Responsible Integration of Generative Artificial Intelligence in Clinical and Health Sciences Publishing

Abstract

Generative artificial intelligence (GAI) is rapidly reshaping academic publishing by supporting manuscript preparation, language refinement, literature synthesis, and other scholarly activities. However, its increasing use has raised important concerns regarding authorship, originality, transparency, accountability, and trust in scientific communication. This editorial highlights the evolving principles of responsible GAI use in publishing, including the prohibition of GAI authorship, disclosure of GAI assistance, and continued human oversight. For authors, transparency in reporting GAI use is essential to maintain research integrity. For editors, effective GAI governance requires clear policies, contextual judgement, and recognition of the limitations of GAI-detection tools. Rather than focusing solely on identifying GAI-generated content, journals should promote responsible GAI adoption through education, standardised disclosure practices, and enhanced GAI literacy among authors, reviewers, and editors. As AI technologies continue to advance, maintaining human accountability remains fundamental to preserving the credibility and integrity of scholarly publishing.