AI in Peer Review
Gardado en:
| Autores: | , , |
|---|---|
| Formato: | carta al director |
| Data de Publicación: | 2026 |
| Descripción: | 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. |
| País: | Kérwá |
| Institución: | Universidad de Costa Rica |
| Repositorio: | Kérwá |
| Idioma: | Inglés |
| OAI Identifier: | oai:kerwa.ucr.ac.cr:10669/104911 |
| Acceso en liña: | https://hdl.handle.net/10669/104911 https://www.doi.org/10.1001/jama.2025.22266 |
| Palabra crave: | Artificial Intelligence (AI) Scientific publications Evaluation Quality control Ethics of science Peer review Optimización Editing Scientific information Scientific innovations |