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I notice the "Limitations" section talks about how content only at some point touched by Claude may return a positive, and content that returns a negative may still be Claude generated. But I really would have liked for them to state explicitly that entirely false positives where a piece is fully human-written may still be marked as generated, because too many institutions with the power to ruin someone's life over that have trouble understanding the concept.
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> 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.

I'd like to know a lot more about how that works.

A lot of my interactions with Claude return pretty precise text. If I ask it to edit a project and refactor a specific function in several places I know exactly what I want to happen, it will NOT be OK if those refactors have some kind of weird pattern baked into their text to act as a watermark.

I guess this may be covered by this:

> Content generated by Claude may not carry a detectable mark if, for example: [...] The passage is very short, leaving too little text for a reliable signal;

>I'd like to know a lot more about how that works.

My guess is that it works like Gemini's SynthID: by altering the logprobs of the next token.

Like, for every 10th token, instead of outputting the most probable, it outputs the 17th most probable, or something. (Obviously it's way more complicated but I think conceptually this is how it works.) No human will notice this, but a classifier trained on Claude's output will.

So it's not like the watermark is the words "le epic bacon" and Claude will output "le epic bacon" in everything. That would be extremely annoying (and easy to defeat).

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My guess is it will be similar to how Genius watermarked lyrics, using things like variants of punctuation

https://www.pcmag.com/news/genius-we-caught-google-red-hande...

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It was quick :) … https://claudewatermarkremover.app/
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Most likely this method https://arxiv.org/pdf/2301.10226 (EDIT: and Google's SynthID paper which builds on it https://www.nature.com/articles/s41586-024-08025-4)
If different model providers use different green logits, does that mean they can only tell if the text came from their own model?
That "just add a constant to the green logits" as a fix to the entropy problem is so elegant I love it.
> I'd like to know a lot more about how that works.

Count load-bearing words using two different algorithms in a belt-and-braces fashion

One thing worth flagging: those words are load-bearing
Fair - I should have been honest about the watermark.
Belt, braces, and suspenders.
Don't forget the suppositories
This is why I never use max effort! I’ll stick with my suspenders, thank you.
You’re absolutely right. Yo momma is doing a lot of heavy lifting here. Her load-bearing methods have the right shape.
That’s the real shape of the problem.
Maybe there is a reason why Opus 5 produces such word salad conversations
What happens if someone handwrites a Claude output, then someone uses that handwritten text as a reference. Now you've got a watermarked idea which may have no direct linkage to the usage of Claude.
Are you worried about being accused of using LLMs to generate your work? As long as you don't plagiarize you have nothing to worry about.
You can't make a blanket statement like this without knowing how the watermark is implemented.
I'm not too sure about that, people making stuff have already gotten penalized by overzealous AI detectors, most recently Kurtzgesagt.
What if I unknowingly read content written by Claude in various articles and it influences my own writing style?
How is that different from referencing digital text that someone copied and pasted from Claude?
Because there's an expectation of authenticity from the written word. If you've referenced something handwritten, you don't expect it to be the output of an LLM.

Similarly, if you quote someone word-for-word, you wouldn't anticipate their words to be flagged as Claude content, but if someone memorized Claude output word-for-word. That would still be classified as a Claude output.

Going forward you could categorize the influence of Claude on a population based off a percentage match between their spoken words with the LLM prose.

It will just thread some load-bearing seams through the paragraphs.
> have some kind of weird pattern baked into their text to act as a watermark.

public abstract class BaseAnimalBeanFactoryGeneratedFromClaudeFactory

Most likely watermark will be proportional to the input/output ratio, i.e. if you input a long document and ask to make edits, it will not attempt to watermark it. On the other hand, if you provide a tweet and ask it to write an article, that will include watermark. Just a guess (and yes, it feels flawed)
Load-bearing==claude
I can tell you how: Claude produces a huge wall of text with jargon ridden bullshit and invented terms no human subject matter expert would seriously use and overuse.
I've heard that this kind of watermarking process works by biassing the statistical sampling towards a partition of the set of possible next tokens (red set and green set), at each position. It might only be a slight nudge each time, but over a sequence of tokens, the likelihood of repeating the bias by chance is increasingly improbable.

The bias is different for each position and follows a defined RNG, seeded somehow predictably.

Can be either an open algorithm, or not. If not open, then an API could be provided to determine if text is watermarked or not.

How it applies to code - maybe it could be a subtle nudge to symbol names, etc, I'm just speculating (I only read about this in passing very recently).

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We need to just stop pretending we can reliably tell if plain text is written by an LLM.

It’s just not a reasonable ask.

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So my code that Claude makes, which previously was using the best (most probable) tokens for the job, will now be getting worse in random positions, to appease a voluntary EU suggestion. Love that.
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I have had a hunch for a while now that (in addition to these tools), Anthropic has actually leaned in to Claude's distinctive manner of writing since it makes the text more obviously AI generated and thus less susceptible to misuse.

That's not necessarily the same thing as a markov-style fingerprint but it could be a correlated factor.

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Can someone help me understand how exactly this watermarking of text works?

Given that text is, well, text, and not some kind of binary format, I don't see how any watermarking can work unless you insert characters which are invalid under Unicode. I further don't really understand how this won't be perceivable by assistive technology (the "watermark" will just appear as either unreadable characters, or if the watermark is mixed thoroughly enough into the text, it will scramble the text to any speech synthesizer and will make it really really obvious). Thus, I don't see how this wouldn't be insanely trivial to remove. And this is before we get into things being put on the clipboard. Sure, I can press the "Copy" button at the end of each response, but what I can also do is manually select the response and copy it, or only copy partial selections, or any number of other things. How does this "watermark" (or any "watermark" technology) take into account this?

So, really, to summarize this: I see no way of this actually being technologically achievable unless we revise the very core of how computers work and encodings for textual information. So I'm very curious as to how this is actually supposed to work.

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An interesting factor of this is competition.

If Claude was the only model family they could ship a change like this and users who want to cheat (or don't like watermarks for other reasons) would just have to put up with it.

In a world with many different competing models, the risk of losing customers to other providers over this is much more real.

Maybe they've looked at the numbers and the portion of people who clearly use Claude to cheat on examples etc is so tiny that losing them to other providers isn't a problem?

Scott Aaronson spoke about this in a colloquium where he said that this was mooted at OpenAI before the decision was made by Altman to not implement it for the reasons you describe.

https://youtu.be/9udWn1Hlj_s?si=VWOiK5-y4zcyDoHI

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I’m more worried that this will degrade performance. I want the best results from a model, not the results that fit a constraint that’s not defined by me. Any increased cost or latency is also unacceptable.
There are already small models trained specifically to prevent statistical detection, e.g., https://huggingface.co/kalpeshk2011/dipper-paraphraser-xxl

I guess whoever is the policy maker is assuming that some protection is better than none and that most people will not reach for such tools.

Either that or they want to comply with the EU AI Act when it affects them.
> We’re also working to enable users and other third parties to detect Claude’s embedded watermarks and provenance metadata.

This seems to be similar in execution to Google's SynthID. I hope they release actual code the technically proficient can use, unlike SynthID which can only (afaik) be queried with Gemini's UI.

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Seems like an awful idea. I hope that that "watermark" will soon be discovered, reverse-engineered, and that tools to remove it will appear.
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People with dyslexia and dystrophia, commonly use LLMs to proofread content. Even Anthropic admits this is a limitation.
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> "Claude models launched on or after August 2, 2026 support marking at launch."

No Anthropic model has been launched in August.

> Generated text will carry embedded watermarks, and generated files will include digitally signed provenance metadata where supported.

This should make it easier to catch cheaters who use Claude, right? Unless everyone runs their artifacts through some watermark and metadata sanitizer?

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Text is too low bandwidth to classify reliably without lots of false positives. Especially as people start talking like LLMs.
I don’t like the idea of hacking a response to contain a watermark. I also don’t like the idea of false positives detections coming directly from Anthropic. If people read more AI generated content, people will probably start writing more in that style
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I have no idea why you were down voted for this. Language is alive and people adopt it from sources they hear a lot.
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I know you're gonna read this so I'll be blunt. This is bad for your brand.
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OpenAI has been watermarking their images with C2PA for some time.
If the western AI companies are forced to comply with this type of BS, and develop their models to do their job while balancing a book on their head and hopping on one foot, the Chinese models just got a free pass to completely dominate the frontier.

EU regulation does it again!

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They should just replace the spaces by one of Unicode special space characters.

Can it be circumvented? Of course. Will most people go through the trouble to circumvent it? No.

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Wasn't enough to play cat and mouse with ad removal, now we can also do the same with watermarking.
You could flip bits in the font itself, but I'm really wondering how portable this is.
I expect a “Prettier” for AI generated text in the near future.
As if "AI generated content" even exists instead of LLMs being a piece of tooling that is directed by a human author.
This is terrible news given the stigma against AI in general. I really don't want people singling me out for it.
Does it mean their models will always write slop? Making the writing non-collapsed to specific patterns seems to break any injected/learned fingerprinting.
So this won't be happening in the US, but in the EU:

"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."

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Good.

They should make it easier, to detect slop so we can ignore it quickly.

I hope Pangram makes an API or an extension to analyze a page to detect slop on a page and then closes the tab immediately.

Nobody should be wasting time on garbage LLM output in code, text, image and videos.

Panagram is a scam.
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Yet another reason to support open-weight alternatives, I guess.