Anthropic has signed the EU AI Act’s Article 50(2) Code of Practice on Transparency of AI-Generated Content, as a provider of both generative AI models and generative AI systems. This article describes how we’re planning to put those commitments into practice, how marking works, and what its limitations are. We’ll update this article and publish more detailed technical guidance as it becomes available.
Anthropic’s commitments under the EU AI Act’s Code of Practice on Transparency of AI-Generated Content
What our marking commitments mean for Claude:
More details about our marking plans are below.
As AI-generated content becomes commonplace, greater transparency and signals about where content comes from can give people useful context about the information they consume. To support transparency and comply with our legal obligations, Anthropic is working to include machine-readable marks in content that Claude generates.
Claude uses two complementary techniques to mark content generated and processed by Claude: (1) watermarks embedded in text, and (2) signed provenance metadata attached to files.
When a supported Claude model generates text, it weaves an imperceptible watermark directly into the text itself. You won’t see it, and it doesn’t change the meaning, quality, or readability of Claude’s response.
Because the watermark is part of the text, it will travel with the text when it’s copied and pasted elsewhere, and may persist through some editing. Watermarking will be applied at the model level, which means it will be present no matter which Claude product or surface the text comes from.
When Claude generates a supported file type, such as a .svg, .png, or .jpg, it will attach signed provenance metadata. This metadata follows the Coalition for Content Provenance and Authenticity (C2PA) open standard, which is used across the industry to record information about content provenance. If a signed metadata label is present, it signals that a file was processed by Claude and lets you detect whether the file has been tampered with.
We’re also working to enable users and other third parties to detect Claude’s embedded watermarks and provenance metadata. Detection checks whether a piece of text or a file carries a supported Claude mark. If a supported mark is found, it indicates that the content may have been processed by Claude.
Machine-readable marks provide important signals about content, but it’s worth understanding their limitations across all content types.