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- Pilot tests at Springer Nature<\/span> suggest generative AI tools could soon transform the review process for authors, editors, and reviewers.<\/li>\n
- The publisher emphasises that AI will complement\u2014not replace\u2014human peer reviewers.<\/li>\n<\/ul>\n
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<\/p>\nDelivering high-quality<\/a>, timely<\/a> peer review is challenging<\/a> in the digital era. Could generative AI (GenAI) provide solutions? In an opinion article<\/a> for Research Information<\/a>, <\/em>Springer Nature<\/a>\u2019s Director of Content Innovation, Markus Kaindl, suggests that GenAI tools could soon transform the review process<\/a> for authors, editors, and referees.<\/p>\n
Modern peer review: a Gordian knot?<\/strong><\/p>\n
The modern peer review system is increasingly voluminous and complex. According to Kaindl, authors <\/strong>struggle to explain discipline-specific data to reviewers and grow frustrated with multiple requests for clarifications and revisions. Editors <\/strong>struggle to find appropriately qualified reviewers<\/a> amidst ever-increasing submission volumes and tight deadlines. Due to time pressures and the complexities of highly specialised or interdisciplinary submissions, reviewers<\/strong> struggle to provide feedback that is detailed, constructive, objective, unbiased, and appropriate to the speciality.<\/p>\n
AI-assisted\u2026<\/strong><\/p>\n
Following pilot tests at Springer Nature, <\/em>Kaindl reports that GenAI could soon:<\/p>\n
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- provide \u201cactionable feedback\u201d to authors <\/strong>early in the submission process to help reduce the number of time-consuming revision rounds<\/li>\n
- accelerate the editorial <\/strong>process by drafting pre-review notes, highlighting key strengths and limitations in advance, and optimising journal selection<\/li>\n
- generate pre-review drafts for reviewers<\/strong>\u00a0and facilitate cross-disciplinary reviewing by simplifying complex, discipline-specific submissions.<\/li>\n<\/ul>\n
Furthermore, GenAI tools could be used to help safeguard research integrity<\/a> during the review process. Springer Nature has developed two such tools: Geppetto<\/a> detects AI-generated content (a potential indicator of paper mill activity), whereas SnappShot <\/a>analyses PDF files with gel and blot images for evidence of duplication.<\/p>\n
\u2026but human-centred!<\/strong><\/p>\n
Kaindl stresses that GenAI should augment<\/a> human expertise, not replace it, and says that AI tools should complement and enhance existing screening systems<\/a>. According to Kaindl, Springer Nature\u2019s <\/em>approach to AI promotes active community engagement (with authors, editors, and reviewers), tackles AI bias<\/a> through rigorous testing, and creates a safe environment for pilot testing to prevent the disclosure of unpublished manuscripts.<\/p>\n
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GenAI should augment human expertise, not replace it.<\/p>\n<\/blockquote>\n
Kaindl states that GenAI may already be in use to assist peer review. By embracing GenAI technology, publishers could help define practices for its effective use, understand its limitations, and future<\/a>-proof academic publishing.\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2013<\/p>\n
- accelerate the editorial <\/strong>process by drafting pre-review notes, highlighting key strengths and limitations in advance, and optimising journal selection<\/li>\n
- The publisher emphasises that AI will complement\u2014not replace\u2014human peer reviewers.<\/li>\n<\/ul>\n
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