A gentle visual guide to how a statistical mark hides inside generated text, and what erases it.
How Claude's text watermarking works
Future Claude models will generate text that contains a watermark. This is a way of determining the likelihood that Claude was involved in writing the text, and we, along with several other major AI providers, are implementing this change to comply with the EU AI Act. In this article, we share answers to some of the questions we’ve received about how our chosen watermarking method works, whether it affects Claude’s outputs, and why we’re making this change.
Google’s invisible AI watermark will help identify generative text and video
New AI tools to generate videos and detect them as well.
Watermarks aren’t the silver bullet for AI misinformation
Digital watermarks are easily broken and abused.
Alex Cui on Twitter / X
Claude's watermark probably doesn't work how you think. As the CTO of GPTZero, I'll explain how Anthropic, Google and OpenAI are building text watermarking in this brief explainer and whether it can be defeated.Almost all forms of watermarking that are fast and cheap enough for… https://t.co/3Ghcz3PTwJ— Alex Cui (@alexcdot) August 11, 2026
AI-text detection tools are really easy to fool
A recent crop of AI systems claiming to detect AI-generated text perform poorly—and it doesn’t take much to get past them.
Identifying AI-generated images with SynthID
Today, in partnership with Google Cloud, we’re beta launching SynthID, a new tool for watermarking and identifying AI-generated images. It’s being released to a limited number of Vertex AI customers using Imagen, one of our latest text-to-image models that uses input text to create photorealistic images. This technology embeds a digital watermark directly into the pixels of an image, making it imperceptible to the human eye, but detectable for identification. While generative AI can unlock huge creative potential, it also presents new risks, like creators spreading false information — both intentionally or unintentionally. Being able to identify AI-generated content is critical to empowering people with knowledge of when they’re interacting with generated media, and for helping prevent the spread of misinformation.
How Claude marks AI-generated content | Claude Help Center
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.
The Impact of AI-Generated Text on the Internet
The proliferation of AI-generated and AI-assisted text on the internet is feared to contribute to a degradation in semantic and stylistic diversity, factual accuracy, and other negative...
The Impact of AI-Generated Text on the Internet
The proliferation of AI-generated and AI-assisted text on the internet is feared to contribute to a degradation in semantic and stylistic diversity, factual accuracy, and other negative...
Code of Practice on Transparency of AI-generated Content
This code of practice supports compliance with the AI Act transparency obligations related to marking and labelling of AI-generated content.
How easy is it to spot AI writing?
With AI writing becoming increasingly commonplace, how can we spot it and what difference does it make?
Google's SynthID AI watermarking tech is being adopted by OpenAI, Nvidia, and more
AI content is getting good, but SynthID might be able to help tell truth from fiction.
Wikipedia:Signs of AI writing
This is a list of writing and formatting conventions typical of AI chatbots such as ChatGPT, with real examples taken from Wikipedia articles, drafts, comments, and other content. It is a field guide to help detect undisclosed AI-generated content on Wikipedia: while some of the signs may be broadly applicable, some may not apply in a non-Wikipedia context.[a] Not all text featuring these indicators is AI-generated, as the large language models that power AI chatbots are trained on human writing, including Wikipedia. Many elements of AI writing can be found in editorials, blogs, or fan fiction.
AI watermarking has a decentralisation problem
With AI watermarking inference providers mark their output as AI generated. But for the system to become useful, lots of independent providers need to collaborate together in a decentralised system without overarching governance.
