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

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

Dwarkesh Podcast

June 4, 2026

Economics of AGI episode w Alex Imas and Phil Trammell. There’s a bunch of important questions about how we deal with AI that only economics can answer. What is the optimal way to tax and redistribute the wealth that will be generated?
Speakers: Dwarkesh Patel, Alex Imas, Phil Trammell
**Dwarkesh Patel** (0:00)
Today, I'm chatting with Alex Imas, who is Director of AGI Economics at Google DeepMind and Professor of Economics at University of Chicago, and Phil Trammell, who is Head of Economics at EFAC 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 will be generated as a result of AGI will be, and what kinds of things will be scarce, because what is 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?

**Alex Imas** (0:44)
Something like the relational sector, which is what I defined as 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 in things that humans are kind of involved in and in the loop for.

**Dwarkesh Patel** (1:05)
I'm curious to understand whether humans doing services for other humans can never be a big part of the economy.
Here's maybe one intuition pump. So in a world where AI can physically do anything humans can do, there's this whole machine economy where they're 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 that you point out where, 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 a performance. But only humans have that preference.
So, there's this human economy where 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 as machine-only economy is creating. So, part of that wealth is flowing out. So, if you just think of this as like, this is not a closed loop, but a lot of things in the machine-only economy are a closed loop, because the machines don't care about getting the human barista to make them a coffee. So, within that model, isn't it intrinsic that the human-only economy will become a smaller and smaller share?

**Alex Imas** (2:24)
I would like to pitch kind of a rephrasing of that question. So, I think my view is that kind of forecasts 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 Andrei Fredkin, Brian DeBarrion and Andrew Koh that came out yesterday actually, that looked at like kind of people's forecasts, economists' forecasts about the labor market. 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 in 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, 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 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 neoclassical, 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. 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.

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