Synthetic Content Labelling and Provenance Plan
In brief
The Synthetic Content Labelling and Provenance Plan is a free XLSX and DOCX procedure for EU AI Act. One labelling design for AI-generated text, images, audio and video: per-feature visible labels and machine-readable marks, with every recorded duty to label, mark or disclose synthetic content. It is licensed CC BY 4.0 and is not legal advice.
- Format
- XLSX and DOCX · Procedure
- Version
- v1, built 5 Oct 2026
- Duties cited
- 22 from 10 instruments
- Rows from the records
- 5
- Frameworks
- EU AI Act
- Written for
- Deployer / user organisation, Provider / developer, Public authority / government body
- Price and licence
- Free · CC BY 4.0
What's inside
- Labelling plan per product feature: visible label, machine-readable marking, standard, markets and detection tests
- Labelling duties sheet across jurisdictions
- Document: design principles, exceptions and a section per duty
Preview
The sheets and sections of version v1, as built. Columns marked ▾ have a dropdown; ƒ is a formula.
Sheet: Labelling plan
| Product feature | Content generated ▾ | Visible label ▾ | Machine-readable marking ▾ | Standard or technique used | Label wording | Markets | Detection tested on | Owner |
|---|---|---|---|---|---|---|---|---|
| Rows are yours to fill; the dropdowns, formulas and colour rules are already in place. | ||||||||
One row per feature that produces synthetic text, images, audio or video. Visible labels tell people; machine-readable marks let platforms and tools detect the content later.
Sheet: Labelling duties
| Duty | Category | Instrument | Jurisdiction | Who it binds | Nature | Source reference | Applies from | What it requires | Evidence a reviewer expects | ISO/IEC 42001 | NIST AI RMF | Verification | Record |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Disclose AI interaction and label synthetic content | Transparency and disclosure | EU AI Act | European Union | Provider / developer, Deployer / user organisation | Legal requirement | Article 50 | 2026-08-02 | Providers must ensure AI systems intended to interact with people inform them they are dealing with AI unless obvious; providers of systems generating synthetic | Disclosure and watermarking design record | Annex A control on communication with interested parties | GOVERN 4.x; NIST AI 600-1 content provenance suggestions | Source-linked | https://aipolicytracker.org/obligations/eu-ai-act-transparency-article-50 |
| Providers of generative AI must mark synthetic output as artificially generated in a machine-readable way | Transparency and disclosure | EU AI Act | European Union | Provider / developer, General-purpose AI model provider | Legal requirement | Article 50(2) | 2026-08-02 | Providers of AI systems, including general-purpose AI systems, that generate synthetic audio, image, video or text must ensure the output is marked in a machine | Provenance marking design and robustness test report; Output sample with embedded machine-readable mark | Annex A.8.2, A.6.2.4 | MEASURE 2.7, MANAGE 4.1 | Verified against the official source 26 Sep 2026 | https://aipolicytracker.org/obligations/eu-ai-act-art-50-2-synthetic-content-marking |
| Deployers must disclose deepfakes and AI-generated text published on matters of public interest | Transparency and disclosure | EU AI Act | European Union | Deployer / user organisation, Public authority / government body | Legal requirement | Article 50(4) | 2026-08-02 | A deployer that generates or manipulates image, audio or video content that is a deep fake must disclose that the content has been artificially generated or man | Synthetic media labelling standard; Editorial sign-off record for AI-drafted text | Annex A.9.2, A.8.5 | GOVERN 5.1, MANAGE 4.1 | Verified against the official source 26 Sep 2026 | https://aipolicytracker.org/obligations/eu-ai-act-art-50-4-deepfake-and-public-interest-text-disclosure |
| Report incidents and mark AI-generated content (generative AI framework) | Transparency and disclosure | Singapore Model AI Governance Framework | Singapore | Provider / developer, Deployer / user organisation, General-purpose AI model provider | Voluntary | Generative AI framework, dimensions on incident reporting and content provenance | The generative-AI framework recommends incident-reporting channels and processes for AI harms, and content provenance measures such as digital watermarking and | Content provenance implementation record | NIST AI 600-1 content provenance and incident disclosure | Source-linked | https://aipolicytracker.org/obligations/singapore-mgf-genai-incident-reporting-and-provenance | ||
| AI business operators must label generative AI output and clearly flag realistic synthetic media | Transparency and disclosure | Framework Act on the Development of Artificial Intelligence and Establishment of a Foundation for Trust | South Korea | Provider / developer, Deployer / user organisation | Legal requirement | Article 31(2) and 31(3) | 2026-01-22 | An AI business operator that provides generative AI or a product or service using it must indicate that the output was generated by generative AI. Where the ope | Output labelling design and samples; Synthetic media labelling standard | Annex A.8.2, A.8.5 | MEASURE 2.7, MANAGE 4.1 | Verified against the official source 26 Sep 2026 | https://aipolicytracker.org/obligations/south-korea-ai-basic-act-art-31-generative-output-labelling-and-deepfake-notice |
Recorded duties to label, mark or disclose AI-generated content, across jurisdictions.
Document outline (DOCX)
- Synthetic content labelling and provenance plan
- Design principles
- Exceptions
- Duties, one by one
- Disclose AI interaction and label synthetic content
- Providers of generative AI must mark synthetic output as artificially generated in a machine-readable way
- Deployers must disclose deepfakes and AI-generated text published on matters of public interest
- Report incidents and mark AI-generated content (generative AI framework)
- AI business operators must label generative AI output and clearly flag realistic synthetic media
How to use it
- 1Request the files. Enter your name, company and work email in the form on this page. The XLSX and DOCX download links arrive by email and work for 7 days.
- 2Read the README page. It states the version (v1), the dataset it was built from and the licence, so anyone reviewing your copy knows which records it reflects.
- 3Fill in your rows. Complete the "Labelling plan" sheet for your own systems. Dropdowns, formulas and colour rules are already set.
- 4Check the duties against your situation. The "Labelling duties" sheet lists the recorded duties with their source references. Mark which apply to you and follow each link to the official text.
- 5Complete the document. Work through the DOCX sections (Synthetic content labelling and provenance plan, Duties, one by one) and replace each placeholder with your organisation's answer.
- 6Keep the evidence and watch for new versions. Link each completed row to the evidence that supports it. When the law on record changes, this template gets a new version and a changelog on this page.
Duties this template covers (22)
Each is cited in the file with its source reference and a link back to the record.
- Frontier developers must publish a transparency report before deploying a new frontier model
- Notify consumers before automated decision-making technology influences a consequential decision
- Disclose the use of the technology and the principal reasons after an adverse consequential decision
- Provide deployers with clear instructions for use
- Disclose AI interaction and label synthetic content
- Employers must inform workers and their representatives before using high-risk AI at work
- Deployers must tell natural persons that a high-risk AI system is used in decisions about them
- Providers of generative AI must mark synthetic output as artificially generated in a machine-readable way
- Deployers of emotion recognition or biometric categorisation must inform exposed persons
- Deployers must disclose deepfakes and AI-generated text published on matters of public interest
- Deployers must explain individual decisions taken with high-risk AI on request
- Employers and employment agencies must publish a summary of the bias audit results
Legal basis
Version history
| Version | Built | Dataset | What changed |
|---|---|---|---|
| v1 | c6967b988bb5 | First version, built from dataset c6967b988bb5. |
Only the latest version is served. A rebuild that changes the content adds a version; a rebuild that does not is skipped.
Frequently asked questions
What is in the Synthetic Content Labelling and Provenance Plan?
Labelling plan per product feature: visible label, machine-readable marking, standard, markets and detection tests. Labelling duties sheet across jurisdictions. Document: design principles, exceptions and a section per duty.
Which duties does it cite?
22 recorded duties from California SB 53, Colorado ADMT law (SB 26-189), EU AI Act and NYC Local Law 144 (automated employment decision tools), including Business and Professions Code Section 22757.12 (as added by SB 53), Article 13, Article 50, Article 26(7), Article 26(11) and Article 50(2). Each row links to the record, and the record to the official source.
Who is it for?
The duties it cites fall on deployer / user organisation, provider / developer and public authority / government body. Whoever owns AI governance for those roles usually completes it, with the system owner supplying the facts.
Is it free?
Yes. Request the XLSX and DOCX with your work email on this page; the download links arrive by email, valid for 7 days. No account and no charge. Licensed CC BY 4.0. You may use, adapt and share this template, including commercially, with attribution to aipolicytracker.org.
How will I know when it changes?
Version v1 was built on 5 October 2026. The library is rebuilt daily; when a change to the records reaches this template it gets the next version, a changelog below and an entry in the templates feed.
Does completing it make us compliant?
No. It is an informational resource, not legal advice; it helps produce the evidence a regulator, customer or auditor asks for. Whether a duty applies to you is a judgement the template cannot make.
Disclaimer: informational only, not legal advice. Verify every claim against the linked official sources and consult a qualified lawyer before acting.