Perspectives of Artificial Intelligence Use for In-House Ethics Checks of Journal Submissions

Journal of Korean Medical Science, 2025

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DOI 10.3346/jkms.2025.40.e170
Data confidence 85 high
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Artificial intelligence (AI) has shown its ability to transform academic writing and publishing. It offers significant benefits, including enhancing efficiency, consistency, and integrity, However, these advancements are accompanied by ethical concerns (particularly around authorship, originality, and transparency) and the need for human oversight in peer review and editorial processes. In this study we explore AI for ethics checks in journal submissions. Specific AI platforms-such as YesChat for bias detection, Turnitin's iThenticate for plagiarism, Proofig for image integrity, and GPTZero for AI-generated content-can identify ethical breaches through tailored prompts and queries. Additionally, AI is increasingly used to detect missing or vague ethics statements, conflicts of interest, and citation manipulation by analyzing structured text and databases. AI-enhanced tools like Elsevier's Editorial Manager and Enago Read assist in ensuring compliance with journal-specific ethical guidelines and streamline peer review. Moreover, emerging algorithms, such as CIDRE, have shown promise in identifying abnormal citation behaviors. As AI accuracy improves, these platforms are expected to be integrated directly into submission systems, enhancing research integrity, transparency, and accountability.