This article explores how the traditional framework of research ethics must be redefined in response to the ethical challenges posed by the academic use of generative artificial intelligence (Gen AI). As Gen AI technologies become increasingly integrated across various stages of research—from study design and data analysis to manuscript writing—they offer notable gains in efficiency, while simultaneously expanding ethical gray areas. In particular, issues such as factual inaccuracies and hallucinations, violations of privacy and copyright, ambiguous authorship, and the deskilling of researchers are becoming increasingly entangled, posing serious threats to the credibility and integrity of academic work. To address these concerns, the article proposes four core ethical principles suited to the Gen AI era: truthfulness and explainability, respect for intellectual property, field-specific guidelines, and the cultivation of researcher competence. The central concern is not merely whether such technologies should be adopted, but rather how the identity and responsibility of researchers, and the sustainability of scholarly communities, can be ethically restructured in the face of transformative technological change.
Kim et al. (Mon,) studied this question.