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Tell readers when AI materially shaped published content or supplied synthetic material. Explain what the system did, identify the affected image, audio, video, text or process, and place the notice beside it where practical. A disclosure is not a claim that the content is accurate: journalists and editors remain responsible for verification and publication.
What a useful AI disclosure tells readers
A reader-facing notice should make the editorial choice legible, not merely announce that a newsroom uses AI. It should answer four questions:
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- What did AI do? Say whether it generated, altered, translated, transcribed, enhanced or otherwise assisted with the material.
- What does the notice cover? Identify the specific image, passage, voice, video or other element—or describe the process involved.
- What human responsibility applies? Briefly explain relevant review and make clear that the newsroom remains responsible for what it publishes.
- Where is more detail available? Link to a policy or provenance information when useful, without making readers hunt for the basic explanation.
For example, a notice might say: “This illustration was generated with AI to accompany our report; it depicts no actual scene. Editors reviewed it, and the newsroom is responsible for its use.” Adapt the wording to the actual workflow; do not imply review guarantees that every detail is error-free.
Set a clear threshold in newsroom policy
There is no single disclosure formula prescribed across the policies and guidance cited here. Newsrooms make different choices about which uses are material, which are prohibited, and how notices fit each medium. A policy should define its threshold rather than treating every AI touch as equivalent.
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Material involvement in published content
The Associated Press’s newsroom standards, updated July 23, 2026, set disclosure standards when generative AI plays a material role in published content. They also say that AI-generated or manipulated material included in AP journalism must be clearly identified and presented in context. AP permits AI support for selected tasks when journalists review and edit the output, but continues to prohibit generative AI from creating, altering or enhancing news photography. This is one policy example, not a universal rule that every newsroom must adopt. AP newsroom standards update
Uses restricted more tightly
The BBC says generative AI should not directly create published or broadcast BBC News/Nations, current affairs or factual journalism except when AI is the subject and its use is illustrative. Where qualifying techniques are used, the audience should be signalled appropriately. The guidance calls for clear disclosure of synthetic voices and active monitoring and human editorial oversight of AI-supported editorial work. BBC guidance on the use of artificial intelligence
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Different thresholds across formats
UK examples illustrate how thresholds and placement can vary. A House of Commons Library briefing dated January 20, 2026, reports that GB News promises verbal or visual disclosure when AI has been used substantially for broadcast content. It also quotes the Guardian’s rule that exceptional, approved use of AI-generated text or images must be signalled on the article itself. These are examples of distinct newsroom approaches, not one shared standard. House of Commons Library briefing on AI content labelling
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When a synthetic element appears in a story, place its explanation at or immediately beside it if practical. A vague outlet-wide footer can leave readers unsure which item is synthetic or altered. Ars Technica advocates proximity between synthetic media and its disclosure; BBC guidance calls for audience signalling appropriate to the technique. Ars Technica’s newsroom AI policy BBC guidance on the use of artificial intelligence
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- Images: Put the explanation in the caption or directly beside the image, and distinguish an illustrative synthetic image from a documentary photograph.
- Audio and broadcast: Use an audible notice or an on-screen label suited to the format. A generated voice can be detached from surrounding context, so a notice should travel with the audio when feasible.
- Text: Identify the passage or describe the material AI role when that role crosses the newsroom’s stated disclosure threshold.
- Reconstruction or alteration: Explain what was reconstructed or changed so the audience does not mistake it for an untouched record of an event.
A fully synthetic image presented as a scene from a real event can create a different impression from routine spelling correction. The notice should reflect that difference rather than using a generic label for both.
Keep disclosure separate from verification
A label explains how material was made; it does not establish whether a report is true. AP says AI does not replace reporting, sourcing, judgment or verification, and requires journalist review of AI-supported output. Reuters likewise requires its journalists to independently verify AI-generated facts, sources and claims, and says Reuters remains responsible for the content it publishes. Reuters Journalistic Standards
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Accordingly, avoid language that makes “AI-generated,” “AI-assisted” or “human-reviewed” sound like a trust or accuracy certification. Explain the newsroom’s actual review where relevant, but keep sourcing and fact-checking obligations intact.
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Use technical provenance as a supplement
C2PA Content Credentials can record provenance in tamper-evident, cryptographically signed manifests. Its implementation guide describes machine-readable source classification, a dedicated AI disclosure assertion, the ability to localize modifications to image regions, document passages or audio/video segments, and records of creation and editing actions. Those details can support a more precise account of an asset’s history. C2PA implementation guide for Content Credentials
Provenance metadata is not a substitute for a visible, understandable notice. It does not prove that a claim is true, and the cited guidance does not establish that every reader or platform will see the records or that metadata will survive every distribution path.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Account for legal obligations in the relevant jurisdiction
The European Commission says the AI Act’s Article 50 transparency obligations apply from August 2, 2026. Its code of practice is a voluntary compliance tool, while the underlying transparency requirements are legal obligations. The described code addresses provider-side marking and detection, as well as deployer-side labelling of deepfakes and certain AI-generated or manipulated text. Which duties apply to a particular publisher depends on its role, the content and applicable law; the Commission’s overview is not a blanket legal conclusion for every newsroom. European Commission: Code of Practice on Transparency of AI-Generated Content
Choose a policy readers can understand
Before standardizing a label, editors can assess the relevant choices against these questions:
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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 match- Threshold: Does disclosure apply to every AI touch, material involvement, or only synthetic content shown to readers?
- Content and risk: Is the use text assistance, a generated image, an altered documentary image, a synthetic voice, video, reconstruction or user-submitted media?
- Placement and format: Does the explanation belong beside a paragraph or image, in a caption, as an audible notice or as an on-screen label?
- Specificity: Can the notice name what was generated, modified, translated or otherwise assisted?
- Accountability: What human review occurred, who owns the final editorial decision, and what does the label not promise?
- Law and provenance: Which jurisdiction and newsroom role matter, and will machine-readable provenance be created and preserved?
Audience testing can reveal whether a notice is clear and useful. A 2026 CHIWORK workshop paper, Designed by Journalists, but Is It for Readers?, reports that an existing controlled experiment included 34 news readers. The paper summarizes detailed disclosure as potentially reducing trust and one-line disclosure as potentially leaving an information gap; it also reports reader-suggested designs including detail-on-demand, proportional AI-ratio visualizations, outlet-level signals and explicit “no AI” labels. This limited workshop-paper evidence is not a population-wide finding or a universal design prescription. CHIWORK ’26 paper: Designed by Journalists, but Is It for Readers?
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