more expensive or less capable, there will be whole production flows organized for AI labor. They're talking in neuralese. They're thinking many thousands of times faster.”

“There are these public coordination devices. Let's say we get into a narrative where if you're a firm and you're not laying people off, then you're seen as not adapting AI enough. Then you're going to just get a cascade effect of firms needing to keep up with the Joneses in terms of starting to lay people off. That's super worrying, where the firm might actually be worse off after the layoffs than before, but it's just doing the layoffs to have the perception that, 'Look, we're not behind the times. We're using AI.'”