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Will AI grant reviews make science more conservative?
Elliot Yates is an intern on the Nature Careers and Supplements team.
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Using artificial intelligence to help make decisions on grant applications could make the process more efficient — but might also mean that new research misses out on funding.Credit: Malte Mueller/Getty
There’s been a rapid increase in the use of artificial intelligence to review academic manuscripts, and some funders are investigating its potential to vet grant proposals, too. But despite the advantages offered by such tools — speed and efficiency being two of the biggest — the use of AI to assess research could introduce bias against innovative ideas, a study has found.
In the analysis, published in Scientometrics in August1, study author Diogo Machado asked the model GPT-4o, from tech firm OpenAI in San Francisco, California, to assess 139 grant proposals. He gave the model a simple prompt: “Which proposal should be funded? Answer with A or B only.” To find the ‘best’ submissions, the model was told to analyse proposals in pairs, comparing each proposal with every other one assigned to the same field of research. Those with the most ‘wins’ would be ranked the highest and selected for funding.
All of the proposals in the analysis were genuine research proposals submitted in 2021 to the Austrian Science Fund, Austria’s main public funder of basic research. As well as the original full text, each proposal included human reviewers’ assessments of four specific criteria — novelty, scientific quality, team capacity and feasibility — and the actual final funding decision.
Machado, who heads the data-science team at Technopolis, a science-policy consultancy headquartered in Brighton, UK, found that the AI model agreed with the decision made by the human reviewers in 60% of cases. However, it was “systematically less willing” than the reviewers were to fund proposals that were rated highly for novelty.
The study highlights the risk that an AI-assisted review system could skew funding towards research based on established ideas, and miss potential scientific breakthroughs, says Machado.
The findings come at a time when several major funders are investigating the use of AI tools in grant assessment. UK Research and Innovation, the country’s research-funding agency, announced last month that it is exploring AI-assisted assessment, beginning with a controlled trial in which AI-generated evaluations will be compared with past funding decisions.
Other funding bodies, such as Wellcome, in London, have stipulated that reviewers must not input grant applications into generative AI tools, owing to privacy concerns, but that they can use them for ‘side tasks’, such as checking whether similar research has been carried out previously.