The rapid emergence of artificial intelligence (AI) tools is reshaping scientific publishing, including the peer review process that underpins the validation of research. This paper explores how AI can be integrated to enhance efficiency, consistency, and analytical rigor while preserving the central role of human judgment. At the same time, significant risks must be managed, including bias reinforcement, over-standardization, loss of reviewer individuality, and the potential suppression of novel findings. We argue that the evaluative aspects of peer review—particularly judgments of significance, originality, and impact—must remain human-driven. A human-centered, AI-enabled framework is essential to ensure these tools augment rather than replace expert assessment, safeguarding the integrity and creativity that drive scientific progress.
Cann et al. (Wed,) studied this question.
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