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Disclose AI use wherever your employer, client, funder, or publisher requires it, and make the statement specific enough for a reader to understand what the tool did and what a human did afterward. Name the tool and model or version, explain the purpose and affected sections, give dates when required, describe your review, and state that a human accepts responsibility for accuracy, originality, attribution, and integrity. Put research or analytical use in the methods or equivalent section; put editing assistance in an acknowledgment or author note; label generated figures or tables at their point of use; and complete any cover letter or submission form. Keep a private record of prompts, inputs, outputs, settings, source checks, and edits, while keeping confidential or unpublished material out of tools that cannot protect it.
What does responsible AI disclosure in a professional report require?
A responsible disclosure answers five questions: which tool was used, for what purpose, which content it affected, when and how it was used, and what human review took place. The report’s named authors remain accountable; an AI system is not an author, coauthor, primary source, or substitute for professional judgment. The ICMJE, APA, and CDC all place responsibility for the final work on people, including its accuracy, originality, attribution, and integrity.
Disclosure is not a disclaimer that transfers liability to software. It is an audit trail that lets a reader, editor, client, or regulator distinguish machine assistance from human decisions. If no AI materially affected the report, do not add a performative statement. If a tool generated wording, analysis, code, a table, an image, or a research step, describe that use even when the final text was heavily edited.
Where should an AI-use statement go?
Place the statement next to the part of the workflow it describes, then repeat it in a required submission channel if a policy asks for that. Placement should make the disclosure visible without forcing readers to infer which figures, methods, or passages were machine-assisted.
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Research, analysis, or code
Describe methodological use in the Methods, methodology, technical appendix, or equivalent section. Explain the prompts or task specification, input types, settings, iterations, validation, and limitations so another qualified person could understand or reproduce the process. JAMA Network specifically expects reproducibility detail for methodological use, including discussion of bias, inaccuracy, privacy, copyright, and generalizability.
Editing, translation, or language polishing
Use an acknowledgment or author note when a system corrected grammar, reorganized prose, translated text, or suggested stylistic changes without generating the underlying analysis. Some publishers distinguish these limited checks from substantive generation. Elsevier exempts basic spelling, grammar, and punctuation checks from its separate declaration, but an employer or client may set a stricter threshold.
Generated figures, images, tables, or code
Label the affected figure, table, code listing, or caption at its location, in addition to any general statement. Identify whether the system generated, transformed, completed, or merely formatted the item. Record the source material and rights review; a polished output is not evidence that it is factually correct, licensed, or free of unwanted resemblance.
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Complete a cover letter, checklist, or submission-form field when the recipient requires one. A statement buried in the report does not replace a mandatory declaration in a journal portal or procurement process. Keep the wording consistent across the report and the submission record, while supplying extra metadata when the form requests it.
What details should an AI disclosure include?
Use the shortest statement that still identifies the material facts. A reviewer should be able to tell what changed because of the tool and what the human team checked.
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- Tool and developer: give the product name and its developer or provider.
- Model or version: include the model name, release, or version available at the time; if the interface did not expose one, say that the interface did not display a version rather than guessing.
- Dates: provide the dates of use when the governing policy asks for them, especially for work that may need to be reproduced later.
- Purpose: state whether the system edited language, drafted text, summarized material, translated, generated code, analyzed data, created a visual, or supported another task.
- Affected content: identify sections, figures, tables, code, analyses, appendices, or other deliverables.
- Human oversight: say that named authors or reviewers checked, verified, and edited the output and accept responsibility for the final report.
- Validation: for analytical or methodological use, describe tests, source checks, calculations, comparison with authoritative material, and treatment of errors or uncertainty.
- Rights and privacy review: state that inputs and outputs were checked for confidentiality, personal or protected information, copyright, attribution, and publication rights when relevant.
Do not claim that an output was tested, fact-checked, or reviewed if that did not happen. A precise account of limited review is more credible than a broad assurance.
How do major professional policies differ?
Policies use different thresholds and locations, so the report owner’s rules control when they conflict. The comparison below summarizes the named guidance and identifies points that each source does not specify.
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|---|---|---|---|---|---|---|
| ICMJE | Disclose whether and how AI was used; an exemption threshold is not stated in the ICMJE guidance. | Manuscript disclosure is required; an exact section is not stated in the cited guidance. | Use details are required; retention or submission of full prompts and outputs is not stated. | Human review must address accuracy and plagiarism; quoted material requires appropriate citation. | Confidentiality safeguards are required; separate image, code, and data rules are not stated in the cited guidance. | Follow the destination journal’s current instructions; an additional cover-letter field is not stated. |
| Elsevier | A separate declaration covers AI used in manuscript preparation. Basic spelling, grammar, and punctuation checks are exempt. | Use the publisher’s separate AI declaration in the manuscript workflow. | Record the tool, purpose, oversight, and supporting records; exact retention duration is not stated. | Describe human oversight and review of the output. | Check the tool’s confidentiality, retention, training, copyright, and output-use terms; media-specific limits depend on the destination policy. | Complete any journal submission fields that request the declaration. |
| APA | Generative AI that drafts a manuscript requires disclosure and citation; a separate exemption for ordinary proofreading is not stated in the cited policy. | Possible locations include the introduction, author note, Methods, or the relevant figure or table location, depending on use. | Citation and use description are required; submission of full prompts or outputs is not stated. | Authors remain responsible for the final text and its sources. | Follow applicable privacy, copyright, and publication-rights rules; detailed media restrictions are not stated in the cited policy. | Publisher or institution instructions determine whether an additional form is required. |
| JAMA Network | Methodological and content-generating use should be described; a separate grammar exemption is not stated in the cited guidance. | The exact section is not stated in the cited fields; place details where the method or affected content can be evaluated. | Provide tool name, version, manufacturer, dates, affected content, and a responsibility statement. | Methodological use should be reproducible and address bias, inaccuracy, privacy, copyright, and generalizability. | Risk analysis includes privacy and copyright; specific image or code permissions are not stated in the cited fields. | Use any journal checklist or submission field in addition to the report statement. |
| CDC guidance published October 21, 2026 | Describe the content affected, action taken, tool, purpose, and human oversight; a grammar-only exemption is not stated. | Use accessible labeling; an exact section is not stated. | Include reproducibility details appropriate to the use, including prompts or settings when they are needed to understand the method. | State the human review and responsibility; disclose limitations such as possible error or bias when relevant. | Do not put sensitive information into public tools; protect personal, protected, confidential, and unpublished material. | Follow the receiving organization’s checklist or form; an additional CDC-specific cover-letter field is not stated. |
These policies are not interchangeable. A journal may require more metadata than an employer, while a client contract may prohibit any external processing even when a publisher permits language assistance. Check all applicable rules before delivery, not only the policy of the final publication.
How can I document prompts, outputs, and edits for an audit?
Keep a private evidence package that connects each significant AI action to the report version it influenced. The package should be readable by a reviewer who did not watch the work happen.
- Identify the governing rules. Before opening a tool, collect the current employer, client, funder, regulator, and publisher instructions. Note the strictest rule that applies to the material.
- Check the tool terms. Confirm whether prompts and files are retained, used for training, reviewed by people, transferred across regions, or covered by an enterprise confidentiality commitment. Check who receives rights in generated output.
- Create a use register. For every material interaction, record the tool and developer, model or version, access mode, date and time zone, operator, purpose, affected section, and report version.
- Preserve the prompt and inputs. Save the exact prompt, attached instructions, data description, and relevant settings. For sensitive work, record a redacted or synthetic description instead of retaining prohibited content.
- Preserve the output. Keep the returned text, code, image, table, or structured result in its original form, along with any regeneration or iteration that materially changed it.
- Record human changes and checks. Use tracked changes, annotated drafts, diffs, or a review log to show what was accepted, rewritten, rejected, or independently recalculated. Link each factual claim and citation check to the source or test result.
- Lock the final package. Store the register, source checks, review notes, rights assessment, and final disclosure with access controls. Recheck the current policy immediately before submission and record the date of that check.
A practical register can use these fields:
| Field | What to record |
|---|---|
| Identity | Tool, developer, model or version, account or access mode, operator |
| Timing | Date, time zone, and report or draft version |
| Purpose and scope | Task, affected section, figure, table, code, or analysis |
| Inputs and settings | Prompt, file or data type, system instructions, temperature or other exposed settings, and iteration number |
| Output | Original response or artifact, including errors that were discarded |
| Review | Reviewer, checks performed, sources consulted, calculations rerun, and changes made |
| Risk and rights | Confidentiality decision, personal-data handling, copyright or license review, and unresolved limitations |
What is the safest workflow before, during, and after AI use?
The following sequence prevents a disclosure from becoming an after-the-fact guess.
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Before using a tool
- Classify the material: public, internal, confidential, personal, protected, client-owned, or unpublished.
- Obtain permission where a contract, ethics process, data-use agreement, or client instruction requires it.
- Decide whether the task can be completed with a local, approved, or non-generative method instead.
- Define what human expertise must remain in control, such as interpretation, recommendation, diagnosis, legal conclusion, or publication decision.
While using a tool
- Minimize inputs and remove names, identifiers, trade secrets, unpublished results, and other sensitive details unless the approved environment protects them.
- Use a prompt that states the task, boundaries, source material, output format, and uncertainty requirements without asking the system to invent evidence.
- Save the exact interaction and settings as you work rather than reconstructing them later.
After receiving an output
- Verify every factual assertion, citation, quotation, calculation, code result, table value, and image detail independently.
- Check for fabricated references, subtle changes in meaning, biased framing, missing caveats, privacy leaks, and copyrighted or recognizable material.
- Run code and calculations in an approved environment, compare outputs with known cases, and document failures as well as passes.
- Rewrite where needed so the final voice, reasoning, and attribution are genuinely the authors’ own.
How should analytical or methodological AI use be explained?
Methodological use needs more than a sentence saying “AI assisted the analysis.” Explain the role of the system in the chain from input to conclusion.
Describe the input and transformation
State whether the system classified, extracted, coded, translated, summarized, generated hypotheses, wrote code, or performed another operation. Identify the input type and preprocessing, while avoiding disclosure of protected content. Explain which parts were automated and which remained human decisions.
Describe validation
Give the tests or comparisons that support the output: independent recalculation, sample review, benchmark cases, source verification, duplicate coding, or expert adjudication. Report material errors and how they were corrected. If no formal test was performed, say that the output received human review rather than implying a stronger validation.
Discuss limitations
Address likely bias, hallucinated or inaccurate content, sensitivity to wording, uneven performance across populations or languages, privacy exposure, copyright uncertainty, and limits on generalizing results. A model’s confidence display is not a substitute for evidence.
How should confidential or unpublished material be handled?
Do not paste confidential client information, personal data, protected health or research information, trade secrets, or unpublished results into a public tool unless an authorized agreement clearly protects that use. ICMJE, Elsevier, and CDC guidance all emphasize confidentiality, and CDC specifically advises keeping sensitive information out of public tools.
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Use data minimization, redaction, access controls, and approved enterprise or local environments where available. Check retention, training, human-review, geographic-transfer, deletion, and output-rights terms before uploading anything. If an accidental disclosure occurs, stop using the tool, preserve the relevant record, notify the data owner or security contact under the applicable incident process, and document the corrective action.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What disclosure wording can I adapt?
Adapt the wording to the actual use; replace the bracketed variables with concrete facts and remove any sentence that is not true.
During preparation of this report, the authors used [TOOL AND DEVELOPER, MODEL/VERSION] on [DATES] to [PURPOSE] for [AFFECTED SECTIONS, FIGURES, CODE, OR ANALYSES]. The authors reviewed, verified, and edited the output, checked sources and rights, and take responsibility for the accuracy, integrity, and originality of the final report.For analytical or methodological use, add a second paragraph:
The tool was used with [RELEVANT PROMPTS, SETTINGS, INPUT TYPES, AND ITERATIONS]. Outputs were [VALIDATION, TESTING, OR REVIEW STEPS], and limitations including possible bias or error were assessed.Do not use the second paragraph to imply testing that did not occur. If the tool only corrected spelling, use the destination policy’s grammar-check exemption when it applies, but disclose more extensive rewriting or generation.
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What common disclosure mistakes should you avoid?
- Naming the tool without describing the work: “We used AI” does not identify affected content or purpose. Add the model, dates when required, scope, and oversight.
- Calling the system an author: List human authors only. Attribute ideas, quotations, data, and sources to their actual creators.
- Hiding methodological use in an acknowledgment: Put reproducibility details where readers evaluate the method.
- Keeping no original record: A polished final draft cannot show what the system generated or what the reviewer changed. Preserve prompts, outputs, and annotated versions.
- Uploading restricted material by convenience: A free or familiar interface may retain or reuse inputs. Confirm permission and terms first.
- Checking only prose: AI can alter numbers, citations, code behavior, images, and table logic. Verify each artifact type separately.
- Using one statement for every audience: A client, employer, funder, and journal may demand different fields. Satisfy the most restrictive applicable instruction and complete required forms.
What is the bottom-line standard for professional reports?
Disclose enough that an informed reader can identify the tool’s contribution and the human controls that followed it. Document enough that an authorized reviewer can reconstruct the material interaction, verify the evidence, and see how errors, privacy, rights, and limitations were handled. When rules conflict, protect confidential information first, follow the stricter authorized policy, and ask the report owner for a written decision before submission.
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Frequently Asked Questions
Do I have to disclose a grammar checker in every report?
Not necessarily. Elsevier exempts basic spelling, grammar, and punctuation checks from its separate AI declaration, but that exemption does not automatically apply to your employer, client, funder, or another publisher. Treat rewriting, translation, drafting, or substantive restructuring as a different category and check the controlling policy.
How long should I keep prompts and AI outputs?
There is no universal retention period in the guidance summarized here. Keep the evidence package for the period required by your contract, records schedule, ethics approval, or publisher, and protect it with the same access controls as the report’s source material.
Should an AI system appear in the report’s author list or references?
AI systems should not be listed as authors or coauthors. Cite the underlying human-created source for a quotation, fact, or idea; identify the tool in the disclosure and use a formal software or tool citation only when the applicable style or policy specifically requires one.
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What should I do if a tool has already received confidential client data?
Stop further uploads and preserve the interaction record. Follow the client’s incident-notification and data-protection procedure, ask the tool provider about retention and deletion under the governing agreement, and document who assessed the exposure and what remediation was completed.
How do I disclose an AI-generated figure or table?
Label the specific figure or table where readers encounter it, identify the tool and the type of generation or transformation, and state the human review. Verify the underlying numbers, source attribution, privacy implications, and permission to publish both the inputs and the resulting visual.
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