A new global reviewer survey from IOP Publishing (IOPP) reveals a growing divide in attitudes among reviewers in the physical sciences regarding the use of generative AI in peer review. The study follows a similar survey conducted last year showing that while some researchers are beginning to embrace AI tools, others remain concerned about the potential negative impact, particularly when AI is used to assess their own work.
Currently, IOPP does not allow the use of AI in peer review as generative models cannot meet the ethical, legal, and scholarly standards required. However, there is growing recognition of AI's potential to support, rather than replace, the peer review process.
Key Findings:
- 41% of respondents now believe generative AI will have a positive impact on peer review (up 12% from 2024), while 37% see it as negative (up 2%). Only 22% are neutral or unsure—down from 36% last year—indicating growing polarisation in views.
- 32% of researchers have already used AI tools to support them with their reviews.
- 57% would be unhappy if a reviewer used generative AI to write a peer review report on a manuscript they had co-authored and 42% would be unhappy if AI were used to augment a peer review report.
- 42% believe they could accurately detect an AI-written peer review report on a manuscript they had co-authored.
Women tend to feel less positive about the potential of AI compared with men, suggesting a gendered difference in the usefulness of AI in peer review. Meanwhile, more junior researchers appear more optimistic about the benefits of AI, compared to their more senior colleagues who express greater scepticism.
When it comes to reviewer behaviour and expectations, 32% of respondents reported using AI tools to support them during the peer review process in some form. Notably, over half (53%) of those using AI said they apply it in more than one way. The most common use (21%) was for editing grammar and improving the flow of text and 13% said they use AI tools to summarise or digest articles under review, raising serious concerns around confidentiality and data privacy. A small minority (2%) admitted to uploading entire manuscripts into AI chatbots asking it to generate a review on their behalf.
Interestingly, 42% of researchers believe they could accurately detect an AI-written peer review report on a manuscript they had co-authored.
"These findings highlight the need for clearer community standards and transparency around the use of generative AI in scholarly publishing. As the technology continues to evolve, so too must the frameworks that support ethical and trustworthy peer review", said Laura Feetham-Walker, Reviewer Engagement Manager at IOP Publishing and lead author of the study.
"One potential solution is to develop AI tools that are integrated directly into peer review systems, offering support to reviewers and editors without compromising security or research integrity. These tools should be designed to support, rather than replace, human judgment. If implemented effectively, such tools would not only address ethical concerns but also mitigate risks around confidentiality and data privacy; particularly the issue of reviewers uploading manuscripts to third-party generative AI platforms," adds Feetham-Walker.
