AI-generated prose and images can look like scientific support without being supported by verifiable sources, data, or methods. A fluent paragraph is not evidence that its claims or references are correct; a convincing figure is not an observation unless it can be traced to the data and process that produced it. The key distinction is whether AI is a disclosed aid, a reproducible part of a research method, or a source of unsupported material presented as evidence.
Why polished AI output can create false confidence
Scientific work earns confidence through more than clear writing or professional-looking figures. Readers need to be able to check claims against reliable sources and understand how reported results were obtained. Generative tools can produce material that looks complete while leaving those checks unanswered.
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That does not mean every use of AI makes research unreliable. Assistance with expression, a reproducible computational method, and a fabricated or unverifiable result are different uses with different implications. The risk arises when readers are invited to treat generated content as evidence without a traceable basis.
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How AI-generated text can mislead
Fluency is not fact-checking
A coherent sentence may still contain an error, an unsupported interpretation, or a reference that does not substantiate the claim. Springer Nature’s AI Use in Manuscript Preparation policy says authors should ensure content is accurate and references are real and checked. In practice, each material factual statement needs to be checked against the cited primary literature or another authoritative record; polished wording cannot do that work for the reader.
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Authors must retain intellectual responsibility
Springer Nature distinguishes basic assistance from more extensive drafting or restructuring: authors remain responsible for accuracy, disciplinary conventions, checked references, and their own intellectual contribution. It also says argument, interpretation, and conclusions must remain author-led. JAMA Network’s guidance likewise places responsibility on authors who use AI to create, review, revise, or edit manuscript content.
This distinction matters because editing a sentence is not the same as delegating the scientific judgment behind it. Authors should be able to defend the reasoning, interpretation, and conclusions in the submitted work rather than treating a model’s output as an authority.
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When a figure is—and is not—evidence
Explanatory images
Some images explain an idea or process rather than report an observation. Elsevier lists flow charts, decision trees, timelines, schematic conceptual illustrations, and experimental workflow diagrams as examples. Under Elsevier’s policy, generative tools may support some explanatory images with human oversight and disclosure in both the figure caption and a general AI statement.
Data visualizations
A plot, graph, chart, or heatmap can communicate results only if it faithfully represents the underlying data and methods. Elsevier says these visualizations must be directly derived from underlying data through reproducible analytical, computational, or statistical methods. Its policy bars using AI to fabricate results, invent or alter underlying data, or generate a figure that is not faithful to the data and methods. When AI is used for such a visualization, Elsevier says to report the tool’s name, version, and developer or manufacturer in Methods.
Primary research images
Microscopy, histology, western blots, radiology scans, and patient images can represent observed or experimental data. They are not interchangeable with explanatory illustrations: generating or altering one may change what readers believe was observed. Elsevier prohibits generative AI tools from creating or altering primary research images that represent observed or experimental data. Its editors may request documentation and original, unprocessed images.
Graphical abstracts and cover art
Elsevier says general-purpose generative image tools must not be used to create graphical abstracts. AI-created cover art may sometimes be allowed with prior permission from the editor and publisher. These are Elsevier-specific rules; they should not be assumed to apply unchanged at another journal.
How publisher policies differ
There is no single rule that can be applied to every journal or every type of image. The table summarizes the scope of the named policies described here; check the destination journal’s live policy before submission.
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|---|---|---|
| Springer Nature | Its policy allows AI-created, modified, enhanced, or analyzed visuals only under conditions intended to preserve accuracy and integrity. Visual material without independently verifiable data, source material, methods, computational outputs, or author-developed content is considered opaque and not permitted by the policy. | Use should be transparent and lawful. The policy calls for disclosure of the model and purpose, inspectable and attributed inputs, human review, accurate representation of evidence, and attention to rights. Authors remain accountable for submitted work. Policy page accessed October 4, 2026. |
| Elsevier journals | The policy distinguishes explanatory images, data visualizations, and primary research images, with different rules for each. It also sets limits for graphical abstracts and cover art. | Some explanatory images require human oversight and disclosure in the caption and general AI statement; AI-assisted data visualizations require tool details in Methods. The policy page was accessed October 4, 2026. |
| JAMA Network | The guidance covers AI tools used to create, review, revise, or edit manuscript content and AI use as part of research methods. | For covered manuscript uses, it requests the software, version, manufacturer, dates of use, portions affected, description of use, and author responsibility, with an exception for basic grammar, spelling, references, and similar checks. Published online March 7, 2024. |
| Nature Geoscience | A June 12, 2024 editorial said that journal did not permit AI-generated images and videos at that time, citing unresolved legal and integrity concerns. It said text assistance was not banned if documented and authors remained responsible. | This is a dated statement about Nature Geoscience, not a rule for every Nature journal or a guarantee of that journal’s current position. |
The policies differ in scope and in what they require authors to disclose. A rule about explanatory artwork, for example, does not establish what is allowed for a microscopy image or a data-derived chart. Springer Nature’s policy asks whether inputs and methods can be inspected; Elsevier sets category-specific image rules; JAMA Network specifies disclosure details for covered manuscript uses. Apply the policy of the actual journal and article type.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to make AI use verifiable
- Check claims and references. Verify material factual statements against the cited literature or authoritative records, and confirm that each reference exists and supports the claim.
- Preserve the basis for figures and analysis. Keep underlying data, original images, source material, methods, and relevant computational or processing records so the work can be assessed. Where applicable, retain prompts or other records that explain how AI contributed.
- Describe the use where the journal asks. Report the tool or model, version, purpose, and extent of its contribution in the location the journal requires, such as Methods, a figure caption, or a general AI declaration. For research-method use, describe the process sufficiently for others to understand and reproduce it; JAMA Network points authors to design-specific reporting guidance where applicable.
- Keep interpretation and accountability with the authors. Review outputs, make the scientific judgments, and take responsibility for the submitted work. A model cannot stand in for an author’s verification or accountability.
- Check the current destination-journal policy. Requirements vary by publisher, visual type, and use, and policies can change. Confirm the live instructions for the journal and submission category rather than relying on a policy from another title.
What the available evidence does not establish
The cited publisher policies explain risks and requirements, but they do not establish how often AI-generated material appears in published papers or measure how often it causes scientific harm. They also do not provide a documented case chronology linking a particular misleading AI-generated passage or figure to a specific scientific consequence. It would therefore be misleading to attach a prevalence or harm rate to the issue on the basis of these sources.
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