Jason Furman: the bigger AI mistake is underusing it, not overusing it
sebkrier · x · 2026-11-02
Former CEA chair and Harvard economist Jason Furman doubles down on his controversial claim that he'd choose today's AI systems over 20 CEA staff economists, in a long personal essay.
- He admits the provocative example backfired but insists the view isn't obviously wrong, and urges honesty about AI labor-market risks rather than denial.
- His core framing: AI can do the analytical output of a "first job" like CEA work, but the real cost is young people losing the path to learn by doing — "AI could do my first job, not my last."
- He observes more people err by underusing AI — economists and think-tankers making avoidable mistakes and not thinking ambitiously — than by overreliance; erring in only one direction means you're using the technology wrong.
Related event: Ex-CEA Chair Furman: AI Can Do My First Job, Not My Last(7 posts)→
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