<scp>AI</scp> ‐Assisted Scientific Figures in Scholarly Publishing: A Risk‐Based Taxonomy by Evidentiary Function
Summary AI‐assisted figures should be assessed by what they claim to represent, not by AI use alone. Existing AI‐image policies may not offer enough granularity for diverse figure types in scholarly publishing. The taxonomy classifies figures as explanatory, analytical, simulated, or evidentiary. Each figure type carries distinct integrity risks and requires proportionate editorial safeguards. Figure‐level classification could improve disclosure, auditability, labeling, and preservation of original observations.
Authors
- Malcolm Koo (ORCID: https://orcid.org/0000-0002-9242-9167)
- Ming‐Chi Lu
Institutions
- University of Toronto (CA)
- Tzu Chi University (TW)
- Public Health Ontario (CA)
- Buddhist Tzu Chi Medical Foundation (US)
Publication Details
- Journal
- Learned Publishing
- Published
- 2026-06-27
- DOI
- https://doi.org/10.1002/leap.2085
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00