Examples
Worked examples
- Is an instance
A disclosed, clearly captioned AI-generated illustrative diagram used to explain a concept, with no claim that it depicts an actual experimental result
- Is an instance
An image-integrity screening tool flagging a submitted figure as showing signs of AI generation, triggering an editorial investigation before the paper proceeds
Counter-examples
Looks similar, but isn't
- Not an instance
A real photograph or scan that has been legitimately, disclosedly processed (contrast adjustment, cropping) with standard image-editing software is not a synthetic image
- Not an instance
Using AI to help design a figure's layout, with all underlying data points being real, is not the same integrity concern as fabricating the underlying image content
Editorial commentary
In a publication context, a synthetic image is largely an integrity concern, not a neutral tooling choice. Presenting an AI-generated or artificially fabricated image as a genuine experimental result — a Western blot, a microscopy field, a clinical scan — is treated by publishers and integrity offices as data fabrication, one of the core categories of research misconduct, regardless of whether the underlying scientific claim happens to be true.
What publisher policy actually permits
Policies converge on a sharp line between fabricated results images and disclosed illustrative content. Nature Portfolio’s AI policy states it is unable to permit AI-generated images or video in article content at all, due to unresolved legal and provenance issues, with only narrow exceptions (content that is itself the subject of an AI-focused piece, reviewed case-by-case). COPE’s February 2023 position on authorship and AI tools requires disclosure of generative AI used to produce images or graphical elements, naming the tool and how it was used. SAGE’s journal policy explicitly bars presenting AI-generated images as unique or novel research images — a prohibited use not curable by disclosure.
How this differs from related AI-band terms
- vs. synthetic data: synthetic structured/tabular data has a legitimate, disclosed research use (privacy-preserving analysis); a synthetic image standing in for a real result does not have an equivalent legitimate use once it enters a paper’s evidentiary content.
- vs. AI image generation: image generation is the underlying technical capability; synthetic image, in this entry’s scope, is specifically the integrity question of what happens when generated output is presented as research evidence.
Detection and the paper-mill connection
Publishers increasingly deploy AI-assisted image-screening tools (in-house and shared infrastructure such as the STM Integrity Hub) to flag manipulated or generated images at submission. Systematic, large-scale image fabrication is also one of the recurring signatures investigators look for when identifying a paper mill — coordinated production of fraudulent manuscripts, of which synthetic or duplicated images are a common tell. See also detection tool (AI-generated) for the honest limits of these screening systems.
Also known as
AI-generated image · Generated image
Machine-readable encodings
Use in your systems
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