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How Claude’s text watermark works · Anthropic News
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20C7.16699 19.5858 7.50278 19.25 7.91699 19.25H32.084ZM32.084 10.5C32.4979 10.5004 32.834 10.836 32.834 11.25C32.8339 11.6639 32.4979 11.9996 32.084 12H7.91699C7.50282 12 7.16706 11.6642 7.16699 11.25C7.16699 10.8358 7.50278 10.5 7.91699 10.5H32.084Z" fill="currentColor"></path></svg></button></div></div></header><main id="main-content" class=""><article><div class="page-wrapper PostDetail-module-scss-module__UQuRMa__hero"><div class="PostDetail-module-scss-module__UQuRMa__header"><div class="PostDetail-module-scss-module__UQuRMa__subjects body-3 bold"><span>Announcements</span></div><h1 class="headline-1 PostDetail-module-scss-module__UQuRMa__title">How Claude’s text watermark works</h1><div class="body-3 agate">Aug 14, 2026</div><div data-theme="ivory"></div></div><div class="PostDetail-module-scss-module__UQuRMa__illustrationHeroWrapper"><div class="Illustration-module-scss-module__WyGOtq__root Illustration-module-scss-module__WyGOtq__aspect-wide Illustration-module-scss-module__WyGOtq__padding-lg Illustration-module-scss-module__WyGOtq__radius-lg bg-heather"><div class="Illustration-module-scss-module__WyGOtq__inner"><img alt="How Claude’s text watermark works" loading="lazy" width="1000" height="1000" decoding="async" data-nimg="1" class="" style="color:transparent" src="https://www-cdn.anthropic.com/images/4zrzovbb/website/33dbe8f783d4835a838b4c4ae85d3c04e352fee1-1000x1000.svg"/></div></div></div></div><div class="page-wrapper"><article><div class="ArticleDetail-module-scss-module__YVTUHa__grid"><div class="ArticleDetail-module-scss-module__YVTUHa__sidebar-container"><aside class="page-wrapper Sidebar-module-scss-module__5Xbtsq__sidebar contentFadeUp" data-theme="ivory"><button type="button" class="Sidebar-module-scss-module__5Xbtsq__sidebar-toggle" aria-label="Show table of contents" aria-expanded="false"><span aria-hidden="true"><svg class="Icon-module-scss-module__lqbdHG__icon" width="24" height="24" viewBox="0 0 24 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class="Sidebar-module-scss-module__5Xbtsq__header-list"></ul></nav></div></aside></div><div class="Body-module-scss-module__z40yvW__body ArticleDetail-module-scss-module__YVTUHa__body-container" data-theme="ivory"><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">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.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">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. To summarize:</p><ul class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><li>We use a method of watermarking that does not have any practical impact on the quality or content of Claude’s outputs;</li><li>The difference between watermarked and un-watermarked text will not be distinguishable to readers;</li><li>Nothing is added to the text and there are no hidden characters;</li><li>Watermarking doesn’t require extra tokens, and will not be more expensive;</li><li>Watermarking carries no identifying information and can’t be traced to a specific person, organization, or chat;</li><li>Watermarking won’t be specific to Claude. As of August 2, the EU requires AI providers serving its market to mark AI-generated content. Other major model developers have signed the same Code of Practice and will be implementing their own watermarks.</li></ul><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="what-is-watermarking"><strong>What is watermarking?</strong></h2><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">Large language models like Claude work by generating one word at a time. Each time the model decides on the next word, it chooses among a list of potential candidates, ultimately selecting the most sensible or likely based on the preceding text. Take the sentence “The weather today was cold and…”. The next word is very unlikely to be “sugary.” But it is quite likely to be “overcast” or “grey.” Under most circumstances, it doesn’t matter much to the reader which of these latter two words the model ultimately chooses—the meaning of the sentence is largely the same either way. In cases like this, the choice is settled by a random number.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">Watermarking uses low-stakes choices like these—which occur many times over a piece of generated text—to leave a pattern in Claude’s responses. That pattern is undetectable to the reader, but <em>is</em> detectable to anyone who has a key that encodes it. When watermarking is used, choices are still made at random, but the <em>source</em> of the randomness is different. Instead of using an arbitrary random number generator to pick the next word, watermarking uses the key and a few words that come before to settle what word the model should pick. That is, the words that Claude picks are still random, but now, one can check the sequence of words and see if it’s consistent with the choices Claude would make if it was using the key. If it is, one can assign a probability that the text was generated by Claude.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">Importantly, it isn’t that the model will now always be biased toward overcast or grey. Just as with non-watermarked text, overcast might be selected in one sentence, grey in the next, depending on the words that came before. And it’s not the case that the watermarking method pushes Claude to choose a word it wouldn’t have considered anyway (for instance, it wouldn’t make Claude pick a word like “nubilous”—an obscure<sup class="caption Body-module-scss-module__z40yvW__sup">1</sup> synonym for overcast or grey that Claude almost certainly wouldn’t use under normal circumstances).</p><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="how-does-watermarking-affect-claudes-outputs"><strong>How does watermarking affect Claude’s outputs?</strong></h2><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">Watermarking does not impact the quality of Claude’s output. To a reader, a watermarked response is indistinguishable from an unwatermarked one (in this way, AI watermarks differ substantially from their namesakes on banknotes, other physical objects, and some digital documents, which <em>are</em> visible to the naked eye).</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">In internal testing, we’ve seen no impact of watermarking on the content, level of creativity, or readability of Claude’s text. In the <a href="https://www.nature.com/articles/s41586-024-08025-4">SynthID-Text paper</a>, which introduced the technique we use, Google DeepMind tested this impact by serving a model that used watermarking to a portion of their Gemini traffic and comparing thumbs-up and thumbs-down ratings. They found no statistically significant differences from the unwatermarked model. And in a controlled study, human raters comparing watermarked and unwatermarked answers side-by-side saw no difference in quality.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">A useful analogy is to imagine you’re playing a game like Monopoly. On each turn, each player moves a random number of spaces around the board according to the roll of a die. Suppose that, instead of rolling the die to get this randomness, we decided to use a book of the digits of pi.<sup class="caption Body-module-scss-module__z40yvW__sup">2</sup> We start from a randomly-chosen digit (say, the 1,012,845th after the decimal place, which happens to be a 6), and from that point on each player simply uses the next digit in the sequence as their next “roll.&quot;</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">For all intents and purposes, the moves are still random: it makes no difference to the players—or to the outcome of the game—whether the randomness comes from pi or from dice rolls each time. But if we could see the sequence of all the moves after the game (and we knew the value of pi), we could work out whether this was a game that likely used pi to determine its moves. The game that used pi is, in a sense, “watermarked.&quot;</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">It’s the same for Claude-generated text. Watermarking doesn’t change the meaning or experience for the person reading it, but if you wanted to check after the fact whether the text was likely generated by Claude, the watermark allows you to do so.</p><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="which-specific-method-of-watermarking-do-you-use"><strong>Which specific method of watermarking do you use?</strong></h2><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">Claude’s text watermark is a version of the SynthID-Text approach published by Google DeepMind in a <a href="https://www.nature.com/articles/s41586-024-08025-4"><em>Nature</em> paper</a> in 2024. It belongs to a family of approaches that go back to a proposal by Scott Aaronson in 2022, all of which share the same design principle that we described above—the watermark only changes the source of the randomness used to pick among words. </p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">There are limitations to the effectiveness of watermarking. Using our key, one can only answer the question “What is the likelihood this was partly written by Claude?” It doesn’t confirm whether the text was human-written, and it can’t tell whether the text was written by a different AI (even if that other AI uses watermarking, it would have a different key; it might also use a different watermarking method altogether). Detecting a watermark also doesn’t work well on small samples, where there are fewer word choices and thus less information to go on. As a passage increases in length, confidence about Claude’s involvement increases too.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">Watermarking is sparser on factual passages where there are fewer choices that can be made without decreasing the accuracy of the text. For example, take the sentence “Isaac Newton’s most famous work was called <em>Principia</em>…”. It really matters whether the next word is “<em>Mathematica</em>” (it’s the only right answer), so the watermark would have nothing to act on. The same is true for proofreading. If you hand Claude a piece of writing and ask it to edit only the grammar and punctuation and nothing else, the watermark can only live in the handful of corrections, which might be too few to register.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="what-about-cases-where-claude-has-proofread-or-edited-human-text"><strong>What about cases where Claude has proofread or edited human text?</strong></h2><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">The watermark only applies to words Claude chooses. When Claude proofreads text written by a person, what it gives back has generally only been lightly edited; because nearly all the words are the person’s, there’s very little (if anything) for the watermark to attach to. Depending on the length of the text and how heavily Claude has edited it, those changes might not be enough to make Claude’s involvement detectable. The more Claude writes, the more decisions it has to make, and the more space there is for a watermark.</p><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="what-about-code-"><strong>What about code? </strong></h2><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">As we noted above, AI watermarking takes advantage of decisions where either choice of a word would be equally good. Where an <em>exact</em> output is required—where there isn’t a choice, and something would be factually wrong or a piece of code would break if a different term was chosen—the watermark isn’t applied.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">For example, once the model has written “2 + 2 =”, there is a very clear best choice for the next token (if the model is completing the sum, there isn’t an answer that’s equally as good as “4”; if it’s talking about George Orwell’s <em>Nineteen Eighty-Four</em>, there isn’t an answer that’s equally as good as “5”). The “nudge” of the watermark wouldn’t be applied here. For the same reason, code—which in very many cases has to be exact—has generally less watermarking than some other forms of text.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">Having said that, in areas where there <em>is</em> an arbitrary choice between particular words or terms within the code, the watermark can be used, such as comments within code. But by definition, it will have a negligible effect on the actual code produced.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="what-does-this-mean-for-users-"><strong>What does this mean for users? <br/></strong></h2><h3 class="Body-module-scss-module__z40yvW__reading-column headline-6 post-subsection" id="does-this-slow-the-model-down-or-make-it-more-expensive"><strong>Does this slow the model down, or make it more expensive?</strong></h3><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><br/>No. Watermarking has a negligible impact on the speed of models, and because it produces no extra tokens, the model is the same price to serve and use.</p><h3 class="Body-module-scss-module__z40yvW__reading-column headline-6 post-subsection" id="can-a-watermark-be-traced-back-to-me-or-my-organization"><strong>Can a watermark be traced back to me or my organization?</strong></h3><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">No. The watermarking applies to Claude and its outputs. It doesn’t identify anything to do with individual users. There’s nothing in the watermark, or its key, that would allow anyone to recover any information about the user, their organization, or their chats with Claude.<br/></p><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="229181bf1d83"><strong><em>Why</em> are you watermarking Claude’s outputs?</strong></h2><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">We’re implementing watermarking to comply with the EU AI Act. Anthropic, along with several other major AI model providers and around <a href="https://digital-strategy.ec.europa.eu/en/news/strong-backing-code-practice-transparency-ai-generated-content">190 total signatories</a>, signed the EU Code of Practice on Transparency of AI-Generated Content in July 2026. This requires AI system providers to use methods of “marking” AI-generated text. We’re applying watermarking globally at launch because we don&#x27;t yet have a durable way to scope it by region. However, we will continue to evaluate different approaches, and will share updates when we have them.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="other-questions"><strong>Other questions</strong></h2><h3 class="Body-module-scss-module__z40yvW__reading-column headline-6 post-subsection" id="how-do-i-check-if-a-piece-of-text-was-written-by-claude"><strong>How do I check if a piece of text was written by Claude?</strong></h3><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">We are releasing a detection API in private preview. It is currently available to eligible organizations as required under EU law (such as regulators, law enforcement, media, fact-checkers, independent researchers, educational organizations, and EU civil society groups). It is also available for enterprises who are similarly obligated to verify watermarking for their own compliance with the Act. We plan to expand access to the detection API over time. You can register interest in access <a href="https://forms.gle/9tGA33hPJJwtHsMk9">here</a>.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><h3 class="Body-module-scss-module__z40yvW__reading-column headline-6 post-subsection" id="what-about-images-and-other-files"><strong>What about images and other files?</strong></h3><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">When Claude produces a file of a supported type (such as a .png, .jpg, or .svg), it will attach a content credential in the form of a small, cryptographically signed note in the file’s metadata, saying that the file was made or processed with Claude. This is an open industry standard called <a href="https://c2pa.org/">C2PA</a>—the same used by camera manufacturers and in photo-editing software to record where an image came from. Any C2PA-aware tool can read it; we’ll be providing our own where you can drop a file and check.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">This metadata label is very different from a watermark. Nothing in the file changes—it is not embedded or hidden. As with text, the credential only says Claude was involved in producing the file; it doesn’t include any identifying information.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><h3 class="Body-module-scss-module__z40yvW__reading-column headline-6 post-subsection" id="cant-someone-just-edit-the-text-to-get-around-the-watermarking"><strong>Can’t someone just edit the text to get around the watermarking?</strong></h3><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">To some extent, yes. Light editing probably won’t remove the watermark completely; a complete rewrite where every word is replaced will. In the latter case, of course, it’s arguable whether the text can any longer be described as AI-generated.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><h3 class="Body-module-scss-module__z40yvW__reading-column headline-6 post-subsection" id="what-does-a-watermark-actually-prove"><strong>What does a watermark actually prove?</strong></h3><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">A watermark can only determine that Claude was likely involved with the content at some point. It cannot distinguish “Claude wrote this” from “Claude heavily edited this.”</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><h3 class="Body-module-scss-module__z40yvW__reading-column headline-6 post-subsection" id="do-watermarks-apply-to-translations"><strong>Do watermarks apply to translations?</strong></h3><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">Yes. A translation produced by Claude carries a watermark, because in this case every word is chosen by Claude.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><h3 class="Body-module-scss-module__z40yvW__reading-column headline-6 post-subsection" id="what-about-older-claude-models"><strong>What about older Claude models?</strong></h3><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">The EU law includes a transition period for Anthropic models launched before August 2, 2026, and we’re working to add watermarking for those models as well. This will be rolled out over the coming months.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p><h3 class="Body-module-scss-module__z40yvW__reading-column headline-6 post-subsection" id="how-does-this-differ-from-ai-detection-software-like-pangram"><strong>How does this differ from AI detection software, like Pangram?</strong></h3><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">AI detection software uses a different method, because the companies that provide it don’t have our key. Among other things, those services look at aspects of the text like the subtle (and not-so-subtle) “tells” that often appear in AI’s phrasing. For example, AI models appear to be fond of the construction “this isn’t [X], it’s [Y]”, and use the word “quietly” a lot more than you might expect. Picking up on these patterns is fundamentally different from checking for a watermark.</p><h3 class="Body-module-scss-module__z40yvW__reading-column headline-6 post-subsection" id="does-this-change-who-owns-a-given-output-or-who-is-legally-responsible-for-it"><strong>Does this change who owns a given output, or who is legally responsible for it?</strong></h3><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">No. A watermark only helps test whether Claude might have produced or processed the content. It doesn’t say anything about ownership or authorship, and doesn’t change a user’s rights under our terms. We only apply the watermark when Claude was involved in processing the content or file.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><br/><em>Updated Sep 1, 2026: </em>Provided up to date information on the watermarking detection API. </p></div></div></article></div><div class="page-wrapper PostDetail-module-scss-module__UQuRMa__postFooter"><div class="PostDetail-module-scss-module__UQuRMa__footnotes"><h4 class="headline-5">Footnotes</h4><ol><li id="footnote-1">Or, you might say, nubilous—which is also a synonym for “obscure.”</li><li id="footnote-2">Pi is technically predictable, but any run of digits from somewhere in the middle of pi is indistinguishable from a run of rolls of a ten-sided die. Also, set aside the fact that the dice in Monopoly go from 1 to 6 whereas a digit of pi can be from 0 to 9; the analogy isn’t perfect.</li></ol></div><div class="PostDetail-module-scss-module__UQuRMa__socialShare"><a href="https://twitter.com/intent/tweet?text=https://www.anthropic.com/news/claude-text-watermark" target="_blank" rel="noopener" aria-label="Share on Twitter"><svg class="Icon-module-scss-module__lqbdHG__icon" width="32" height="32" viewBox="0 0 32 32"><path d="M28 28L18.6145 14.0124L18.6305 14.0255L27.0929 4H24.265L17.3713 12.16L11.8968 4H4.48021L13.2425 17.0593L13.2414 17.0582L4 28H6.82792L14.4921 18.9215L20.5834 28H28ZM10.7763 6.18182L23.9449 25.8182H21.7039L8.52468 6.18182H10.7763Z" fill="#191919"></path></svg></a><a href="https://www.linkedin.com/shareArticle?mini=true&amp;url=https://www.anthropic.com/news/claude-text-watermark" target="_blank" rel="noopener" aria-label="Share on LinkedIn"><svg class="Icon-module-scss-module__lqbdHG__icon" width="32" height="32" viewBox="0 0 32 32"><path d="M25.8182 4H6.18182C4.97636 4 4 4.97636 4 6.18182V25.8182C4 27.0236 4.97636 28 6.18182 28H25.8182C27.0236 28 28 27.0236 28 25.8182V6.18182C28 4.97636 27.0236 4 25.8182 4ZM11.5862 23.6364H8.368V13.2815H11.5862V23.6364ZM9.94436 11.8011C8.90691 11.8011 8.068 10.96 8.068 9.92473C8.068 8.88945 8.908 8.04945 9.94436 8.04945C10.9785 8.04945 11.8196 8.89055 11.8196 9.92473C11.8196 10.96 10.9785 11.8011 9.94436 11.8011ZM23.6407 23.6364H20.4247V18.6007C20.4247 17.3996 20.4029 15.8549 18.7524 15.8549C17.0778 15.8549 16.8204 17.1629 16.8204 18.5135V23.6364H13.6044V13.2815H16.6916V14.6964H16.7353C17.1651 13.8825 18.2145 13.024 19.78 13.024C23.0385 13.024 23.6407 15.1687 23.6407 17.9571V23.6364Z" fill="#141413"></path></svg></a></div></div><section class="LandingPageSection-module-scss-module__ZSMdoa__root" data-theme="ivory"><div class="page-wrapper"><div class="SectionIntro-module-scss-module__i9TRza__root LinkGrid-module-scss-module__wTN57W__intro"><h2 class="headline-4 SectionIntro-module-scss-module__i9TRza__title">Related content</h2></div><div class="LinkGrid-module-scss-module__wTN57W__root"><div class="LinkGrid-module-scss-module__wTN57W__items LinkGrid-module-scss-module__wTN57W__threeItems"><div class="LinkGrid-module-scss-module__wTN57W__item"><h3 class="headline-6">Developing Enterprise Frontier Safeguards with our customers</h3><a href="/news/enterprise-frontier-safeguards" class="ButtonTextLink-module-scss-module__q8IAwW__textLink LinkGrid-module-scss-module__wTN57W__cta" referrerPolicy="no-referrer-when-downgrade"><span class="body-3">Read more</span><span class="ButtonTextLink-module-scss-module__q8IAwW__icon"><svg class="Icon-module-scss-module__lqbdHG__icon" width="20" height="20" viewBox="0 0 21 21"><path d="M4.14585 9.87492L14.4584 9.87492L9.60419 5.04158L10.5 4.14575L16.8542 10.4999L10.5 16.8541L9.60419 15.9583L14.4584 11.1249L4.14585 11.1249L4.14585 9.87492Z" fill="currentColor"></path></svg></span></a></div><div class="LinkGrid-module-scss-module__wTN57W__item"><h3 class="headline-6">Improving our alignment and security efforts</h3><p class="body-3 serif">On July 30, we reported three incidents in which Claude models gained unauthorized access to real computer systems. We are conducting an in-depth analysis of both incidents, and planning to work with METR for an independent review. In the meantime, we’re sharing some of the changes we’ve made over the past month.</p><a href="/news/improving-alignment-security-efforts" class="ButtonTextLink-module-scss-module__q8IAwW__textLink LinkGrid-module-scss-module__wTN57W__cta" referrerPolicy="no-referrer-when-downgrade"><span class="body-3">Read more</span><span class="ButtonTextLink-module-scss-module__q8IAwW__icon"><svg class="Icon-module-scss-module__lqbdHG__icon" width="20" height="20" viewBox="0 0 21 21"><path d="M4.14585 9.87492L14.4584 9.87492L9.60419 5.04158L10.5 4.14575L16.8542 10.4999L10.5 16.8541L9.60419 15.9583L14.4584 11.1249L4.14585 11.1249L4.14585 9.87492Z" fill="currentColor"></path></svg></span></a></div><div class="LinkGrid-module-scss-module__wTN57W__item"><h3 class="headline-6">Previewing the Model Hardware Standard</h3><p class="body-3 serif">We’re opening a research preview of the Model Hardware Standard (MHS), a shared specification for AI agents to safely operate physical devices, to a first group of scientific research labs and advanced manufacturers. </p><a href="/news/model-hardware-standard-research-preview" class="ButtonTextLink-module-scss-module__q8IAwW__textLink LinkGrid-module-scss-module__wTN57W__cta" referrerPolicy="no-referrer-when-downgrade"><span class="body-3">Read more</span><span class="ButtonTextLink-module-scss-module__q8IAwW__icon"><svg class="Icon-module-scss-module__lqbdHG__icon" width="20" height="20" viewBox="0 0 21 21"><path d="M4.14585 9.87492L14.4584 9.87492L9.60419 5.04158L10.5 4.14575L16.8542 10.4999L10.5 16.8541L9.60419 15.9583L14.4584 11.1249L4.14585 11.1249L4.14585 9.87492Z" fill="currentColor"></path></svg></span></a></div></div></div></div></section></article></main><footer id="footer" class="SiteFooter-module-scss-module__JdOqwq__root" role="contentinfo" aria-label="Site footer"><div class="page-wrapper SiteFooter-module-scss-module__JdOqwq__footer"><div class="SiteFooter-module-scss-module__JdOqwq__logoWrapper"><a href="/" aria-label="Return 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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.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"06a241180a71\",\"_type\":\"block\",\"children\":[{\"_key\":\"809431607739\",\"_type\":\"span\",\"marks\":[],\"text\":\"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. To summarize:\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"6ad94fc13f94\",\"_type\":\"block\",\"children\":[{\"_key\":\"0bd4af63eee2\",\"_type\":\"span\",\"marks\":[],\"text\":\"We use a method of watermarking that does not have any practical impact on the quality or content of Claude’s outputs;\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"3d376cb9410e\",\"_type\":\"block\",\"children\":[{\"_key\":\"1c8c4ba6f548\",\"_type\":\"span\",\"marks\":[],\"text\":\"The difference between watermarked and un-watermarked text will not be distinguishable to readers;\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"872e0747918c\",\"_type\":\"block\",\"children\":[{\"_key\":\"cb22e1e9fc84\",\"_type\":\"span\",\"marks\":[],\"text\":\"Nothing is added to the text and there are no hidden characters;\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"c9220a726726\",\"_type\":\"block\",\"children\":[{\"_key\":\"d1cf5c478d4e\",\"_type\":\"span\",\"marks\":[],\"text\":\"Watermarking doesn’t require extra tokens, and will not be more expensive;\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"e36ff7746cc4\",\"_type\":\"block\",\"children\":[{\"_key\":\"335ec3412977\",\"_type\":\"span\",\"marks\":[],\"text\":\"Watermarking carries no identifying information and can’t be traced to a specific person, organization, or chat;\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"04ca3db57c4e\",\"_type\":\"block\",\"children\":[{\"_key\":\"8f5b6b876e84\",\"_type\":\"span\",\"marks\":[],\"text\":\"Watermarking won’t be specific to Claude. As of August 2, the EU requires AI providers serving its market to mark AI-generated content. Other major model developers have signed the same Code of Practice and will be implementing their own watermarks.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"866b7a59d1bd\",\"_type\":\"block\",\"children\":[{\"_key\":\"15c33df54bb9\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"What is watermarking?\"}],\"markDefs\":[],\"style\":\"h3\"},{\"_key\":\"30540d58d68f\",\"_type\":\"block\",\"children\":[{\"_key\":\"481ef7a56a7a\",\"_type\":\"span\",\"marks\":[],\"text\":\"Large language models like Claude work by generating one word at a time. Each time the model decides on the next word, it chooses among a list of potential candidates, ultimately selecting the most sensible or likely based on the preceding text. Take the sentence “The weather today was cold and…”. The next word is very unlikely to be “sugary.” But it is quite likely to be “overcast” or “grey.” Under most circumstances, it doesn’t matter much to the reader which of these latter two words the model ultimately chooses—the meaning of the sentence is largely the same either way. In cases like this, the choice is settled by a random number.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"b3e840ec539a\",\"_type\":\"block\",\"children\":[{\"_key\":\"083eca72f8a8\",\"_type\":\"span\",\"marks\":[],\"text\":\"Watermarking uses low-stakes choices like these—which occur many times over a piece of generated text—to leave a pattern in Claude’s responses. That pattern is undetectable to the reader, but \"},{\"_key\":\"d4a1e7ea5691\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"is\"},{\"_key\":\"029e92cf85b3\",\"_type\":\"span\",\"marks\":[],\"text\":\" detectable to anyone who has a key that encodes it. When watermarking is used, choices are still made at random, but the \"},{\"_key\":\"b86141d10f97\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"source\"},{\"_key\":\"6d93d84e08b7\",\"_type\":\"span\",\"marks\":[],\"text\":\" of the randomness is different. Instead of using an arbitrary random number generator to pick the next word, watermarking uses the key and a few words that come before to settle what word the model should pick. That is, the words that Claude picks are still random, but now, one can check the sequence of words and see if it’s consistent with the choices Claude would make if it was using the key. If it is, one can assign a probability that the text was generated by Claude.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"3150590a37cd\",\"_type\":\"block\",\"children\":[{\"_key\":\"ef1dd9a48dd3\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"7b3c27b07aa3\",\"_type\":\"block\",\"children\":[{\"_key\":\"8ea1d91fbcb5\",\"_type\":\"span\",\"marks\":[],\"text\":\"Importantly, it isn’t that the model will now always be biased toward overcast or grey. Just as with non-watermarked text, overcast might be selected in one sentence, grey in the next, depending on the words that came before. And it’s not the case that the watermarking method pushes Claude to choose a word it wouldn’t have considered anyway (for instance, it wouldn’t make Claude pick a word like “nubilous”—an obscure\"},{\"_key\":\"6584e3dd7b19\",\"_type\":\"span\",\"marks\":[\"sup\"],\"text\":\"1\"},{\"_key\":\"d2e88718e50c\",\"_type\":\"span\",\"marks\":[],\"text\":\" synonym for overcast or grey that Claude almost certainly wouldn’t use under normal circumstances).\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"28655fc2a3ff\",\"_type\":\"block\",\"children\":[{\"_key\":\"9114363addaa\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"How does watermarking affect Claude’s outputs?\"}],\"markDefs\":[],\"style\":\"h3\"},{\"_key\":\"8f5efaf9e85c\",\"_type\":\"block\",\"children\":[{\"_key\":\"27a1f37a39b1\",\"_type\":\"span\",\"marks\":[],\"text\":\"Watermarking does not impact the quality of Claude’s output. To a reader, a watermarked response is indistinguishable from an unwatermarked one (in this way, AI watermarks differ substantially from their namesakes on banknotes, other physical objects, and some digital documents, which \"},{\"_key\":\"468734255658\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"are\"},{\"_key\":\"a19bf72603fd\",\"_type\":\"span\",\"marks\":[],\"text\":\" visible to the naked eye).\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"692868f346ea\",\"_type\":\"block\",\"children\":[{\"_key\":\"879bdbc385d3\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"6cf9fc2e6892\",\"_type\":\"block\",\"children\":[{\"_key\":\"716ff77fc845\",\"_type\":\"span\",\"marks\":[],\"text\":\"In internal testing, we’ve seen no impact of watermarking on the content, level of creativity, or readability of Claude’s text. In the \"},{\"_key\":\"5778f831f162\",\"_type\":\"span\",\"marks\":[\"e9828b422e17\"],\"text\":\"SynthID-Text paper\"},{\"_key\":\"9780e261595f\",\"_type\":\"span\",\"marks\":[],\"text\":\", which introduced the technique we use, Google DeepMind tested this impact by serving a model that used watermarking to a portion of their Gemini traffic and comparing thumbs-up and thumbs-down ratings. They found no statistically significant differences from the unwatermarked model. And in a controlled study, human raters comparing watermarked and unwatermarked answers side-by-side saw no difference in quality.\"}],\"markDefs\":[{\"_key\":\"e9828b422e17\",\"_type\":\"link\",\"href\":\"https://www.nature.com/articles/s41586-024-08025-4\"}],\"style\":\"normal\"},{\"_key\":\"2ce24a1e3424\",\"_type\":\"block\",\"children\":[{\"_key\":\"4d12368d8734\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"c559422c1381\",\"_type\":\"block\",\"children\":[{\"_key\":\"132229303cc0\",\"_type\":\"span\",\"marks\":[],\"text\":\"A useful analogy is to imagine you’re playing a game like Monopoly. On each turn, each player moves a random number of spaces around the board according to the roll of a die. Suppose that, instead of rolling the die to get this randomness, we decided to use a book of the digits of pi.\"},{\"_key\":\"252af29b29d0\",\"_type\":\"span\",\"marks\":[\"sup\"],\"text\":\"2\"},{\"_key\":\"8eb928e2a653\",\"_type\":\"span\",\"marks\":[],\"text\":\" We start from a randomly-chosen digit (say, the 1,012,845th after the decimal place, which happens to be a 6), and from that point on each player simply uses the next digit in the sequence as their next “roll.\\\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"39092a21447a\",\"_type\":\"block\",\"children\":[{\"_key\":\"61ae3ffbc9ef\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"0945660ba8d6\",\"_type\":\"block\",\"children\":[{\"_key\":\"8d5c3526bc26\",\"_type\":\"span\",\"marks\":[],\"text\":\"For all intents and purposes, the moves are still random: it makes no difference to the players—or to the outcome of the game—whether the randomness comes from pi or from dice rolls each time. But if we could see the sequence of all the moves after the game (and we knew the value of pi), we could work out whether this was a game that likely used pi to determine its moves. The game that used pi is, in a sense, “watermarked.\\\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"5cffc2e44bf3\",\"_type\":\"block\",\"children\":[{\"_key\":\"ea4727b92fdf\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"93d5985687c0\",\"_type\":\"block\",\"children\":[{\"_key\":\"e79f4c2e37ba\",\"_type\":\"span\",\"marks\":[],\"text\":\"It’s the same for Claude-generated text. Watermarking doesn’t change the meaning or experience for the person reading it, but if you wanted to check after the fact whether the text was likely generated by Claude, the watermark allows you to do so.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"305e12a00867\",\"_type\":\"block\",\"children\":[{\"_key\":\"3ac7819a5d38\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Which specific method of watermarking do you use?\"}],\"markDefs\":[],\"style\":\"h3\"},{\"_key\":\"9c44cde1e4a4\",\"_type\":\"block\",\"children\":[{\"_key\":\"89d2e7ae534b\",\"_type\":\"span\",\"marks\":[],\"text\":\"Claude’s text watermark is a version of the SynthID-Text approach published by Google DeepMind in a \"},{\"_key\":\"b74c441c882b\",\"_type\":\"span\",\"marks\":[\"f99f04c18e86\",\"em\"],\"text\":\"Nature\"},{\"_key\":\"d8d02e94da6d\",\"_type\":\"span\",\"marks\":[\"f99f04c18e86\"],\"text\":\" paper\"},{\"_key\":\"2ba1b70ecb89\",\"_type\":\"span\",\"marks\":[],\"text\":\" in 2024. It belongs to a family of approaches that go back to a proposal by Scott Aaronson in 2022, all of which share the same design principle that we described above—the watermark only changes the source of the randomness used to pick among words. \"}],\"markDefs\":[{\"_key\":\"f99f04c18e86\",\"_type\":\"link\",\"href\":\"https://www.nature.com/articles/s41586-024-08025-4\"}],\"style\":\"normal\"},{\"_key\":\"3015dc3b0088\",\"_type\":\"block\",\"children\":[{\"_key\":\"5347e123b03c\",\"_type\":\"span\",\"marks\":[],\"text\":\"There are limitations to the effectiveness of watermarking. Using our key, one can only answer the question “What is the likelihood this was partly written by Claude?” It doesn’t confirm whether the text was human-written, and it can’t tell whether the text was written by a different AI (even if that other AI uses watermarking, it would have a different key; it might also use a different watermarking method altogether). Detecting a watermark also doesn’t work well on small samples, where there are fewer word choices and thus less information to go on. As a passage increases in length, confidence about Claude’s involvement increases too.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"10802dc266a9\",\"_type\":\"block\",\"children\":[{\"_key\":\"df5b59229e6b\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"dba23c71209a\",\"_type\":\"block\",\"children\":[{\"_key\":\"512823a7ebae\",\"_type\":\"span\",\"marks\":[],\"text\":\"Watermarking is sparser on factual passages where there are fewer choices that can be made without decreasing the accuracy of the text. For example, take the sentence “Isaac Newton’s most famous work was called \"},{\"_key\":\"ba081bc594d2\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"Principia\"},{\"_key\":\"664d8130c248\",\"_type\":\"span\",\"marks\":[],\"text\":\"…”. It really matters whether the next word is “\"},{\"_key\":\"381f9f78fa0a\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"Mathematica\"},{\"_key\":\"199b2c89d45b\",\"_type\":\"span\",\"marks\":[],\"text\":\"” (it’s the only right answer), so the watermark would have nothing to act on. The same is true for proofreading. If you hand Claude a piece of writing and ask it to edit only the grammar and punctuation and nothing else, the watermark can only live in the handful of corrections, which might be too few to register.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"f9e454d7d8c5\",\"_type\":\"block\",\"children\":[{\"_key\":\"a062e6cadf30\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"951b6cea74cb\",\"_type\":\"block\",\"children\":[{\"_key\":\"f231bd24c63f\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"What about cases where Claude has proofread or edited human text?\"}],\"markDefs\":[],\"style\":\"h3\"},{\"_key\":\"363a8ee50f3a\",\"_type\":\"block\",\"children\":[{\"_key\":\"5f7fcded92b7\",\"_type\":\"span\",\"marks\":[],\"text\":\"The watermark only applies to words Claude chooses. When Claude proofreads text written by a person, what it gives back has generally only been lightly edited; because nearly all the words are the person’s, there’s very little (if anything) for the watermark to attach to. Depending on the length of the text and how heavily Claude has edited it, those changes might not be enough to make Claude’s involvement detectable. The more Claude writes, the more decisions it has to make, and the more space there is for a watermark.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"83aa1fdc2287\",\"_type\":\"block\",\"children\":[{\"_key\":\"0c37484b332d\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"What about code? \"}],\"markDefs\":[],\"style\":\"h3\"},{\"_key\":\"04f68560200f\",\"_type\":\"block\",\"children\":[{\"_key\":\"120b888be937\",\"_type\":\"span\",\"marks\":[],\"text\":\"As we noted above, AI watermarking takes advantage of decisions where either choice of a word would be equally good. Where an \"},{\"_key\":\"83bf67b3e555\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"exact\"},{\"_key\":\"a28b79a4fdb2\",\"_type\":\"span\",\"marks\":[],\"text\":\" output is required—where there isn’t a choice, and something would be factually wrong or a piece of code would break if a different term was chosen—the watermark isn’t applied.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"f0c9e676183c\",\"_type\":\"block\",\"children\":[{\"_key\":\"2f66adb6578c\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"20908339bfac\",\"_type\":\"block\",\"children\":[{\"_key\":\"82c4636a257c\",\"_type\":\"span\",\"marks\":[],\"text\":\"For example, once the model has written “2 + 2 =”, there is a very clear best choice for the next token (if the model is completing the sum, there isn’t an answer that’s equally as good as “4”; if it’s talking about George Orwell’s \"},{\"_key\":\"fe90b6170fa2\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"Nineteen Eighty-Four\"},{\"_key\":\"64e8ddaa0a2f\",\"_type\":\"span\",\"marks\":[],\"text\":\", there isn’t an answer that’s equally as good as “5”). The “nudge” of the watermark wouldn’t be applied here. For the same reason, code—which in very many cases has to be exact—has generally less watermarking than some other forms of text.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"edf4291ef84a\",\"_type\":\"block\",\"children\":[{\"_key\":\"c5cb98ac2cf6\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"3d902b8510d2\",\"_type\":\"block\",\"children\":[{\"_key\":\"885878b48e03\",\"_type\":\"span\",\"marks\":[],\"text\":\"Having said that, in areas where there \"},{\"_key\":\"f60b3e89f836\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"is\"},{\"_key\":\"549abb9dd7fa\",\"_type\":\"span\",\"marks\":[],\"text\":\" an arbitrary choice between particular words or terms within the code, the watermark can be used, such as comments within code. But by definition, it will have a negligible effect on the actual code produced.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"503f3245e9c5\",\"_type\":\"block\",\"children\":[{\"_key\":\"d1d7aa5a9deb\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"23a225719729\",\"_type\":\"block\",\"children\":[{\"_key\":\"a42afd2ef251\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"What does this mean for users? \\n\"}],\"markDefs\":[],\"style\":\"h3\"},{\"_key\":\"b34abafe090a\",\"_type\":\"block\",\"children\":[{\"_key\":\"561dda752fd0\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Does this slow the model down, or make it more expensive?\"}],\"markDefs\":[],\"style\":\"h4\"},{\"_key\":\"6dd3d3288e18\",\"_type\":\"block\",\"children\":[{\"_key\":\"d59013d3b724\",\"_type\":\"span\",\"marks\":[],\"text\":\"\\nNo. Watermarking has a negligible impact on the speed of models, and because it produces no extra tokens, the model is the same price to serve and use.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"4c2dbc221d35\",\"_type\":\"block\",\"children\":[{\"_key\":\"3cd11b65ba88\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Can a watermark be traced back to me or my organization?\"}],\"markDefs\":[],\"style\":\"h4\"},{\"_key\":\"03fbd76349dc\",\"_type\":\"block\",\"children\":[{\"_key\":\"962b9986ef17\",\"_type\":\"span\",\"marks\":[],\"text\":\"No. The watermarking applies to Claude and its outputs. It doesn’t identify anything to do with individual users. There’s nothing in the watermark, or its key, that would allow anyone to recover any information about the user, their organization, or their chats with Claude.\\n\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"229181bf1d83\",\"_type\":\"block\",\"children\":[{\"_key\":\"a6798e581d85\",\"_type\":\"span\",\"marks\":[\"strong\",\"em\"],\"text\":\"Why\"},{\"_key\":\"b672353cb3fc\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\" are you watermarking Claude’s outputs?\"}],\"markDefs\":[],\"style\":\"h3\"},{\"_key\":\"2c9099755372\",\"_type\":\"block\",\"children\":[{\"_key\":\"acf4b251ee27\",\"_type\":\"span\",\"marks\":[],\"text\":\"We’re implementing watermarking to comply with the EU AI Act. Anthropic, along with several other major AI model providers and around \"},{\"_key\":\"e709e226bde7\",\"_type\":\"span\",\"marks\":[\"e1758f9013bb\"],\"text\":\"190 total signatories\"},{\"_key\":\"0360e0ef3b90\",\"_type\":\"span\",\"marks\":[],\"text\":\", signed the EU Code of Practice on Transparency of AI-Generated Content in July 2026. This requires AI system providers to use methods of “marking” AI-generated text. We’re applying watermarking globally at launch because we don't yet have a durable way to scope it by region. However, we will continue to evaluate different approaches, and will share updates when we have them.\"}],\"markDefs\":[{\"_key\":\"e1758f9013bb\",\"_type\":\"link\",\"href\":\"https://digital-strategy.ec.europa.eu/en/news/strong-backing-code-practice-transparency-ai-generated-content\"}],\"style\":\"normal\"},{\"_key\":\"a5831a34881c\",\"_type\":\"block\",\"children\":[{\"_key\":\"a40ca3667857\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"9086ff40203c\",\"_type\":\"block\",\"children\":[{\"_key\":\"f407fc501cf3\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Other questions\"}],\"markDefs\":[],\"style\":\"h3\"},{\"_key\":\"56f4ef5a52d3\",\"_type\":\"block\",\"children\":[{\"_key\":\"3e15183192dd\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"How do I check if a piece of text was written by Claude?\"}],\"markDefs\":[],\"style\":\"h4\"},{\"_key\":\"e31cc23bbbae\",\"_type\":\"block\",\"children\":[{\"_key\":\"43d5ed489558\",\"_type\":\"span\",\"marks\":[],\"text\":\"We are releasing a detection API in private preview. It is currently available to eligible organizations as required under EU law (such as regulators, law enforcement, media, fact-checkers, independent researchers, educational organizations, and EU civil society groups). It is also available for enterprises who are similarly obligated to verify watermarking for their own compliance with the Act. We plan to expand access to the detection API over time. You can register interest in access \"},{\"_key\":\"47310cf22ca1\",\"_type\":\"span\",\"marks\":[\"8f8fec4be7b3\"],\"text\":\"here\"},{\"_key\":\"3591ab368773\",\"_type\":\"span\",\"marks\":[],\"text\":\".\"}],\"markDefs\":[{\"_key\":\"8f8fec4be7b3\",\"_type\":\"link\",\"href\":\"https://forms.gle/9tGA33hPJJwtHsMk9\"}],\"style\":\"normal\"},{\"_key\":\"f1b6ae483f85\",\"_type\":\"block\",\"children\":[{\"_key\":\"293de61a278c\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"dde6b466576b\",\"_type\":\"block\",\"children\":[{\"_key\":\"df5e1d47c0dc\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"What about images and other files?\"}],\"markDefs\":[],\"style\":\"h4\"},{\"_key\":\"d9cffff675af\",\"_type\":\"block\",\"children\":[{\"_key\":\"0f7ff81f9035\",\"_type\":\"span\",\"marks\":[],\"text\":\"When Claude produces a file of a supported type (such as a .png, .jpg, or .svg), it will attach a content credential in the form of a small, cryptographically signed note in the file’s metadata, saying that the file was made or processed with Claude. This is an open industry standard called \"},{\"_key\":\"36b063aae96f\",\"_type\":\"span\",\"marks\":[\"dae90b2be4b1\"],\"text\":\"C2PA\"},{\"_key\":\"61cc70d3b633\",\"_type\":\"span\",\"marks\":[],\"text\":\"—the same used by camera manufacturers and in photo-editing software to record where an image came from. Any C2PA-aware tool can read it; we’ll be providing our own where you can drop a file and check.\"}],\"markDefs\":[{\"_key\":\"dae90b2be4b1\",\"_type\":\"link\",\"href\":\"https://c2pa.org/\"}],\"style\":\"normal\"},{\"_key\":\"87d8282a0bcc\",\"_type\":\"block\",\"children\":[{\"_key\":\"d3f5d93e7d68\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"be3497a864ac\",\"_type\":\"block\",\"children\":[{\"_key\":\"4bb37e08fcb7\",\"_type\":\"span\",\"marks\":[],\"text\":\"This metadata label is very different from a watermark. Nothing in the file changes—it is not embedded or hidden. As with text, the credential only says Claude was involved in producing the file; it doesn’t include any identifying information.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"f3261cd49af4\",\"_type\":\"block\",\"children\":[{\"_key\":\"08ac111dd89b\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"8f0ee7122db6\",\"_type\":\"block\",\"children\":[{\"_key\":\"351a02e3b45b\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Can’t someone just edit the text to get around the watermarking?\"}],\"markDefs\":[],\"style\":\"h4\"},{\"_key\":\"43b8be8e63ed\",\"_type\":\"block\",\"children\":[{\"_key\":\"08069589ad9e\",\"_type\":\"span\",\"marks\":[],\"text\":\"To some extent, yes. Light editing probably won’t remove the watermark completely; a complete rewrite where every word is replaced will. In the latter case, of course, it’s arguable whether the text can any longer be described as AI-generated.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"f41d7a148332\",\"_type\":\"block\",\"children\":[{\"_key\":\"22e1032e460f\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"3d9f356086ae\",\"_type\":\"block\",\"children\":[{\"_key\":\"93ccc3453c6c\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"What does a watermark actually prove?\"}],\"markDefs\":[],\"style\":\"h4\"},{\"_key\":\"688990d13dff\",\"_type\":\"block\",\"children\":[{\"_key\":\"32541a13730e\",\"_type\":\"span\",\"marks\":[],\"text\":\"A watermark can only determine that Claude was likely involved with the content at some point. It cannot distinguish “Claude wrote this” from “Claude heavily edited this.”\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"21737e9b4a0a\",\"_type\":\"block\",\"children\":[{\"_key\":\"341945dc456b\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"66088f7c7464\",\"_type\":\"block\",\"children\":[{\"_key\":\"50369e2adb52\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Do watermarks apply to translations?\"}],\"markDefs\":[],\"style\":\"h4\"},{\"_key\":\"0d6e8fc29ba8\",\"_type\":\"block\",\"children\":[{\"_key\":\"e2c12fd2e307\",\"_type\":\"span\",\"marks\":[],\"text\":\"Yes. A translation produced by Claude carries a watermark, because in this case every word is chosen by Claude.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"5a714ad30e5d\",\"_type\":\"block\",\"children\":[{\"_key\":\"734f99f9ae43\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"2d4cd90f79ba\",\"_type\":\"block\",\"children\":[{\"_key\":\"7297610c09d2\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"What about older Claude models?\"}],\"markDefs\":[],\"style\":\"h4\"},{\"_key\":\"0c5b084f6b47\",\"_type\":\"block\",\"children\":[{\"_key\":\"0224f8040129\",\"_type\":\"span\",\"marks\":[],\"text\":\"The EU law includes a transition period for Anthropic models launched before August 2, 2026, and we’re working to add watermarking for those models as well. This will be rolled out over the coming months.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"8b3cc52a73d7\",\"_type\":\"block\",\"children\":[{\"_key\":\"3c2014be972d\",\"_type\":\"span\",\"marks\":[],\"text\":\"\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"a2639ab325df\",\"_type\":\"block\",\"children\":[{\"_key\":\"d397ac1b1928\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"How does this differ from AI detection software, like Pangram?\"}],\"markDefs\":[],\"style\":\"h4\"},{\"_key\":\"9e14e5abf080\",\"_type\":\"block\",\"children\":[{\"_key\":\"83807a20084b\",\"_type\":\"span\",\"marks\":[],\"text\":\"AI detection software uses a different method, because the companies that provide it don’t have our key. Among other things, those services look at aspects of the text like the subtle (and not-so-subtle) “tells” that often appear in AI’s phrasing. For example, AI models appear to be fond of the construction “this isn’t [X], it’s [Y]”, and use the word “quietly” a lot more than you might expect. Picking up on these patterns is fundamentally different from checking for a watermark.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"a39748c15dfa\",\"_type\":\"block\",\"children\":[{\"_key\":\"3e8ee9b9dd07\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Does this change who owns a given output, or who is legally responsible for it?\"}],\"markDefs\":[],\"style\":\"h4\"},{\"_key\":\"0ca985b7ad7d\",\"_type\":\"block\",\"children\":[{\"_key\":\"028559d6317e\",\"_type\":\"span\",\"marks\":[],\"text\":\"No. A watermark only helps test whether Claude might have produced or processed the content. It doesn’t say anything about ownership or authorship, and doesn’t change a user’s rights under our terms. We only apply the watermark when Claude was involved in processing the content or file.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"abba279e973c\",\"_type\":\"block\",\"children\":[{\"_key\":\"80fc26e2bd60\",\"_type\":\"span\",\"marks\":[],\"text\":\"\\n\"},{\"_key\":\"a2f765c7500b\",\"_type\":\"span\",\"marks\":[\"em\"],\"text\":\"Updated Sep 1, 2026: \"},{\"_key\":\"ab47e5122fee\",\"_type\":\"span\",\"marks\":[],\"text\":\"Provided up to date information on the watermarking detection API. \"}],\"markDefs\":[],\"style\":\"normal\"}],\"sidebar\":{\"isVisible\":true}}]}],\"$L1f\",\"$L20\",\"$L21\"]}]}]\n"])</script><script>self.__next_f.push([1,"1a:[\"$\",\"footer\",null,{\"id\":\"footer\",\"className\":\"SiteFooter-module-scss-module__JdOqwq__root\",\"role\":\"contentinfo\",\"aria-label\":\"Site footer\",\"children\":[\"$\",\"div\",null,{\"className\":\"page-wrapper 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