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

2026-06-04 Science & Technology
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Dwarkesh Patel
Dwarkesh Patel
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Description

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? How should countries not in the AI supply chain index into the gains? Is there any world where inequality doesn't explode? It might seem like these questions have obvious answers, but the first thing economics teaches you is that your intuitions can often be entirely wrong. It was very helpful to chat through these things with Alex and Phil. 𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊𝐒 * Transcript: https://www.dwarkesh.com/p/alex-imas-phil-trammell * Apple Podcasts: https://podcasts.apple.com/us/podcast/alex-imas-and-phil-trammell-what-remains-scarce-after-agi/id1516093381?i=1000771185825 * Spotify: https://open.spotify.com/episode/52wp90vqwiRmmQaOm9M2uZ?si=8a81MnA4Tf-X3VUzpzE1qg 𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒 * Jane Street invests heavily in turning smart people into exceptional researchers and engineers. In addition to their apprenticeship model, Jane Street runs lectures and bootcamps in their in-office classrooms -- managers clear their teams' schedules to encourage attendance. If you'd like to work at a place that takes learning this seriously, Jane Street is hiring. Check out their open roles at https://janestreet.com/dwarkesh * Google's Gemini Omni has incredible video editing capabilities -- you can upload a video and have Omni change the background, adjust lighting, or add specific elements. But Omni is also a preview of how future frontier models will be trained -- fully multimodal on both input and output. You can try it yourself in the Gemini app at https://gemini.google or in Flow at https://flow.google * Cursor used targeted RL with textual feedback to help train their Composer 2.5 model. One of their researchers, Sasha Rush, gave me an impromptu blackboard lecture to explain how this form of on-policy self-distillation works -- I posted the full thing on X. If you want to try Composer 2.5, go to https://cursor.com/dwarkesh To sponsor a future episode, visit https://dwarkesh.com/advertise. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 00:00:00 – Will capital share increase? 00:19:36 – Messy Middle scenario 00:25:57 – How to tax and redistribute AI wealth 00:30:02 – Why demand collapse is unlikely 00:39:26 – Human employees would be hard to integrate into the machine economy 00:43:08 – What if some humans (or AIs) value wealth accumulation intrinsically? 01:01:28 – What should developing countries do?

Top Comments (10)

@Wembanyana 2026-06-04

Just lost to New York, needed this. Thanks!

54 6 replies
@pietervoogt 2026-06-04

13:30 bad example because singing became automated too with recordings. People love music so much that a world without recordings would probably employ millions of musicians

32 6 replies
@Galizur-Raziel-777 2026-06-04

Well, the question is, if a significant amount of the doctor job (for example) gets automated, which thing happens: 1. The doctor spends more time per patient, 2. The hospital owners try to have more patients per doctor, 3. Both, and price difference determines which one any patient gets. Because that doctor's freed up time could go to either more patients, or to more time with each patient. Btw, "time with patient" isn't just some kind of emotional support, but could relate to detecting earlier signals of chronic disease, and similar things that most doctors just don't have time to prioritize currently. Translate that to every job: what increases in terms of human output: quality, quantity, or both? If we assume that profitability (capital demand) is the primary constraint, then either we have quantity with lower price, or quality with higher price. Interestingly, this merely expands a dynamic already at play; the trend of offloading more tasks to nurses could be seen as another version of "automation."

15 9 replies
@rickymort135 2026-06-07

If economists can't predict the future, their model of economics is wrong. That's how we do things in science you build confidence in a model by showing it can predict. What you can't do is say hey we're bad at predicting but listen to us anyway

5 9 replies
@andrew.sandler 2026-06-05

Have been loving the newer videos. You get better as you go.

4
@ErikByrwa 2026-06-06

This was a fantastic discussion. Thank you for sharing!

2
@user-id3mv5dh8s 2026-06-06

Thank you so much for sharing this with us ❤️

1
@pianoforte611 2026-06-04

Amazing interview. Really interesting to hear from people who understand both economics and AI. 46:00 I actually expected the opposite. In a world where AI produces vast material wealth, then people with higher preference for interacting with AI would benefit from some of that wealth and have more resources to raise children (you only need one mate, you don't need to interact exclusively with humans).

1
@zf0666 2026-06-08

great podcast! would have liked it to be 3 hours. bring them back!

0
@brendanwhiting1235 2026-06-08

great timing, this is the right conversation

0

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