AI in Peer Review

 

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Bibliographic Details
Authors: Chaverri Fernández, José Miguel, Zavaleta Monestel, Esteban, Arguedas Chacón, Sebastián
Format: carta al director
Publication Date:2026
Description: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.
Country:Kérwá
Institution:Universidad de Costa Rica
Repositorio:Kérwá
Language:Inglés
OAI Identifier:oai:kerwa.ucr.ac.cr:10669/104911
Online Access:https://hdl.handle.net/10669/104911
https://www.doi.org/10.1001/jama.2025.22266
Keyword:Artificial Intelligence (AI)
Scientific publications
Evaluation
Quality control
Ethics of science
Peer review
Optimización
Editing
Scientific information
Scientific innovations