Describe what AI contributed, where it contributed it, and what you did with the result. Put that explanation where people encounter the work—or in the platform or publisher’s required submission workflow. There is no single disclosure rule for every creator: legal duties depend on the jurisdiction and content, while platforms, publishers, and professional organizations may set their own requirements.
What should an AI disclosure say?
A useful disclosure is specific enough to tell a reader or viewer what happened without overstating or hiding the tool’s role. One adaptable pattern is:
“I used [tool or model] to [specific task] in [part or element]. I reviewed and [edited, selected, or verified] the result.”
Include the tool or model when it is relevant or required. Be candid about the human work: say what you reviewed, changed, selected, or verified, rather than implying oversight that did not happen. Avoid calling a work “AI-generated” if AI made only a small, isolated contribution; avoid an imprecise “AI-assisted” label if much of the finished work was generated.
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The U.S. Centers for Disease Control and Prevention (CDC) offers a more detailed framework for scientific products: “Content Affected + Action Taken + AI Tool + Purpose of AI Use + Human Oversight.” It is useful to adapt, but it is scientific-product guidance, not a universal legal checklist for creative work.
Examples you can adapt
- Illustration: “I used [tool] to generate the background texture. I selected and retouched the final texture and drew the characters myself.”
- Writing: “I used [tool] to suggest alternate headlines. I wrote and edited the published article.”
- Music: “I used [tool] to generate a backing layer; I performed the vocals and edited the final mix.”
These are examples, not prescribed wording. Adjust them to match the actual contribution and any applicable rules.
Where should the disclosure go?
Choose a placement people can find in the context where the work is encountered, and follow any required platform or publisher workflow. The right format depends on the medium and on whether the disclosure is meant for the audience, the distributor, or both.
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| Disclosure method | Useful for | What to keep in mind |
|---|---|---|
| Short written note or credits/methods entry | Text, publications, and works with a credits or methods section | Place it where readers can reasonably find it; a submission declaration may also be required. |
| Caption or credits note next to the work | Visual art, images, and other displayed work | Keep the notice legible and accessible as text, rather than relying only on an image or icon. |
| Visible or audible cue | Video, audio, performance, or other time-based work | Use a cue appropriate to the format when required or useful; an audible notice may be appropriate for speech or audio. |
| Platform or publisher submission metadata | Distribution workflows that request structured declarations | Complete the current workflow accurately. A private submission field may not serve as a public-facing notice. |
| Machine-readable provenance metadata | Recording origin or editing history when supported | Treat it as supplementary: it can be lost during conversion or reposting and may not meet a visible-notice requirement. |
For scientific products, CDC guidance recommends written disclosure for manuscripts and text, visible labels paired with accessible text for visual content, and verbal disclosure for speech or audio. Those recommendations illustrate format-specific approaches; they do not create a general creative-industry standard.
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Not in every case under one universal rule. Separate the possible sources of an obligation: law, a platform or publisher’s submission terms, professional or organizational guidance, and your own choice to be transparent. A rule for a particular jurisdiction or distribution workflow should not be generalized to all creative work.
European Union: a limited transparency duty, not a blanket label
The European Commission says the EU AI Act’s Article 50 transparency obligations apply from 2 August 2026. Its Code of Practice is voluntary compliance guidance; the underlying legal obligations are not voluntary for actors and situations covered by Article 50.
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For deployers, Article 50(4) disclosure concerns two specified categories: deepfake image, audio, or video content that resembles real people, objects, places, entities, or events and falsely appears authentic; and AI-generated or manipulated text published to inform the public on matters of public interest, where there has been no human review or editorial control and no person has assumed editorial responsibility. This is not a duty to label every creative use of AI.
For deepfake content that is part of an evidently artistic, creative, satirical, fictional, or analogous work or programme, the Commission says disclosure should be appropriate and should not hamper the work’s display or enjoyment. For the specified public-interest text, the Commission says the disclosure duty does not apply where there has been human review or editorial control and a natural or legal person holds editorial responsibility.
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United States: copyrightability is a separate question
The U.S. Copyright Office’s 29 January 2025 summary addresses whether AI-related material can qualify for copyright protection, not whether creators generally must disclose AI use. It says protection can apply when a human determines sufficient expressive elements, including through human-authored expression perceptible in the output or creative arrangement or modification. Mere prompting is not enough, while AI assistance or the inclusion of AI-generated material in a larger human-created work does not by itself bar copyrightability.
Do not treat a copyright analysis as a disclosure rule. Whether to disclose may instead be determined by another applicable law, a publisher or platform policy, or a voluntary transparency choice.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do platform rules affect disclosure?
A platform may ask for a structured declaration even where a public-facing label is not required by the specific legal rule being considered. Use the platform’s current instructions for the relevant account, content type, and distribution method.
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YouTube music partner deliveries
YouTube’s guidance for music partners provides generative-AI classifications through DDEX or CSV delivery metadata: “Fully Gen AI,” “Partly Gen AI,” and “No Gen AI.” Its examples include fully generated songs; partly generated arrangements; recorded vocals over generated layers; AI-assisted lyric or melody development later recorded in a studio; and AI-generated visuals accompanying fully human-performed audio. The guidance lists routine pitch correction and AI mastering as “No Gen AI” examples.
These categories apply to the described music-partner delivery workflow. They should not be assumed to govern every YouTube upload or another platform’s rules. Check the current delivery documentation and your account workflow before submitting.
What counts as AI-generated versus AI-assisted?
There is no single definition in the sources here that settles every medium or platform’s terminology. For a clear disclosure, describe the contribution itself: which element was affected, what the tool did, and how you used the output. The amount and role of generated material matter more than a broad label standing alone.
- Substantial generation: If the tool created most of the song, image, scene, or other central element, say so rather than reducing the role to vague “assistance.”
- One component: If AI produced a particular layer, texture, visual, or passage in a larger work, name that part.
- Assistance in development: If AI suggested or developed material that you then recorded, rewrote, selected, or substantially changed, describe both the tool’s contribution and your actions.
- Routine processing: A platform may define certain operations differently from a creator’s everyday use of “AI.” Follow the relevant platform’s examples and definitions for its workflow.
Can provenance metadata replace a visible notice?
No—not where a visible or audible notice is required. OpenAI describes C2PA Content Credentials as a way to carry information about origin and history, such as the tool and creation time, but says those signals can be lost through ordinary actions such as screenshots or file conversion. It also describes watermark signals whose coverage varies by product, model, export path, file type, and creation date. OpenAI explicitly says provenance signals do not replace visible labels, banners, or notices that may be required.
Use provenance metadata as a supplement when available, not as proof that an audience or distributor will always be able to detect the work’s history.
A practical disclosure check before release
- Identify the contribution. Record what AI generated, transformed, or helped develop, and which parts of the finished work it affected.
- Check the applicable rules. Review the relevant jurisdiction’s requirements, plus the current submission terms for the publisher, platform, distributor, contest, or other route you plan to use.
- Write a specific statement. Name the task and affected element; identify the tool or model when relevant or required; explain the purpose if useful; and state accurately what you reviewed or changed.
- Put it in the right place. Make an audience-facing notice accessible in the work’s context when appropriate or required, and separately complete any structured submission fields.
- Check the delivered version. Confirm the notice remains legible or audible in the format people receive. Do not assume that metadata or a watermark will survive editing, conversion, or reposting.
Requirements can also come from national laws and organization-specific rules beyond the EU and U.S. examples discussed here. For consequential legal exposure, identify the creator’s location, intended audience markets, medium, and distributor, then consult the relevant primary rules.
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