Generative Artificial Intelligence and Research Integrity: A Responsibility-Centred Framework

Generative artificial intelligence (GenAI) is increasingly integrated into academic writing, research workflows, and editorial processes, raising fundamental ethical and governance concerns for scholarly publishing. This paper presents an integrative narrative review and conceptual synthesis of a large interdisciplinary corpus of Scopus-indexed literature on AI in academic research, publishing ethics, and editorial decision-making. The study pursues three interrelated aims: to clarify the ethical challenges associated with GenAI across research, peer review, and editorial decision-making; to systematise AI-assisted scholarly practices by distinguishing among integrity-compromising uses, ethically responsible uses, and persistent grey zones in which norms remain contested; and to develop a human-centred, context-sensitive governance perspective to guide authors, reviewers, and editors. The analysis identifies human epistemic responsibility as the central ethical concern, showing that risks arise not from AI itself but from the displacement or obscuring of accountable scholarly judgment. The study contributes a framework for the responsible integration of GenAI into scholarly research and publishing.