How to Report the Use of Artificial Intelligence in Scientific Articles: A Scoping Review and Taxonomy of Editorial Policies
DOI:
https://doi.org/10.37226/rcp.v10i1.17451Palabras clave:
artificial intelligence, transparency, editorial policies, scientific integrity, disclosureResumen
Objective. This study maps and synthesizes, for the period 2023–2025, the policies and guidelines that require or recommend disclosure of artificial intelligence (AI) use in scientific manuscripts. It also introduces a practical taxonomy of disclosure elements with bilingual (EN/ES) templates readily available for authors and editors. Method. A scoping review was conducted in accordance with PRISMA-ScR and PRISMA-S standards. A multi-source search was performed across organizations such as ICMJE, COPE, and WAME; major publishers including AAAS/Science, Nature/Springer Nature, Elsevier, IEEE/ACM, Taylor & Francis, and Wiley; journals and portals such as PLOS; and sector-wide resources including STM and EQUATOR. The analysis covered materials published between January 1, 2023, and October 21, 2025. Official editorial policies, position statements, and public guidelines were included, while individual opinions without institutional endorsement were excluded. Results. A core consensus was identified emphasizing that AI cannot be listed as an author, that its use must be transparently disclosed with non-delegable human responsibility, and that confidentiality prohibits uploading manuscripts or data to non-approved AI services, particularly during peer review. However, operational differences remain regarding where to place the disclosure, the required level of detail—such as the tool and version used, prompts, and verification—and the treatment of images or code, which face strict restrictions in several publishing houses. To harmonize these criteria, the AI Use Disclosure for Research Articles (AI-Use-12) is proposed as a standardized 12-item reporting framework. Conclusions. It is recommended that journals adopt a formal “AI Use Disclosure” section and design editorial workflows that complement rather than replace human judgment with automated detectors of variable accuracy. Comparative tables, a timeline, a checklist, and declaration templates aligned with current editorial policies are provided.
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Derechos de autor 2026 Juan Aníbal González-Rivera
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
