Name: The better AI gets, the smaller its share of the economy might get – Alex Imas and Phil Trammell
Uploaded: 2026-06-04T16:37:38+00:00
Duration: 4569 s

Speakers

Alex Imas — Director of AGI Economics at Google DeepMind and Professor of Economics at the University of Chicago

Phil Trammell — Head of Economics at Epoch and research scholar at Stanford

Dwarkesh Patel — Host, Dwarkesh Podcast

Summary

Alex Imas and Phil Trammell discuss what economics suggests about scarcity, labor share, and wealth distribution under advanced AI. They explore which sectors could capture value, including relational/human-in-loop services, AI compute, software, and data centers, and how countries outside the AI supply chain might index to AGI gains. The conversation also covers why negative-growth automation scenarios may be implausible and why housing is poorly positioned for AI wealth exposure.

Defines labor share versus capital share and debates whether it could collapse under AI.
Identifies relational/human-intrinsic services as a possible scarce, valuable sector.
Explains compute demand may not satiate, with H100 rental prices above prior years.
Argues software has highly elastic demand and may keep expanding as it becomes cheaper.
Recommends developing countries prioritize indexing to AGI rather than only retraining.
Suggests US housing is not complementary to AI or robot production.
Discusses the AI-as-electricity versus social-media analogy and open-model access.

Ideas

Alex Imas Director of AGI Economics at Google DeepMind and Professor of Economics at the University of Chicago 0:44

Human-in-loop services stay scarce and valuable.

Even after broad automation, goods and services where a human in the loop is part of the product's value will remain scarce. Experiments show people pay more for human-made art because they value empathy, connection, and intrinsic human involvement, so value should accrue to the relational/human-intrinsic sector.

Alex Imas Director of AGI Economics at Google DeepMind and Professor of Economics at the University of Chicago 15:33

AI compute demand may keep rising.

The historical Moore's-law pattern where computation value halved as supply exploded may be breaking: H100 rental prices are higher than three years ago because smarter models raise the opportunity cost of compute. If new uses keep appearing, compute demand may not satiate and its share of the economy could keep increasing.

Alex Imas Director of AGI Economics at Google DeepMind and Professor of Economics at the University of Chicago 34:49

Software demand is highly elastic.

Software is described as a particular kind of good with highly elastic demand: as it gets cheaper, people want disproportionately more of it, unlike oil, insulin, or agriculture where satiation limits total spending. That means software spending can keep expanding rather than automatically collapsing.

Alex Imas Director of AGI Economics at Google DeepMind and Professor of Economics at the University of Chicago 50:02

Data center returns are currently super high.

Returns to data centers are currently very high. Whether that persists depends on whether capital owners satiate; if capital satiates, returns to accumulation fall and consumption rises, but for now data center returns are high.

Phil Trammell Head of Economics at Epoch and research scholar at Stanford 65:24

US housing is poor AI wealth exposure.

Most households' capital is tied up in a house, but housing is uniquely ill-suited to be complementary to AI or robot production. Its current value is mostly land near other humans and relational factors, which will not be the main factor of production in an AI economy.

Phil Trammell Head of Economics at Epoch and research scholar at Stanford 70:07

Developing countries should index AGI gains.

For countries outside the AI production chain, Phil prioritizes indexing into AGI/global equity returns via sovereign wealth funds or equivalent over relying on retraining, because AI could arrive quickly. In an electricity-like scenario, broad index exposure captures the gains, and even with concentration it is worth trying to index now.

The better AI gets, the smaller its share of the economy might get – Alex Imas and Phil Trammell

Summary

Ideas

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