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Economists Clash Over the AI Research Boom

Jan Kulveit's lament that AI economics research has grown 10-30x in volume but not quality sparked a multi-day debate among economists over whether AI will breed ten times as many economists and reshape the field's paradigm.

2026-10-24 ~ 2026-10-25 · 2 episodes · 7 posts

Episode 1 · Economists studying AI grew 10-30x, but quality disappoints insiders (2026-10-24, 5 posts)

TL;DR: Researcher Jan Kulveit posted on October 24 that only a handful of economists seriously considered AI's economic impact a few years ago. That group has since grown 10-30x, yet the quality of the output disappoints him. The take was quickly reshared and debated by many users, sparking a concentrated discussion in the community about the "quantity up, quality down" phenomenon in AI economics research.

Confirmed

  • Kulveit recalled that only a few economists — Erik Brynjolfsson, Anton (Aki) Korinek, Paul Trammell, Carl Shulman — and their collaborators were seriously studying AI's economic impact a few years ago.
  • Back then he thought the field should scale up roughly 10x; it has actually grown 10-30x, but he is disappointed with the results, saying much of the newcomers' output is of questionable quality.

Why it matters

  • The observation speaks to a broader problem of surging academic supply amid the AI boom: a rapid expansion in researcher headcount doesn't necessarily bring a matching rise in quality of ideas.
  • Within a day or two the post was echoed and discussed by users including voooooogel and aniketapanjwani, showing the judgment resonates in the AI-economics crossover community and reflecting insiders' dissatisfaction with the current level of discourse.

Episode 2 · Economists Debate How AI Will Reshape Economic Research (2026-10-25, 2 posts)

Economists including Jan Kulveit and Ben Golub, with MIT researcher David Duvenaud joining in, debated whether AI will produce ten times as many new economists, with Golub arguing that empirics-dominated, conservative economics struggles to generate major new theory in the AI era.