TLDR: A new global survey by IOP Publishing indicates a significant split among physical science reviewers regarding the integration of generative AI into the peer review process. While currently disallowed due to ethical concerns, there’s a growing acknowledgment of AI’s potential to assist, rather than replace, human reviewers.
IOP Publishing (IOPP) has released findings from a recent global reviewer survey, highlighting a notable divergence in perspectives among experts in the physical sciences concerning the application of generative artificial intelligence (AI) in peer review. The survey, detailed in an article by Faye Holst titled ‘Reviewers Increasingly Divided on the Use of Generative AI in Peer Review,’ underscores the complex challenges and opportunities presented by this emerging technology.
According to the survey results, a clear divide exists within the academic community. While some reviewers express enthusiasm for AI’s potential to streamline and enhance the peer review workflow, others harbor significant reservations, primarily centered on ethical, legal, and scholarly integrity issues. IOPP’s current stance reflects these concerns, as the organization explicitly prohibits the use of generative AI in peer review. This prohibition is rooted in the understanding that current generative models cannot consistently meet the stringent ethical, legal, and scholarly standards essential for maintaining the integrity and reliability of the peer review process.
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Despite the current restrictions, the survey also revealed a growing recognition within the scientific community of AI’s potential to serve as a supportive tool. Rather than envisioning AI as a replacement for human judgment, many see its future role as an assistant, capable of handling routine tasks, identifying potential issues, or aiding in preliminary assessments, thereby allowing human reviewers to focus on more nuanced and critical aspects of manuscript evaluation. This nuanced perspective suggests a future where AI could augment, rather than undermine, the foundational principles of academic peer review, provided robust guidelines and ethical frameworks are established.
