Ethics and integrity in university research supported by artificial intelligence: A systematic literature review

Chiclayo Padilla H.J.; Hilario-Vargas J.; Vela Meléndez L.; Rios Villacorta M.A. · Revista de Ciencias Sociales (2026) · DOI: 10.31876/rcs.v32i2.45589

Resumen

This article analyzes ethical and integrity issues in research using artificial intelligence in university settings. It examines 35 selected articles, selected using the PRISMA protocol for the period between 2020 and 2024, and employing a systematic review method. The results identify three types of problems: i) the erosion of intellectual authorship, systemically promoted by automated plagiarism and content impersonation; ii) methodological fractures resulting from algorithmic opacity, biases, and data distortions; and iii) failed governance, related to regulatory gaps and inadequate protocols for managing artificial intelligence in research. These are signs of a crisis of scientific credibility and reproducibility that generates distrust in scientific knowledge. Current editorial ethics codes are insufficient in the face of emerging automated authorship. Best practices require training in artificial intelligence ethics, institutional policies, human oversight, and algorithmic transparency. It is necessary to establish adaptable regulatory frameworks and an academic culture that integrates artificial intelligence while preserving integrity. Future research should include policy comparisons, university perspectives, and longitudinal evaluations to improve the ethical governance of artificial intelligence research. © Licencia de Creative Commons Atribución 4.0 Internacional (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/deed.es

Instituciones: Universidad Nacional Pedro Ruiz Gallo; Universidad César Vallejo; Universidad Católica Santo Toribio de Mogrovejo