AI in Peer Review

 

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Библиографические подробности
Авторы: Chaverri Fernández, José Miguel, Zavaleta Monestel, Esteban, Arguedas Chacón, Sebastián
Формат: carta al director
Дата публикации:2026
Описание: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.
Страна:Kérwá
Институт:Universidad de Costa Rica
Repositorio:Kérwá
Язык:Inglés
OAI Identifier:oai:kerwa.ucr.ac.cr:10669/104911
Online-ссылка:https://hdl.handle.net/10669/104911
https://www.doi.org/10.1001/jama.2025.22266
Ключевое слово:Artificial Intelligence (AI)
Scientific publications
Evaluation
Quality control
Ethics of science
Peer review
Optimización
Editing
Scientific information
Scientific innovations