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

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?

Dwarkesh PatelhostAlex Imasguest

Jun 4, 20261h 16mWatch on YouTube ↗

EPISODE INFO

Released: June 4, 2026
Duration: 1h 16m
Channel: Dwarkesh Podcast
Watch on YouTube: ▶ Open ↗

EPISODE 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?

SPEAKERS

Dwarkesh Patel
host
Podcast host known for long-form interviews on AI, economics, and science.
Alex Imas
guest
Economist focused on AGI economics (Google DeepMind) and professor of economics at the University of Chicago.

EPISODE SUMMARY

In this episode of Dwarkesh Podcast, featuring Dwarkesh Patel and Alex Imas, The better AI gets, the smaller its share of the economy might get – Alex Imas and Phil Trammell explores post-AGI economics: scarcity, labor share, redistribution, and global inclusion risks The conversation frames “what remains scarce after AGI” as a question about which preferences and constraints still bind when production can be machine-run end-to-end, highlighting a possible “relational sector” where humans are valued intrinsically rather than instrumentally.

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