ArticleAccountability in research2026
Disclosing artificial intelligence use in scientific research and publication: When should disclosure be mandatory, optional, or unnecessary?
Article in Accountability in research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Comprehensive Consideration of Ethics in AI-assisted Scientific Writing and Peer Review.Journal of Korean medical science · 2026Review
- Guidelines needed for the use of AI in the preparation or review of IRB, IBC, and IACUC applications.Accountability in research · 2026Article
- How ChatGPT writes scientific titles in medical research: structural and content differences compared to human authors.Journal of the Medical Library Association : JMLA · 2026Article
- Un-AI-ing: Compliance, Evasion, and the Distortion of Research Writing in the Age of AI Detection.Annals of biomedical engineering · 2026Article
- Moving from disclosure to substance in AI transparency.Patterns (New York, N.Y.) · 2026Article
- Article
- Autonomous artificial intelligence, scientific research, and human values.AI and ethics · 2026Article
- Use of artificial intelligence tools in the publishing process: expectations from publishers through author guidelines.Frontiers in research metrics and analytics · 2026Article
- The Presence and Nature of AI-Use Disclosure Statements in Medical Education Journals: A Bibliometric Study.Perspectives on medical education · 2026Article
- Artificial Intelligence in Detecting Statistical Errors: Implications for Authors, Reviewers, and Editors.Journal of Korean medical science · 2025Review
- From chaos to symbiosis: exploring adaptive co-evolution strategies for generative AI and research integrity systems.BMC medical ethics · 2025Article
- Artificial intelligence policies in bioethics and health humanities: a comparative analysis of publishers and journals.BMC medical ethics · 2025Article
- Disclosing generative AI use for writing assistance should be voluntary.Research ethics · 2025Article
- Defining the Boundaries of AI Use in Scientific Writing: A Comparative Review of Editorial Policies.Journal of Korean medical science · 2025Review
- Can ChatGPT write better scientific titles? A comparative evaluation of human-written and AI-generated titles.F1000Research · 2025Article
- The Blurred Thresholds of AI-Use Disclosure: Health Professions Education Journal Editors' Expectations of Necessity and Sufficiency.Perspectives on medical education · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Currently there is a broad consensus among scholars that artificial intelligence (AI) tools can be used in research and publication, and that their use should be disclosed. Publishers and influential organizations, like the International Committee of Medical Journal Editors, have developed different and sometimes contradictory disclosure policies. We review some of these policies, examine the ethical reasons for disclosing AI use in research, and develop a framework for disclosure. We distinguish between mandatory, optional, and unnecessary disclosure of AI use, arguing that disclosure should be mandatory only when AI use is intentional and substantial. AI use is intentional when it is directly employed with a specific goal or purpose in mind. AI use is substantial when it 1) produces evidence, analysis, or discussion that supports or elaborates on the conclusions/findings of a study; or 2) directly affects the content of the research/publication. To support the application of our framework, we state three criteria for identifying substantial AI uses in research: a) using AI to make decisions that directly affect research results; b) using AI to generate content, data or images; and c) using AI to analyze content, data or images. Disclosure should be mandatory when AI use meets one of these criteria.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.