Adhere to OECD 2024 Update transparency requirements for generative AI + content provenance + authenticity. Generative AI transparency for outputs must (a) clearly disclose to users when they are interacting with AI-generated content + AI-personalised content + or AI-augmented content per applicable jurisdiction requirement (EU AI Act Article 50 + similar), (b) maintain disclosure proportionate to the risk + context + and potential for harm of mistaking AI-generated content for human-generated content + (c) implement labelling + watermarking + or other technical measures for AI-generated synthetic media including deepfakes + voice cloning + image manipulation per emerging standards (C2PA Coalition for Content Provenance and Authenticity + W3C standards + similar). Content provenance and authenticity must (a) implement cryptographically verifiable provenance metadata including content origin + creation chain + modifications + AI involvement per C2PA or equivalent standard, (b) preserve provenance through content distribution including platforms + intermediaries + with mechanisms to detect tampering, (c) support downstream verification by users + platforms + journalists + regulators + civil society + (d) integrate with broader misinformation + manipulation + safety + security responses.
This control maps to 19 controls across 9 other frameworks. If you already hold one of them, the evidence you collected for it is the starting point here rather than new work.
Every mapping shown was judged rather than inferred from wording similarity, and the ones that failed review are published too. See the coverage reports and what was rejected.
The graph holds this control, the 19 it maps to, and the evidence behind each claim, over MCP and REST.