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[ARTICLE · art-38833] src=marginalrevolution.com ↗ pub= topic=artificial-intelligence verified=true sentiment=↓ negative

Translated from the Chinese

Stanford REAP team's CoPaper.AI generates complete empirical papers with code and charts from raw data in 30 minutes, threatening manual labor in social sciences. The tool automates EDA, variable definition, and econometric modeling, raising concerns about job displacement for data analysts and paper mills.

read1 min views1 publishedJun 25, 2026
Translated from the Chinese
Image: Marginal Revolution

I think this is the Cursor moment for academia.

The Stanford REAP team has made their move,

[CoPaper.AI is mass-terminating the manual labor of traditional empirical papers. Link:][copaper.ai/landing]If using large models to write papers before was just about polishing and compiling references for you, then this Project from Professor Ross Griebenow’s team at Stanford is like dropping a nuclear bomb in the empirical circles of social sciences and economics.

The greatest truth is the simplest; the heaviest sword has no edge. Its functions are straightforward. Feed in the raw dataset, and within 30 minutes, it can generate a complete DOCX paper complete with full Stata/R code and publication-quality charts.

It chains together EDA, variable definition, econometric model building (from OLS to advanced DID, regression discontinuity, causal forests) all using an Agent workflow.

Every chart it produces comes with 100% reproducible Stata, R, EViews source code underneath. How many low-quality paper mills and data drones’ jobs will this smash?

Data drones and paper ghostwriters are collectively facing unemployment countdown. Because from now on, for social science papers, AI handles all the entropy-increasing drudgery—humans only need to define the problem.

Here is the link. Mostly that is not true, so perhaps the Chinese are trying to demoralize us. But will it never ever be true? In two years be true? Less?

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