AI help in grant proposals tied to higher funding odds at NIH

"Scientists are increasingly turning to artificial-intelligence systems for help drafting the grant proposals that fund their careers, but preliminary data indicate that these tools might be pulling the focus of research towards safe, less-innovative ideas. These data provide evidence that AI-assisted proposals submitted to the US National Institutes of Health (NIH) are consistently less distinct from previous research than ones written without the use of AI - and are also slightly more likely to be funded."

"These results indicate that, if the trend continues, "we could be on a path towards homogeneity", says Misha Teplitskiy, a science, technology and policy researcher at the University of Michigan in Ann Arbor. "This paper provides some suggestive evidence of that happening." The analysis, which has not yet been peer reviewed, was posted on the preprint server arXiv on 21 January."

"Since large language models (LLMs) became mainstream in 2023, most scientists have tried using AI tools to assist them with researching their ideas and writing and editing their manuscripts, according to a 2024 survey. Dashun Wang and Yifan Qian, computational social scientists at Northwestern University in Evanston, Illinois, were curious whether this rapid and widespread adoption of AI tools has changed the type of science that is funded."

AI-assisted grant proposals submitted to the US National Institutes of Health are consistently less distinct from previous research than those written without AI and are slightly more likely to be funded. Analyses of thousands of grant proposals submitted to the NSF and NIH between 2021 and 2025 compared proposals from two large US universities with publicly available grant abstracts. Large language models became mainstream in 2023, and most scientists used AI tools for research and writing according to a 2024 survey. The pattern suggests widespread AI adoption may steer proposals toward safe, less-innovative ideas, increasing the risk of homogeneity in funded science.

Read at Nature