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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchJournals should require authors to disclose meaningful AI assistance, keep authorship and accountability with people, and explain how disclosure works. Universities should set minimum standards for verification and data protection. Both should tell researchers to check the rules of the journal, funder, sponsor, discipline, and data provider involved in each project. There is no single disclosure threshold or rule for every AI task, so policies need to distinguish uses and make their requirements clear.
What should an AI-use policy answer?
A useful policy gives researchers, editors, reviewers, and university staff clear answers to five questions:
- Which uses of AI must be disclosed, and where?
- Can an AI system be named as an author, and who is responsible for its output?
- What research or manuscript information may be entered into an AI tool?
- May editors and reviewers use AI when handling confidential submissions?
- Which rule applies when journal, university, funder, sponsor, or data-provider requirements differ?
Policies should also say which tasks they cover. AI use may involve manuscript writing or editing, translation, image and graphic production, coding, data collection or analysis, literature synthesis, or idea generation. A rule that addresses only drafting text can leave important research activities unclear.
What AI use should authors disclose?
Set a clear threshold and a useful level of detail
ICMJE recommends that journals require authors to disclose at submission whether they used AI-assisted technologies in producing the submitted work. COPE calls for disclosure of the tool and how it was used when AI contributes to manuscript writing, images or graphical elements, or data collection and analysis. Elsevier calls for a separate declaration for the manuscript-preparation uses covered by its policy.
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These policies support transparent disclosure, but they do not establish one universal threshold for every journal or every low-impact task, such as routine spelling correction, translation, or brainstorming. Each journal should define its threshold, covered tasks, and required format rather than assume authors can infer them.
Make the disclosure informative
A practical journal declaration can ask authors to provide:
- The AI tool and version, if known.
- The task it performed and the part of the research or manuscript it affected.
- What the authors checked or changed before using the output.
The journal should specify whether the statement belongs in the submission form, methods, acknowledgments, or a dedicated declaration. It should use the same instructions on its website and in its submission system so editors can find and process disclosures consistently.
Can ChatGPT or another AI tool be an author?
No. ICMJE and COPE say AI tools should not be listed as authors. Authorship carries responsibility that a tool cannot accept. ICMJE explains that chatbots cannot take responsibility for accuracy, integrity, and originality in the way authors are expected to do.
Human authors remain accountable for every claim, reference, data statement, figure, code contribution, and interpretation in the paper, including material generated or revised with AI. A disclosure identifies the tool’s role; it does not transfer responsibility to the tool.
How should authors verify AI-generated work?
Authors should treat AI output as material to check, not evidence that a claim is true or that an analysis was performed correctly. Columbia warns that AI may produce citations to nonexistent papers and authors, as well as accounts of experiments that never occurred. MIT identifies fabricated or falsified data, results, or citations as unacceptable. Elsevier says authors must review and verify generated output and that the final manuscript must reflect their own analysis, interpretation, and scientific judgment.
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Verification should match the task:
- References and claims: Confirm that each cited source exists, supports the statement, and is represented accurately.
- Data and analysis: Check the underlying records and independently validate calculations or analytical outputs where appropriate.
- Images and code: Compare outputs with original records, check that they have not distorted or misrepresented the research, and review code before relying on its results.
- Methods and reporting: Ensure the manuscript describes what researchers actually did and does not imply that AI-generated text, results, or summaries are experimental evidence.
What information may researchers enter into AI tools?
Universities should warn researchers not to enter confidential, proprietary, unpublished, restricted, or otherwise controlled research information into tools that have not been approved for that use. Columbia’s policy covers unpublished research, confidential information, peer-review manuscripts and proposals, and participants’ personal information. Penn highlights the need to check consent and IRB requirements before exposing participant data to AI. George Mason calls for a protected environment when sensitive data is involved, while Northeastern describes a review process for certain confidential, restricted, or personal information.
Before using a tool with research material, researchers should check the applicable consent terms, IRB conditions, data-use agreements, contracts, law, and intellectual-property timing. They should consult their institutional privacy or security office when the data classification or tool approval is unclear. Anonymization or a vendor setting that says data will not be used for training does not, by itself, resolve every legal, ethical, contractual, or security concern.
What rules should editors and peer reviewers follow?
Editors and reviewers handle unpublished work under confidentiality duties, so journal AI policies should address their use explicitly. ICMJE says journals should have an AI-use policy and make editors, reviewers, and authors aware of it. Its reviewer guidance says reviewers must request journal permission before using AI to facilitate review, and that confidential manuscripts should not be uploaded where confidentiality cannot be assured.
A journal should state whether AI assistance is permitted in review, whether permission is required, what information may be submitted, and whether reviewers must disclose their use. It should also explain how confidentiality and deletion are handled. Universities should remind faculty that review invitations, grant applications, and unpublished manuscripts may carry duties to the organization that supplied the material.
How should university and journal rules fit together?
A university policy should establish minimum standards for integrity, human accountability, and data protection. Researchers should then check the requirements that apply to the specific work: the destination journal, discipline, funder, sponsor, institution, contract, and any participant-consent or data-provider terms. Columbia directs researchers to consider journal, funding-agency, and professional-society policies; MIT also identifies sponsor, peer-review, journal, and university requirements.
When requirements overlap, policies should direct researchers to meet the stricter applicable rule rather than assume that one institution’s permission overrides another party’s conditions. Because journal policies and tool terms can change, authors should check the actual destination journal at submission time, not rely only on a general university FAQ or an old submission checklist.
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How can policy makers compare rule options?
The sources do not establish a single policy model or rank the options below. These are practical design choices that journals and universities should resolve openly.
| Policy choice | Options to define | Practical consideration |
|---|---|---|
| Disclosure threshold | All AI use, substantive assistance only, or task-specific categories | Broad disclosure can improve transparency, but unclear categories may burden authors and make consequential contributions harder to identify. |
| Disclosure location | Submission form, methods, acknowledgments, or a dedicated statement | Choose a predictable place and align the journal website, form, and editorial workflow. |
| Covered tasks | Writing and editing alone, or also translation, coding, literature synthesis, image generation, data analysis, and ideation | COPE expressly addresses writing, images, data collection, and analysis; policies should say whether other research tasks are covered. |
| Peer-review use | Prohibit AI assistance, permit it in approved environments, or require editor authorization and reviewer disclosure | Confidentiality and the handling of submitted content should guide the choice. |
| Data-risk controls | Prohibit sensitive inputs, or require tool-specific review and approved secure environments | Institutions need clear data classifications and a process for approving tools and environments. |
| Enforcement and correction | Define how nondisclosure or fabricated content is handled | Use proportionate correction and investigation procedures linked to existing integrity rules. |
What should a policy say in practice?
A concise policy can turn these principles into instructions people can follow. For example:
Authors must disclose AI assistance covered by this journal’s policy, identifying the tool and its role in the work. AI systems must not be listed as authors. Human authors are responsible for verifying all submitted content, including references, analyses, images, and code. Do not enter confidential, unpublished, personal, or otherwise restricted information into an AI tool unless the relevant institution and data terms permit that use. Editors and reviewers must follow this journal’s rules for AI assistance and protect the confidentiality of submitted material. Authors must also follow applicable university, funder, sponsor, discipline, contract, consent, and data-provider requirements.
That sample is a starting point, not a universal standard. A journal should define which uses trigger disclosure, where the statement belongs, and what permission or safeguards apply to editors and reviewers. A university should provide a route for resolving uncertain data and security cases, while requiring researchers to check local and destination-specific rules.
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