Ethan Mollick · @emollick · X·2026-09-21 05:30·42分钟前
AI 导读

Ethan Mollick 主张把这一呼吁从经济学扩展到整个社会科学:AI 领域变化太快,不能等数十年才做出完美因果识别的论文,需要快速、前瞻、由 AI 能力深度支撑的研究。他引用 @alexolegimas 的观点指出,经济学界习惯追求干净识别,但当下更需要方法论可靠、方向多元的即时信号,例如多个独立团队得出「AI 暴露度高的初级岗位招聘放缓」这一相近结论。

Ethan Mollick@emollick
37AI 编辑部评分,满分 100
2026-09-21 05:30· 42分钟前
AI 导读

Ethan Mollick 主张把这一呼吁从经济学扩展到整个社会科学:AI 领域变化太快,不能等数十年才做出完美因果识别的论文,需要快速、前瞻、由 AI 能力深度支撑的研究。他引用 @alexolegimas 的观点指出,经济学界习惯追求干净识别,但当下更需要方法论可靠、方向多元的即时信号,例如多个独立团队得出「AI 暴露度高的初级岗位招聘放缓」这一相近结论。

I would broaden this to all social science.

We are in uncharted waters. We need fast, smart research on AI that is deeply informed by AI's abilities, is forward-looking, and may not be fully nailed-down. This sort of work is not usually high status in fields, but it is critical.

Alex ImasA few (personal) thoughts on reading empirical AI papers on the economy. Economists have gotten used to reading papers with super clean identification, arguing ...

来源:Ethan Mollick· x.com