ESR Journals editors’ joint statement on Guidelines for the Use of Large Language Models by Authors, Reviewers, and Editors

Hamm, Bernd; Marti-Bonmati, Luis; Sardanelli, Francesco

doi:10.1186/s13244-023-01600-9

Insights Imaging

2024

DOI: 10.1186/s13244-023-01600-9

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ESR Journals editors’ joint statement on Guidelines for the Use of Large Language Models by Authors, Reviewers, and Editors

Bernd Hamm,

Luis Marti-Bonmati,

Francesco Sardanelli

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Cited by 2 publications

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Artificial Intelligence and Submissions to Annals of Plastic Surgery

Bhandari,

Drolet,

James

et al. 2024

Ann Plast Surg

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Artificial Intelligence and Submissions to Annals of Plastic Surgery

Bhandari,

Drolet,

James

et al. 2024

Ann Plast Surg

View full text Add to dashboard Cite

AI-powered peer review needs human supervision

Seghier

2024

JICES

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Purpose This paper aims to appraise current challenges in adopting generative AI by reviewers to evaluate the readability and quality of submissions. The paper discusses how to make the AI-powered peer-review process immune to unethical practices, such as the proliferation of AI-generated poor-quality or fake reviews that could harm the value of peer review. Design/methodology/approach This paper examines the potential roles of AI in peer review, the challenges it raises and their mitigation. It critically appraises current opinions and practices while acknowledging the lack of consensus about best practices in AI for peer review. Findings The adoption of generative AI by the peer review process seems inevitable, but this has to happen (1) gradually, (2) under human supervision, (3) by raising awareness among stakeholders about all its ramifications, (4) through improving transparency and accountability, (5) while ensuring confidentiality through the use of locally hosted AI systems, (6) by acknowledging its limitations such as its inherent bias and unawareness of up-to-date knowledge, (7) by putting in place robust safeguards to maximize its benefits and lessen its potential harm and (8) by implementing a robust quality assurance to assess its impact on overall research quality. Originality/value In the current race for more AI in scholarly communication, this paper advocates for a human-centered oversight of AI-powered peer review. Eroding the role of humans will create an undesirable situation where peer review will gradually metamorphose into an awkward conversation between an AI writing a paper and an AI evaluating that paper.

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ESR Journals editors’ joint statement on Guidelines for the Use of Large Language Models by Authors, Reviewers, and Editors

Cited by 2 publications

References 8 publications

Artificial Intelligence and Submissions to Annals of Plastic Surgery

Artificial Intelligence and Submissions to Annals of Plastic Surgery

AI-powered peer review needs human supervision

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