Garicano: humans stay relevant in the AI economy as long as compute beats problems
JMateosGarcia · x · 2026-11-04
In a follow-up discussion of the NBER Genius on Demand paper, economist Luis Garicano argues the AI economy's general equilibrium hinges on what remains scarce: compute, agent autonomy, or problems.
- As long as compute is scarcer than the problems we want to solve with it, humans will have a role to play.
- When it costs less to turn a messy need into a clear, checkable task than the value AI can produce on it, firms keep creating such tasks — keeping compute scarce and human time valuable, sustaining broad employment.
- Turning humans into "horses" requires three conditions at once: autonomous AI, compute capacity exceeding available opportunities, and high enough costs of defining new well-specified problems.
- The economic imperative is turning latent needs into purchasable units of work faster than compute grows — from personalized education to scientific discovery, the stock of hard problems remains vast.
Related event: NBER paper: on-demand AI genius will reshape knowledge work(3 posts)→
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