AI in Peer Review
Abstract
The text discusses the integration of artificial intelligence (AI) into the peer review process in scientific publishing. It argues that improving review quality should take precedence over increasing efficiency by emphasizing reviewer training, encouraging authors to critically assess their manuscripts before submission, and ensuring rigorous evaluation of AI systems. The authors also highlight potential risks associated with AI, including cognitive overreliance, bias, inaccurate outputs, and unequal access to technological resources. Finally, they advocate for the transparent, validated, and equitable implementation of AI to strengthen the fairness, rigor, objectivity, and integrity of peer review rather than focusing solely on faster editorial processes.
Fields of Study & Subjects
scientometrics and bibliometrics research
Artificial Intelligence in Healthcare and Education
Academic Publishing and Open Access
Publication details
- Journal / source
- JAMA
- Publisher
- American Medical Association (AMA)
- Volume
- 335
- Issue
- 6
- Pages
- 549–549
- Publication date
- 8 January 2026
- Language
- EN