Toward Structured Transparency: A Governance Framework for AI Use in Biomedical Publishing
TL;DR
It is argued that medical publishing should move from a restrictive approach toward a framework of structured transparency that systematically documents, evaluates, and verifies AI use and is proposed a practical governance framework that includes a three-tiered AI disclosure system.
Abstract
The rapid adoption of large language models and generative artificial intelligence (AI) is transforming biomedical research and publishing. Although international organizations such as the International Committee of Medical Journal Editors (ICMJE) and the Committee on Publication Ethics (COPE) have established the principle that AI cannot be recognized as an author, and the ICMJE, in its January 2026 revision, has introduced a dedicated section addressing AI use by authors, peer reviewers, and editors, journal-level Instructions for Authors still require further operational detail to apply these principles consistently throughout the publication process. This review critically examines current AI-related policies in the Journal of Korean Medical Science (JKMS) and the Korean Association of Medical Journal Editors (KAMJE) and identifies three major challenges: the practical limitations of the AI non-authorship principle, the inadequacy of current AI disclosure practices, and the emergence of AI-specific conflicts of interest that extends beyond conventional financial disclosures. We argue that medical publishing should move from a restrictive approach toward a framework of structured transparency that systematically documents, evaluates, and verifies AI use. To achieve this goal, we propose a practical governance framework that includes a three-tiered AI disclosure system, strengthened accountability for corresponding authors, expanded institutional conflict-of-interest disclosures, transparent reporting of AI use by peer reviewers, and formal editorial policies governing AI-assisted editorial activities. Future revisions of the KAMJE and JKMS Instructions for Authors should prioritize transparent and accountable AI governance rather than restricting AI use. Adoption of a structured, publication-wide framework encompassing authors, peer reviewers, and editors would strengthen research integrity while supporting the responsible integration of AI into biomedical publishing.