Human-AI Collaboration in Science at Scale: A Global Large-scale Randomized Field Experiment
Collaboration is the defining mode of modern science, yet its core mechanism -- feedback -- remains hard to observe, difficult to scale, and unequally distributed. Here we test whether large language models (LLMs) can contribute to this hidden but vital practice and reallocate scientific feedback, an essential yet scarce resource for knowledge production. In a global large-scale randomized field experiment, we delivered customized LLM-generated feedback for over 31,000 arXiv preprints across 150 fields and more than 45,000 researchers from 133 geographic regions. Relative to controls, authors who received feedback had a significantly higher likelihood of revising their manuscripts, corres...
| Authors | Binglu Wang, Weixin Liang, Jiahui Xue et al. |
|---|---|
| Primary category | physics.soc-ph |
| Published | 22 May 2026 |
| Last updated at source | 22 May 2026 |
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