The vast majority of academics do not want artificial intelligence used to assess the next Research Excellence Framework (REF), according to a new report.

Ahead of changes to guidance for the REF 2029 expected to be announced this month, the study also found that more senior university staff are generally more supportive of using AI and not succumbing to a “moral panic” around its use.

The report, led by the University of Bristol and funded by Research England, found that some universities are already using generative AI to assess the quality of their research.

But it showed that there was wide variation in how it was being used, with some universities using AI tools to gather evidence of real-world impact, and others building new tools to streamline REF processes or assess their research.

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In a survey of almost 400 academics and professional services staff conducted as part of the study, the majority of respondents strongly disagreed with all aspects of using AI in the REF.

Two-thirds strongly disagreed with the idea that universities should use it to support internal assessment of REF research outputs, and three-quarters strongly disagreed with its use by REF panels in assessing outputs.

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A further 86 per cent disagreed with AI being used to support the assessment of impact case studies by REF panels.

With funding required for REF 2029 likely to be even higher than the £471 million spent in 2021, lead author Richard Watermeyer, professor of higher education at Bristol, said AI had the potential to alleviate some of the burden.

“GenAI could be a game-changer for national-level research assessment, helping to create a more efficient and equitable playing field.”

Some respondents in the report highlighted the advantage of using AI tools to handle the “drudge dimensions” of some REF preparations, and in reducing the huge burden placed on academics in reviewing outputs for REF institutional selections.

However, Watermeyer said GenAI offers no complete solution and acknowledged the “vocal opposition” the survey revealed to the incorporation of it into the REF.

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“It could also create new bureaucratic challenges of its own, including establishing new requirements and protocols for its appropriate use.”

The report found different views among the 16 pro vice-chancellors it interviewed, with some urging caution amid an “AI bubble” until it becomes clearer what the limitations of the technology are, and others concerned around how much they can trust AI.

But another said: “I do think that just to put our heads in the sand and say it’s not going to happen or not on our watch I think is very limiting of what the future might look like…I think there’s a lot of moral panic.”

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Watermeyer said opposition to AI is concentrated among certain academic disciplines, in particular arts and humanities and social sciences, while professional services staff tend to be much more enthusiastic about its potential.

Steven Hill, director of research at Research England, said the findings offer “both a caution and a call to action”.

“It warns against haste and complacency alike, while inviting the sector to lead with principle, collaboration, and well-informed critique. With the right safeguards, the integration of GenAI can help us uphold excellence, fairness, and trust in the assessment of UK research.”

Authors recommended that all universities should establish and publish a policy on the use of GenAI for research purposes, that staff should receive full training on the responsible and effective use of AI tools, and for robust national oversight.

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The majority of interviewees cautioned that that without a standardised tool across the sector, the use of GenAI in REF preparations will “bake in structural inequalities for poorer resourced institutions”. So the report also called for a shared, high-quality AI platform for the REF to be developed and made accessible to all institutions.

patrick.jack@timeshighereducation.com