Inteligencia Artificial Generativa en la Investigación Académica: Una revisión de literatura desde la ética

Le résumé fourni par la source

The objective of this study was to analyse recent scientific production regarding the ethics of generative artificial intelligence in academic research, aiming to identify its main challenges, trends, and gaps. Methodologically, a literature review was developed using a systematized selection process and thematic synthesis. The search was conducted in Scopus between January 2019 and November 2024, utilizing the terms "generative artificial intelligence," "research," and "ethics." A total of 20 articles were analysed following the stages of identification, screening, eligibility, and inclusion. The information was organized into an extraction matrix and examined with the support of NVivo 12, employing an inductive-deductive logic. The findings were grouped into four core axes: ethical challenges; governance and regulation; quality, originality, and reproducibility of knowledge; and social and institutional implications. The evidence reveals a rapid expansion of the debate, but also regulatory gaps, poorly standardized criteria, and a limited consolidation of institutional frameworks for the responsible use of these technologies. It is concluded that their ethical integration into academic research demands explicit policies, critical training, and oversight mechanisms guided by principles of transparency, integrity, equity, and institutional responsibility.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.