Anthropic's ‘watermark’ text adulteration in Claude is a perversion of writing | Hacker News Reader

Anthropic's ‘watermark’ text adulteration in Claude is a perversion of writing

daringfireball.net

825 pointsropbear731 comments

My biggest concern is that checking any text for watermarks requires sending the entire text to Anthropic. And even that is not sufficient, as the text might have been generated with ChatGPT, Gemini, Grok, Mistral, ...

So every check requires sending the text to as many AI providers as offer a watermarking detection API, almost all of which have a very dubious track history with obtaining training data through illicit means.

Any university using AI detection in their submission pipeline, or lawyers, editorialists, proofreaders that check for AI marks will be sending significant amounts of text like unpublished research, books, potentially internal documents and more, most of which is high quality human written, to dozens of AI companies, blindly trusting they won't train on any of that.

Would really like to know how their watermarking technique works, and if they can use it to store arbitrary information in the text (I assume they can if only in a limited way). I assume if the text is long enough they could add all kinds of metadata that would then be undetectable as the model that generated the text is the "cryptographic" key that encodes the data. I wonder if you can have another model run over the text and destroy the watermark. I predict an interesting cat and mouse game to develop.

Doesn’t this mean Anthropic can accuse anyone of using their AI to write for them?

I think this is a very real concern. But I’m not sure of any way around it. Any stenographic system that you have the code for can be trivially defeated.

I wonder if this would be a good use for homeomorphic encryption. There might be a way to let anthropic check some text without actually giving them access to the source text. Any experts around? We could use your skills!

>Any university using AI detection in their submission pipeline, or lawyers, editorialists, proofreaders that check for AI marks will be sending significant amounts of text like unpublished research, books, potentially internal documents and more, most of which is high quality human written, to dozens of AI companies, blindly trusting they won't train on any of that.

Uh, yeah, why do you think it's setup this way? The frontier companies desperately desire more high quality human text and this is how they are planning to get it for free.

And I'm sure students will use tools to have every other paragraph written in the style of a different AI, in an attempt to defeat this fingerprinting.

That's why detectors like Pangram exist too I think.

Sounds like a business opportunity.

You've discovered the perpetual mutually assured destruction money generator — guess what the best defense against LLM spam also is?

LLMs cause a wide number of problems, the good news for our investors is that they're all solvable with LLMs.

Exactly, so even if you are avoiding AI, any interaction with society is now being structured so you have to submit to the digital surveillance equivalent of a cavity-search machine. What a dystopia awaits the budding generations.

Anthropic had absolutely nothing to do with this. The Chinese models will soon be adopting such devices as well. It is an overwhelming force coming inter alia from educators worldwide.

I expect them to work as reliably as AI text generators do now...

> checking any text for watermarks requires sending the entire text to Anthropic

Couldn’t it be checked in the TEE using confidential computing to keep Anthropic’s algorithm secret?

While Anthropic is sharing this publicly, there’s isn’t much reason that other models could quietly be doing this or start.

Local models could probably catch some patterns.

That's just storing what they output in a database and then checking, not a watermark.

> And even that is not sufficient, as the text might have been generated with ChatGPT, Gemini, Grok, MistraL

I would think that these things would eventually converge and we’d get one watermarking algorithm as an industry standard. That way, all major provider would follow it and we’d get independent software for checking. This would partly limit the efficacy of the watermarks, but on the other hand if it’s done correctly, removing the mark could still be enough of a pain that casual users would not bother. That would obviously depend on a lot of factors. It would at least add significant friction in the production of daily slop.

Of course it wouldn’t do much for thing like foreign propaganda but that’s a whole other discussion we need to be having.

> Any university using AI detection in their submission pipeline, or lawyers, editorialists, proofreaders that check for AI marks will be sending significant amounts of text like unpublished research, books, potentially internal documents and more, most of which is high quality human written, to dozens of AI companies, blindly trusting they won't train on any of that.

Isn’t it already what they are doing right now with some of the plagiarism detection tools? Not every university is going to have a representative corpus, and yet they are all using the software. So I guess the provider is doing the work of feeding all that data to their algorithm.

I’m worried that until such tech is perfected, pervasive and uniform across all models, education will be dead, as it certainly is at the moment. Flat out dead.

I read stacks of term papers all year and it is a reality that, apart from such schemes, we are in an extinction event for civilization.

its lovely training data. no detection? add to training set -_-.

its also kind of laughable that somehow people are trying to prevent the outputs not to be altered. Asif you cannot manually paraphrase anything you can read. So the only solution would be, to make it utterly unreadable (which is not possible, it obviously defeats the purpose of the thing).

Not to mention local models ofcourse :-)

Why not switch it around? Solves problems of privacy (no data upload), is far more doable and it's far more important to be able to verify content has not been tampered with after originating from a human or capture device (like a camera). We also have decades of cryptographic experience in reliably signing text, images, video, etc. and it doesn't break apart because a text is too short.

Having proof that content (especially images and video evidence) is unmodified (whether via Photoshop, Paint or a model) is far more valuable then having evidence that an image was manipulated or generated fully by a model (which still leaves other forms of manipulation), I feel the same goes for human authored vs generated text. Free to admit that using models to generate any kind of media whole-cloth is still unappealing to me and I still pay for commissioned artwork or make it with my limited abilities for what that's worth. Do like to (poorly) write my musings too and see UX as something were thoughtful contributors (like the opinionated, sometimes controversial, but certainly talented GNOME Gitlab contributors) can make a major impact.

Code can be beautiful, interesting and serve purpose beyond execution, of course, but for most people, in most cases, it does not in the same way as audiovisual content (not limited to art). Having code just to execute and resolve a problem can have value all in itself, the code being a means to an end whose quality, let us be honest, was barely a concern in most corporations long before LLMs.

Also have rarely (honestly never) before LLMs fully owned all parts of any code base, always relied in part on someone's prior effort in (Flutter/Dart mostly) packages, whereas when writing, drawing, etc. I have far more situations where I make something from scratch and everything there is only there because of my conscious decision. Even simple marketing mockups that, quality wise, any modern model would beat feel different when I was fully in control, where to place what, etc. Objectively worse (at my skill level), probably, but still never the same.

Knowing something was made from scratch by a human has value to me, beyond misinformation prevention. Knowing for a fact that LLMs were used instead of importing a library, using a template, or something similar that leads to expending similar amounts of effort, I don't see that being nearly as valuable. Heck, with all the importing and my experience back then vs now, I am spending more effort actually fully reading any LLM output in my code then I spent back then auditing Flutter/Dart packages. Then again, LLM output fails far more unpredictable then those messy packages that simply got Gradle to take down my system...

Happy to admit, I have been skeptical of watermarking LLM output being feasible for quite some time and having looked into SynthID Text and proposals being researched, I am convinced that it is challenging to impossible beyond the lowest common denominator and less important then proofing human authorship.

It will catch people just copying LLM output into their replies without thought, which is not a negative in my book, especially if it is not discernibly affecting output quality in regular use cases. Anyone who wouldn't copy Wikipedia into their dissertation will, in my opinion, be able to bypass text watermarking as proposed however, I feel we need to be honest there.

Thing is, if that's the case and text watermarking will only ever catch LLM created slop, is that a bigger problem then the misinformation, harm to creators due to authorship questions and accusations, making it harder to use evidence in proceedings, teachers not trusting students even when they did the work themselves, etc.? Signatures for all such cases will be difficult to implement, yes, but I feel are going to be of greater value in the not to distant future and I equally feel are not impossible, not least because idiots will always want to hide their LLM usage, whereas human authorship is something they take pride in and want to proof.

> blindly trusting they won't train on any of that

being allowed to train on any data that you can legally obtain ought to be a right for anyone.

After all, i am allowed to learn off anything i can legally read (and perhaps even illegally read). The only thing not allowed (rightly so) is to produce a copy with enough similarities that it can be replacing the original.

> I want any LLM I use to choose the very best, most precise words at every single decision point.

Then bad news: LLMs already use randomness in a fundamental way. Each time they go to generate a token, they first generate a probability distribution of possible tokens. Then they pick one randomly according to this distribution. The technique described can be thought of as making the random number generator pseudo random. The output it generates is one of the possible outputs it would have generated before, just now it's deterministic and will generate the same thing every time.

The best discussion I've seen so far is from Scott Aaronson: https://scottaaronson.blog/?p=6823

> To illustrate, in the special case that GPT had a bunch of possible tokens that it judged equally probable, you could simply choose whichever token maximized g [a cryptographic function]. The choice would look uniformly random to someone who didn’t know the key, but someone who did know the key could later sum g over all n-grams and see that it was anomalously large. The general case, where the token probabilities can all be different, is a little more technical, but the basic idea is similar.

That's inaccurate in two ways:

(1) The behavior that is approximately what you describe is not "fundamental" (though it may not be something you can disable on some hosted providers), it is an option that is not fundamental (and with runtimes where you have full control can be either disabled or tuned in a large number of manners), and

(2) The actual behavior that is approximately what you describe already usually involves use of PRNG (with a user or harness supplied seed), not a true RNG; the change to do watermarking isn't going from RNG to PRNG, it involves adding an additional set of constraints on token generation on top of the existing ones, which inherently compromises quality.

I think this is a key reason why humans write better prose than LLMs - we can try to choose the best word every time, and go back and restructure sentences and paragraphs if we want.

On the other hand, LLMs are forced into picking some likely-ish word, and then have to build the rest of their response to retcon that choice into making sense.

Even good human writers would probably struggle with this constraint. It would be like someone interrupting your writing to tell you the next word MUST be such-and-such, and then you have to try and make it work as best you can first try, without going back to edit. The result would probably be a little clunky. (Maybe it’s impressive LLMs write as well as they do.)

Yeah this is my main issue with the argument. He acknowledges in the article that LLMs are already non-deterministic, but he doesn’t seem to actually understand that.

I think the article is wrong on this but it's more subtle than that. Probability distributions have a peak; there is still a token with a peak probability. What's interesting about these techniques is that token by token it can actually make the peak token even more probable. A distribution doesn't have to be "flattened" to leave a watermark - it can be "amplified" and made "more peaky".

This is true and the author seems to not understand the problems with greedy (top 1) decoding or the fact that watermarking affects only high entropy tokens. But the published watermarking methods still have a slight negative effect on perplexity, so there is something more to it.

The quality of the LLM just _is_ the quality of the token probabilities it generates. Better quality token probabilities, better quality output. Worse quality token probabilities, worse quality output.

Watermarking changes the probability calculations for reasons other than quality. It can't not compromise quality. It literally leads the LLM to occasionally chose different tokens just for watermarking purposes.

I cannot believe the markdown guy is this deranged.

Another good way to think about this is that it does change the output, but in a way that is equally likely to make it "better" as it is to make it "worse".

That's missing the point. It's the distribution that's the "best", not the tokens. Then Anthropic comes in and makes the distribution something other than the best. The only saving grace is that Anthropic says it's not that bad.

Even so, I don't think it will stop here. Once this is in place, the next step is to put more and more identification into the AI generated content; might as well pack it in, it's not that bad, and if it is they won't admit it. There's no way for anyone to check. And your argument will still be technically correct but missing the point.

This is not the same thing

> "The exact words we choose when writing matter."

Then write your own damn text if you care about the exact wording so much

His complaint seems to center on conversations between him and the LLM, not copy being written for publication elsewhere. That is, if Claude is going to teach him a new skill, he wants it to pick the most accurate words possible, not "pretty accurate words, subject to watermarking techniques".

If the exact words we choose when writing matter so much, then why use a non-deterministic LLM that produces slightly different output on every run?

Additionally, LLM are already rolling the dice on different wordings so I don't see how this watermarking makes it any less precise.

You are responding to the original article, authored by John Gruber, who, last I checked, has been writing his own damn text multiple times every damn day for multiple decades as a primary vocation.

I’m willing to venture that Gruber is on the list of folks that get to hold the opinion choice of words matters.

He's a professional writer. As the article says, even if you write your own words, this is still a problem with proofreading, copy-pasting references or quotes, and "AI checkers".

The exact words matter to people who people who don’t use it to write for them. A lot of people use Claude as a friend/therapist/romantic partner/etc. That’s who I imagine would be most affected

OpenAI released a feature that lets you tweak ChatGPT output to sound more human and like yourself and correct inaccuracies:

http://blog.tyrannyofthemouse.com/2026/04/open-ai-strikes-ba...

I mean this is the thing that really comes off hard.

If you want precision and clarity of your writing, then you need to hand write it. Just like when you are optimising, its common to drop to a lower level language because the compiler doesn't express what you want. Sure its hard, but you know, thats kinda the point.

Even if you don't want that, the LLM is an average of the style it was trained to give out. Which is a homogenisation of the language to create a vague padding medium between a few generalised facts. (because a. it makes it less jarring when stuff is wrong, because its smeared over a higher amount of text and b. it looks more 'professional' because American business English is all guff and no meat)

Also yes, two isolated phrases may have subtly different meaning, frankly, the nuance is missed on most people. If you look at the interactions on here, at least 25% of the arguments are caused by people angrily reacting to the things _they_ thought the other person was saying, rather than what the actual person was saying.

So no its not a perversion, the LLM is, if you're gonna be picky about things.

What are you talking about? I understand OP has the perspective of writers, but let’s say you’re asking an LLM to explain a concept and it uses green words that are actually more difficult to understand. Or you ask for an analogy to explain a topic and the analogy doesn’t quite land because the description used “gray” instead of “overcast”.

I'm sure he honestly appreciates the pushback.

why you act so tough bro?

What an absurd take on a very reasonable concern. As much as I hate “obviously AI” writing, I don’t understand why we have to handicap the tech and prevent it from improving. This manipulation of word choices virtually guarantees AI will always sound like a robot.

Do people not realize this will apply to ALL Claude output, not just writing you ask it to produce?

> Marks will apply to output from supported Claude models across Claude Platform (API), Claude, Claude Code, Claude Cowork, and Claude Tag, and wherever Claude is offered.

I've never asked an LLM to generate writing I wish to post as my own. I don't understand why we think it is a good idea to fudge all output just so people can't cheat on their homework or generate slop. It won't have any impact on those things because there will always be models that don't do this. All it will do is increase the rate of false negatives.

It is deeply misguided regulation and Anthropic should have just said no on grounds of common sense.

One could also use butterflies to write ;) https://xkcd.com/378/

The problem is, that LLMs worked very well for me to improve my writing. Especially as I'm not a native speaker, it was a great way to improve the legibility of my work.

I want a tool that helps me improve my writing. A tool I can learn from. Not a tool that switches out "bananas" to "airplanes."

I'm was using Claude Opus and now Fabel extensively for editing my texts and I find the recent updates abysmal. Not sure if it's due to the Text Watermark.

Before Claude was great in sharpening the meaning in my writing, it's now close to unusable.

LLMs are no more than pen and paper at this point. Especially for those who aren't trying to create slop. We all would want our pens to accurately reflect the strokes (well in this case thoughts) rather than adding tiny watermarks to identify that it is generated by a particular pen or a user.

Watermarking per model is just the start. The method is cheap enough to distinguish individual users.

Crazy how a smart person like this fails to understand the gumbel softmax technique. It does not affect writing quality at all, provably. The very fact that there is generally no "best next token" with 100% certainty is precisely why the trick works (you cannot watermark a response to "respond with the To be or not to be soliloquy from the first folio Hamlet", for precisely this reason).

It seems to me like he started out mad and looked to justify it.

I'm skeptical that anybody generating LLM text is really all that concerned about optimal word choice. Or even particularly good prose. But let's pretend that person exists.

If that person tried, say, an open model and that same model with watermarking applied, I'd be eager to hear their thoughts on the prose quality. Especially if they built an experiment harness and rated a few hundred blinded examples and found a measurable difference.

But getting this upset in advance of any demonstrated problem? It really seems to me like the point isn't the point

>fails to understand the gumbel softmax technique

I think in this case it doesn't help that there are multiple watermarking schemes, and the easiest for people to understand is the red/green scheme by Kirchenbauer et al. (https://arxiv.org/pdf/2301.10226), which does technically distort the logits (but I'd argue only in cases where you wouldn't notice it anyway).

I wasn't aware of this gumbel softmax scheme, it seems you're referring to https://simons.berkeley.edu/talks/scott-aaronson-ut-austin-o... ? That's really clever as it doesn't even distort the logits, basically cryptographically indistinguishable from a "real" random sample unless you have the key.

The actual scheme Claude uses seems to be neither of those two though, they say it is SynthId-text which seems to be tournament sampling based.

>It does not affect writing quality at all, provably

Prove it, then? It's not a claim that GumbelSoft paper makes: "Regarding generation quality (perplexity), GumbelSoft shows relatively low perplexity"

https://arxiv.org/html/2402.12948v3

If this is true then the probability of the detection tools flagging completely human generated text as AI generated is non-trivial. Let's say I write a completely original piece and the detection tool says there is a 36% probability it was generated with Claude. What then? Now it's up to the person looking at the score to cast a subjective judgement. Maybe to me, anything over 25% is unacceptable. Maybe to someone else, it must cross over the 50% threshold. This is the problem.

Cognitive surrender.

Gruber is always happy to lead with his emotions and backfill justifications for them. See his recent debacle with App Store review: https://daringfireball.net/2026/08/retraction_app_store_reje...

Making blog posts about AI that make it apparent that the tech is going whoosh is a choice.

It's a writer perspective versus a reader perspective maybe?

Sometimes when you're trying to write something, it really seems like the exact words matter a lot. Suggestions made to be more direct or use a more common word here or whatever seem to really impact the thought that you're trying to communicate.

Certainly we've all had times when trying to communicate clearly when the specific words seem very important.

> The very fact that there is generally no "best next token" with 100% certainty

This is not entirely accurate. Sure, there's never a token with 100% certainty, but there are often tokens with 99.9% probability, but this technique of course does not change how such a token is sampled.

By definition watermarking narrows and biases the response distribution. Clever algorithms might reduce the perceptual impact and minimize some cherry picked metrics, but it's still worse.

> The very fact that there is generally no "best next token" with 100% certainty

Indeed.

It's frankly bizarre to see the assumption to the contrary being made by someone who's been passionately blogging by hand for years, who also happens to be responsible for the notoriously vague, humanistic, DWIMmy Markdown standard.

> a smart person like this

Can you give an example of something smart John Gruber has said or written? Because I can't think of one, but I can think of many dumb ones.

I couldn't be happier that people are mad about it. To quote Calvin, "nothing helps a bad mood like spreading it around"

> “By definition it must make text worse … because the nature of the watermarking algorithm requires it to sometimes increase the probability of selecting a worse word choice and decrease the probability of selecting the model’s best choice.”

Gruber made an effort to but doesn't fully understand how SynthID works. LLMs select the next word randomly from a set probability distribution, so there is no "best choice" unless you run the LLM with a temperature of 0 which would give out terrible results. Anthropic runs a non-distorting version of SynthID that doesn't change the probabilities of the underlying distribution of tokens. It makes the watermark less likely to work over smaller samples but preserves text quality. I encourage the mathematically inclined to read the paper:

https://www.nature.com/articles/s41586-024-08025-4

> LLMs select the next word randomly from a set probability distribution, so there is no "best choice" unless you run the LLM with a temperature of 0 which would give out terrible results.

I'm not understanding how the word with the highest probability isn't the "best choice"?

I came here to quote the same sentence. Here's another way to look at it:

Suppose there actually is a best word choice. The LLM doesn't know what it is but makes a guess. Maybe it's the best one, maybe it isn't. The probability that SynthID changes the best choice to a worse one is equal to the probability that it changes a worse choice to the best one.

>I want any LLM I use to choose the very best, most precise words at every single decision point.

Does the author think he is currently getting T=0 output from Claude? Is he under the impression that T=0 produces the "best" writing?

This entire article just seems so detached from the basics of how LLMs work.

> Does the author think he is currently getting T=0 output from Claude? Is he under the impression that T=0 produces the "best" writing?

No and no. I am not sure I agree with his point but I know he is not ill-informed on either of these points, because I mentioned them to him a couple of days ago.

I think it is a common misconception for anyone who hasn’t actually tried implementing a LLM to think that there is a best choice of token at each step and that following every locally best choice will lead to a globally “best” writing. This is intuitive yet wrong and perhaps there is no better way to rid oneself of this misconception other than actually implementing a simple LLM.

This is a reductionist counterargument. Sure, the passage you quoted does sound like he's being equally reductionist. But the underlying point does not depend on T=0. You could state it as saying that instead of minimizing error (maximizing "writing quality"), you're using some of that error for watermarking and minimizing the rest.

Describing it in terms of a word-by-word choice is simpler, but writing quality is dependent on the interplay between words.

"The weather today was cold and {grey,overcast}." If the next sentence is "I miss yesterday, when it was {bright,sunny}." then the choice between "grey" and "overcast" is no longer neutral. "grey" and "bright" pair together, as do "overcast" and "sunny". Or if you disagree with my aesthetic sensibilities, consider:

    The weather today was cold and {grey,gray}. The {color,colour} of the sky matched my {humorless,humourless} mood.

I think the author is just mad people will be able to detect and filter out their AI slop writing in the future.

Gruber shows here that he really doesn’t understand the basics of how LLM text generation works. It’s weird he picked this battle about the quality of writing in LLMs. Was he planning to use LLMs to write his articles?

Well, not that weird actually. He just has a hard-on against anything that comes from the EU since Apple got in trouble. If the EU said tomorrow that they want peace in the world he’d be in Fox News the next day calling for an invasion. As a former reader of Daring Fireball, it’s just sad to see.

Gruber went from the naively wrong claim that it would insert secret hidden characters (which would be trivial to remove, obviously), to quickly writing a giant essay as if he's an expert on LLMs. Like you said, he is strangely fixated on the EU, and is certain any EU rule is the worst thing in the universe, and this whole piece seems motivated by that guiding force.

Further he later compares Gemini to Anthropic models, saying the latter "writes better", emptily ascribing this to the synthid stuff. I think he heard that Anthropic currently has superior models, but it certainly isn't because they "write better", and if anything Opus 5 now is virtually unintelligible, before the fingerprinting.

The fingerprinting stuff sounds weird. If the EU wants it, it should be limited to the EU, and Anthropic is fully capable of doing that but clearly saw value in recognizing their own output. Is it going to destroy the quality of the output? We'll have to see, and this anti-EU piece, predicated on utter ignorance of the field, is not convincing.

Yes, I decided to stop reading his blog relatively recently after some extremely hot takes on EU policy. I don't feel his thoughts on the matter are particularly well-thought-out, and I feel like he's just stanning for Apple from his priors rather than from any grounding in reality.

I dunno, I guess that's what you should expect from Gruber but these EU-bashing articles lowered the enjoyment I got from his blog underneath the bar for me.

Translation: No one can ever again use Claude for proofreading their own prose unless they’re willing to risk that the whole thing might be flagged as having been generated by Claude.

I think that was intended, yes.

You know, back in the era when proofreaders were human, I never one met a proofreader who rewrote my text afresh, rather than annotating the text with a pen.

It's still possible to use Claude to proofread - highlight grammatical, flow, structure, logic errors and make simple suggestions for you to pick and choose or adapt as you wish. No watermarking will flag your text. No flaw accusations of LLM authorship will haunt you. All will be fine.

But if you want an LLM to rewrite your text, that's (a) not proofreading, and (b) should be flagged as LLM generated ... because it is.

I'm not sure the quoted statement is true. Proofreading like "point to problems in the text", if you fix the problems yourself and don't copy-paste the solutions given to you, should still be safe, shouldn't it? So, human-written text should not be falsely flagged if you use LLM for proofreading.

And if you copy-paste the answers from LLM, I think it's only fair the end result gets flagged. You're not writing it yourself.

Can't the LLM just generate e.g diffs? Or some other intermediate language. Then the watermark is lost when the translation step is applied.

It is quite just, if you think about it. Human works are copyrighted and protected at the moment of creation. All rights reserved. Yet, LLM outputs are uncopyrightable. Therefore, if Claude or any AI has processed my copyrighted work, the end result is uncopyrightable and in the Public Domain. The public has a right to know: is this a human copyrighted work, an LLM PD work, or is the human falsely claiming authorship in order to retain copyright?

A point of confusion for me, however: is every watermark unique? Is every algorithm for watermarking going to vary amongst models and amongst model versions? Will each model publisher keep this watermarking as a trade secret, that they alone can detect? If so, this can't scale! How do you detect "JoeBob 4.3 LLM" output? By querying every single model's watermark-detector? And if they all work by re-running the model and using tokens anew? That is extraordinarily wasteful.

If a watermark is not self-evident, or universally detectable, then it is no good. Take, for example, US currency. The security measures are published and well known. Any count-out room in retail has a big poster indicating how you can detect authentic US bills. Nobody has to accept non-US currency in the US, and so the only authenticity you need to worry about is your US bills alone. LLM watermarking has none of this in common. Currently sounding like a shitshow, if you ask me.

The question is, when is the "pro writer" version coming that lets you control this behaviour but costs more? Like night follows day, this will happen.

They will need to dodge around the EU requirements but it will probably just come down to an alternative method to watermark or a contractual assurance you won't mis-represent the source of the text.

Rands made this point a few days ago as I recall. Worries about having his tool corrupt his writing during editing, etc.

The thing that could change is interpreting "the whole thing as generated by Claude"

wait what?

but proof reading is a linter, not a writer. the proof reader will say "I think this is clumsy can you try x,y & z"

> One of my fundamental problem with this is that no two synonyms carry the exact same meaning. “He leaped at the chance” and “He jumped at the opportunity” are very similar sentences expressing the same general sentiment, but they are not the same. The exact words we choose when writing matter.

Then why are you using an LLM to write? They're not capable of understanding such nuance. They do pick randomly between two synonymous phrases, they do not use some super smart algorithm to pick the one that sounds the best.

This excuse doesn't hold any water at all - Occam's razor says the author is just super annoyed that his AI writing will be identifiable as AI writing.

Yeah, I snorted at the sentence "The exact words we choose when writing matter." Well, then why the heck are you using an LLM to "write," man?

What a truly bizarre article. Arguments about pre-existing randomness, temperature and whatnot aside, I simply cannot comprehend what the author here really thinks the "best word" is. There's no such thing. We humans fall on familiar patterns of writing ourselves, so we may forego something with a flourish in favor of a more commonly-used word unless we put in effort to be "special", which should be used sparingly. That is to say, human writers are likely to choose a "worse" word in far more than the supposed 51% of cases, and that has no effect on the actual quality of writing in the end.

But even if there were such a thing as a truly "best word", for some context, what are the examples here? Mango vs pineapple? Gray vs overcast? In what case is one of these better, that AI would normally infer but would suddenly be "perverted" by SynthID? Do you think your emotional state and preferences are being evaluated if they aren't explicitly in memory? And if they are there, do you think that the generator will bypass those instructions in favor of the watermark instead of placing it somewhere you won't care? I just. Genuinely don't get it. There may be words that matter in specific contexts or to you as a reader, so you should bloody well put them there.

> “He leaped at the chance” and “He jumped at the opportunity” are very similar sentences expressing the same general sentiment, but they are not the same. The exact words we choose when writing matter. I want any LLM I use to choose the very best, most precise words at every single decision point.

Neither of these is "better" or "more precise"; in fact, LLMs will generally choose randomly between these candidates based on temperature, and SynthID should not distort the output of an LLM any more than the default temperature settings do already.

I agree that those are not the same sentences, but if the difference matters to you, you shouldn't be using an LLM. This difference exists at the level of what sounds better and is more evocative; to an LLM, nothing sounds like or evokes anything. They simply do not write good prose.

I’m more concerned that this will negatively impact code generation. An additional constraint completely unrelated to code quality is unacceptable as far as I’m concerned. I was an Anthropic user but now I’m looking at OpenAI or even better, open models.

I was initially surprised that Gruber was so invested in the "quality" of AI-generated text, which in my mind is an oxymoron. But really, Gruber's interest here is with the EU. This forms part of his ongoing attacks on the EU, all because they have been forcing Apple to align with regulations.

Can we install random unapproved apps on our iPhones yet, or is Apple aiming to just be fined a trillion dollars because they make more than that from the 30% cut?

I am from EU. Alas it has a tendency to produce some idiotic regulations. Cookie banner, new packaging fee, etc. I genuinely think some Apple related ones hurt customers more than help them.

This article feels slightly incoherent. You want high quality precise writing and to use an LLM to generate it? Feels like those are diametrically opposed

Exactly. The watermark is proportional to how much text is AI generated. Either the AI really just “fixed some typos” (not enough AI content to hide a watermark) or the AI did most of the writing (enough AI content to hide a watermark).

This feels like the inevitable outcome of a STEM-only education system. Now people think there's a mathematical formula for picking the "best" words, instead of having to be thoughtful and creative.

I’m surprised by the comments here being so favorable to anthropic. The comments are right about there being no “best” token, and yeah Gruber may have an agenda here. But I think the fundamental principle is that this approach messes with the distribution in ways that deviate from the trained model. Take the “gray” and “overcast” choices. And lets say before applying synthid the percentages were 48% and 52%. Those percentages were learned from the training data and RL. To change those percentages to 45% and 55% in a non learned way makes it seem like training wasn’t important? Or more likely they dont have the data that shows the failure modes? also, don’t these choices compound the changes to the distribution in later sampling choices?

It is a bit of a mystery to say that “its okay to choose different tokens that we would have for watermarking bc people don’t notice” as though word choice doesn’t matter. If it doesn’t matter, doesn’t that mean that intelligence is more of a commodity than they would want it to be?

> To change those percentages to 45% and 55%

This seems like a fundamental misunderstanding of how this sort of watermarking works. (Either that, or I have a fundamental misunderstanding of how it works lol.) It doesn't change the probability distribution of the next token at all. If you were getting XYZ 48% of the time before, you're still getting XYZ 48% of the time. What's changed is where the random numbers come from. But as far as you're concerned, there's just as random as they were before, just like an encrypted message is indistinguishable from random bytes if you don't know the key.

> I think the fundamental principle is that this approach messes with the distribution in ways that deviate from the trained model.

But it doesn't! The distribution doesn't change at all. The only thing that changes is that sampling of that distribution becomes deterministic as per a precomputed seed.

I’m sure it matters. But how much does it matter? How much (perceived) intelligence would you be willing to sacrifice for an accurate AI predictor?

I’d sacrifice a few %, easily. Maybe 10%. The models are getting smarter at such a fast rate that I’d be willing to lose a month or two of progress to help slow down the AI cheating epidemic.

It sounds like you expect this fingerprinting approach would dramatically reduce the intelligence of their models. But I’m sure anthropic has measured it. I doubt they would have rolled this out if the intelligence cost were that significant. I suspect the cost is less than 5%. I personally can’t tell any difference from before they added fingerprinting. I bet you can’t either.

> To change those percentages to 45% and 55% in a non learned way makes it seem like training wasn’t important?

I think (or I hope, anyway) that this overestimates how much impact the tweaks actually have on text.

The model has some things it "wants" to say. If it wants to tell a story about how someone reacted to dreary weather, it's going to tell approximately the same story regardless of whether the dice-roll caused it to describe the weather as "gray" or "overcast". And because "gray" and "overcast" were _already_ possibilities, the tweak from 52% -> 55% is completely lost in the noise.

But it's true that this is all based on hope. I'm confident that you could make the tweak against arbitrary prose and even a true artiste like Gruber would never be able to tell the difference. I'm less confident that there isn't some edge case somewhere that causes a tweak to be worse than 3%, especially in some narrow application where word choice _does_ matter (like law). Even then, though, laws are already written by people who are as noisy if not noisier than LLMs.

> Gruber may have an agenda here

Such as?

You're assuming the training data is a true representation of language usage, which it isn't. In the "gray" or "overcast" case, a single weather website might already skew the count of these words.

> But I think the fundamental principle is that this approach messes with the distribution in ways that deviate from the trained model.

This. I want the model I'm paying for to be "pure". I don't Anthropic or anyone else messing around with it, especially not for idiotic reasons like facillitating AI stigmatization. The "safety" nonsense is obnoxious enough.

They should train the best possible model and let the weights speak for themselves, not degrade it into some perverted form to appease people who hate AI anyway.

What a bunch of entitled whining. How is the system to know that it's just a private conversation that won't be used in some fraudulent way? Abuse is currently rampant, yes please let's find a way to mark LLM output. The thing I'm worried about is giving the providers the power to claim provenance. Even ignoring the privacy issues, the operational hassle of having to check N providers makes these approaches at best limited. I want to see research into providing a shared public or ideally self-hostable oracle that uses some standardized method for watermark detection. Similar to asymmetric crypto where users can't reasonably find out the secret part but can do something useful with it nonetheless.

This is not meant to be snarky, But almost any writing done by Claude is a perversion of writing.

I honestly can't stand the way Claude writes. This watermark change just makes it scarier.

I moved to Sol for my writing and it is so so much better. But it makes more mistakes. I think they have different ideas of product but it seems OpenAI is going to follow Anthropic’s lead over the next year. I think I am going to put more effort into my writing skills to remove myself from this awful situation

Sorry, what's scary about it exactly?

LLMs are already perversions of writing, so what else is new. Oh no, the over-long circumlocution generated by three autocorrects in a trenchcoat might be slightly longer because of this and maybe people will start noticing the subtle rhythms of vaguely peculiar word choices as yet another cue that you are wasting their time with machine-generated wordslop, what a terrible fate. Your long rambling walls of machine-waffling might be 37.05% longer than they need to be instead of the mere 36.58% longer they are now.

> But only Anthropic will be able to determine if text was seemingly generated by Claude, and Anthropic will only be able to detect the watermarks that are applied by Claude. Claude can’t detect the hidden watermark signals generated by, say, Gemini, and Gemini can’t detect the hidden watermark signals created by Claude, because each implementation is predicated on secret keys held only by the LLM provider

Well, akshwally...

> Interoperability. Providers must implement an interoperability solution for watermark detection such as a standardized API access method, a publicly readable signpost mechanism embedded in content, or participation in a consortium detection solution by February 2, 2027

it serves to show just how little regard the people behind these generated-text fingerprinting schemes have for the actual craft of writing.

LLMs have never been the place I've thought to expect any commitment to the craft of writing, to be fair.

> I want any LLM I use to choose the very best, most precise words at every single decision point.

Oh! If you want that, you should run your own model and set the generation temperature to 0 :) Because that's not what any commercial LLM is doing. Never has been. This is just making up a universe that doesn't exist so you can get mad about no longer being in the universe that doesn't exist.

The masking technique of using a subset of the statistical distribution for each next token isn't going to be meaningfully distinguishable from a natural language perspective. I honestly think its a very elegant way to implement watermarking. I've got no real opinions on how effective it will be to people actively trying to defeat it, but I suspect that the people who are trying to pretend that LLM text was something they wrote themselves are probably too lazy to put in the work to try and defeat it anyway.

It seems fine. I use an LLM to argue with me prior to posting blog posts so that I don't post obvious incorrectness, but the UX element to it is that it constructs notes about various sections of the text and we talk about those. There's no way for the generated text to enter the blog unless I copy-paste it and I'm not going to do that because the entire point is for me to write it.

At the point that you're generating entire volumes of text from Claude you're not really trying to be a sophisticated writer. I don't see how it's going to hurt for it to choose random related words.

This seems like a non-issue, or maybe I have the wrong expectations about writing. You write a text, ask Claude to proof-read it, but then you wholesale just copy Claudes output and use that as the final text? Wouldn't you review the changes it suggests and only take those you agree with, there by completely bypassing the watermarking?

Alternatively, you ask Claude to write the whole thing and proof read it yourself. In that case I'd like to know how much you'd need to change to break the watermarking, i.e. how much of a text would you need to change for it to be considered your work and not that of Claude?

> I chose to depend on a private company to express my own thoughts and now I'm mad that I'm not in control of the output

Who could have seen this coming???

LLM output, as the author acknowledges here, is already non-deterministic. Next token probabilities are set, and tokens are chosen pseudo-randomly. As I understand it, this watermark is just going to be a matter of using a known seed and algorithm to make those pseudo-random choices, such that a signature can be detected. The important thing is, it's not replacing intentional choices with random ones, it's just generating pseudo-random results differently. Quality shouldn't be affected.

That cannot be true. The quality of an LLM's output is the quality of the probability calculations for the next token. Anything that degrades the relationship between the system's best assessment of the appropriate probability and the actual probability used is a degradation of the quality of that probability and therefore of the output.

If this didn't have a detectable effect on the quality of the token probability calculation, the watermark wouldn't be detectable. It may be a small degradation in the quality of the output relative to the neds of many users in many situations, but it's not zero. It's literally sometimes choosing different words that it otherwise would specifically for watermarking purposes.

Gruber has a ridiculous knee-jerk response to anything the EU does, so hardly a surprise he didn't come to the table with a sober facts-based response.

There are many reasons to hate this watermarking but affecting the output quality isn’t one of them. The central argument he’s making is wrong. Switching out one RNG for another doesn’t make the results worse.

> The provider must mandate in their terms-of-service that users not remove the watermarking.

So, you don't own the generated text, and can't use it freely then. What if I copy paste a section, or rewrite a section of text to my liking? What if I rewrite some lines of code that contains the mark?

Security theater, and vague enough to be used as a weapon against who the government wishes.

I hope it's left off for non-EU customers.

You know you can just ignore EU laws outside of the EU

Claude's writing was already easy to recognize. The fact that Anthropic complied without complaint makes me wonder if they already watermark their outputs and used the opportunity to create goodwill. Presumably they want to avoid training their new model on text generated by the previous model, so they have reasons to be able to recognize AI-generated text.

> I want any LLM I use to choose the very best, most precise words at every single decision point.

Try running an llm like qwen 3.8 27B in Q8 locally with an intentionally very low temperature setting, it will write like a caveman crossed with a robot. You may find that an extremely literal output does not look pleasant to read for humans.

That is not what that means. Generally, precise word choice requires more than autocomplete. Larger models simulate this with hidden layers.

I commented it last time the post about Claude watermarking went viral and I'm going to say the same thing again:

"I've been working in the media and model IP space for quite many years. What this article misses a bit is the threat model for watermarking in general. Watermarking and fingerprinting have inherently weak security guarantees -- they rely a lot on security through obscurity, weak assumed adversaries to deliver. There are clear trade offs between true positives, false positives and maintaining the quality of the media. It's true for audio-visual media, models and their outputs alike. As much as I like to take shots at poor technical choices by corps and govs, this one is unjustified. Sure, inserting glyphs is bad but biased sampling is as good as it gets in 2026."

Since the announcement, there have been many people who don't seem to fully understand what a security guarantee is, what trade offs it might involve, or how popular the type of technological solution is in general (media watermarking is ubiquitous).

And naturally, there are challenges with how you will make sense of the score in your org, e.g. you wrote an email, and it's flagged as LLM-generated because you copied two generated/edited paragraphs.

Yeah, the article might disagree with watermarking as a matter of principle, comparing it to censorship. But the methodological arguments that I have read so far have been thin in these articles.

I often agree with John Gruber, but I think he’s lost the plot with this one.

The thing I don’t understand is why he seems to care so damned much about this subject--enough to write over 4,500 words on it!

John writes for a living. That’s his profession. He’s been writing for over 25 years now. When you’re that good at writing, and you care this much about your writing, you don’t allow an LLM to take over your job. I just can’t imagine that he’s in the market for LLMs and that literary excellence is his number one selection criterion.

So why is he so livid about it? It’s like being angry that wine is going to start coming in smaller bottles even though you don’t drink wine.

Even if he’s angry on behalf of other people, I don’t get it either. In my view, having LLMs write publishable content on your behalf is not a socially-acceptable use case, nor a professionally-acceptable one in most professions, even though people are abusing it for this purpose anyway. And besides, the models aren’t even all that good at it today. If you agree with that, then you certainly should not care if it’s using different phrasing than you otherwise might prefer if the meaning is similar enough.

I can't help but wonder if perhaps his hatred of EU technology regulation (which, admittedly, is mostly pretty dumb and is mainly just making life worse for users) is getting the better of him.

This guarantees he can never use it for the one purpose he might care about though

There is no coherent position in which the watermarking is a perversion of writing but AI writing as a whole is not a worse one.

> My error was believing Anthropic that their system wouldn’t adulterate and corrupt the semantics of the text their models generate.

Has that ever been the case? Are they not actively tweaking their models, their fine tuning, the system prompts, the tool definitions and implementations, the guard rails, tool calls, instant responses. There are hundreds of knobs that they can change daily, or between each prompt, or even half way through a generation.

Author read the posts but didn't understand them.

> At each decision point, they’re a little more likely to pick a word from the green list than the red list.

Wrong. There is no global red and green list. It's dependent on context and balances out on average. It won't change the result when one token is predicted overwhelmingly likely.

The fact that Gruber points to a "must-read" article about how the watermarking works, which, in turn, was very obviously entirely LLM-generated, says a lot about his lack of experience reading LLM output.

If Gruber can't tell a fully AI-generated article from a human-written one, perhaps he shouldn't care so much.

NB: I was told yesterday it's apparently a meme to call out Claude-generated output, but here I am, as I believe it's quite relevant to the topic at hand.

Gruber really doesn't like any EU regulation

Watermarks are garbage because they may embed account id, IP address and deanonimize you. That's why we should be using open-weights LLM whenever possible.

I don’t disagree about open weights (though the enabling aspect there is actually open source inference, right?)

But it feels to me like you would need a hell of a lot of text to bury even a simple account ID. The nudges they are talking about are of the order of a handful of bits over several hundred words, I think?

This is the first post I've seen mention it. How traceable are the embedded codes?

Watermarking will be one more nail in the coffin of proprietary models if the world is so fortunate.

Reminds me of printer tracking dots.

https://en.wikipedia.org/wiki/Printer_tracking_dots

And yet we still use printers and 90% of our color documents have the tracking dots.

The idea that language models can write anything remotely useful yet is - mostly - a fallacy.

It's a good idea for many human endeavors to be able to identify AI writing. Communication, after all, is our main way of building the social fabric.

However - and crucially - good writing is still beyond the frontier of any model I've seen so far.

Watermarks for the things that truly matter may not be important at all.

Finally, as X commentators have shown, simply removing punctuation or changing a word here or adding an adverb there manually will screw up the whole process enormously.

The best will be the clever folks who retroactively apply the model distribution to fraud or other crimes to try to implicate the companies via watermark.

Gotta feel for their product, policy and legal team.

"The difference between the almost right word and the right word is really a large matter. ’tis the difference between the lightning bug and the lightning." - Mark Twain

"Just flip a coin to pick a random synonym. Who cares?" - AI Labs

Sorry, this article's argument just doesn't hold water. Yes, we want Claude to write "the best text" and having its word choice even very slightly varied could arguably be construed as "not the best." But "best" is highly subjective, always has been. Claude has never, and will never, write what _you_ consider the best version of a piece of text. It has many choices, influenced by all kinds of random, context-dependent weights and environmental settings. Slightly tweaking weights to prefer certain phrasings might even tilt it toward your idea of "best."

Lots of faux outrage, rambling and hyperbole here from Gruber.

“Absurdly and insultingly”? Come on…

Are there some narrow cases (like in outputting the input almost verbatim) where the probability for every best token is always much higher than second best, and in those cases would there be no watermark?

The issue here isn't (just) adulteration, it's that watermarking in general is unworkable.

If all the providers use watermarking systems with different shifting logit weightings, and the keys are secret, you have to check every provider to see if it produced a given text.

Which is clearly ridiculous.

And if all providers collaborate and use the same weightings, or if the weightings are constant and not rotated cryptographically, a generic watermark remover becomes trivial.

That's not even getting into the legal complexities of businesses running open source models without watermarking locally.

I dont see how there would be remotely enough entropy in most model outputs for this to be close to feasible with any kind of accuracy.

Either they false positve on pretty much everything ever written, or the chances of catching a true positive is so low as to be useless.

Basically Cinavia for text, and that often falls over and is easy to remove even when there is megabytes of data streaming over a long period of time rather than 2 or 3 bits per wall of text, let alone what most people use claude for, when there is a strict dictionary and other tight output constraints.

This is moronic. This is like being mad that the slot machine you think is lucky is occupied.

I think we will see a hidden motivation behind this as ultimately so the output can have an author, the author can be attributed and finally the output will be copyrighted and so the LLM has more value.

Everyone who invests in AI companies wants to see the value of their investment increase.

I'd give it about 3-5 years until an AI company claims copyright over code their LLM produces. This is a crucial step in that path.

As someone who doesn't utilize LLMs for writing production code I'm looking forward to starting a consultancy and reaping the rewards.

I think you're right that it's actually to do with attribution (i.e. They're not just watermarking your output as claude generated, but watermarking it as claude generated _by claude user id 73684_). I think it's more to do with the growing militarization of the internet. Just another brick in the wall of enter your phone number to create an account, send your id to prove your age, smile for the flock cameras, etc. Allowing the plebs to have privacy and anonymity is not allowed anymore.

Watermarking seems feasible for creative tasks (that admit many valid results).

But if I craft a prompt that doesn't leave space for creativity, how can they include a watermark? e.g. "Rewrite the following text, replacing 'foo' with 'bar'."

I'm curious to see where they draw the line, and whether the watermarking really affects the (perceived) quality of results.

Although that feels like an overly simplistic example to the point of not being not being a helpful example, I agree that the amount of tokens to encode the watermark is so low in text, that it wouldn't take much to erase or distort it.

They can't include a watermark in that case, that's not the relevant use case.

The main reason we don't see much quality degradation in LLM writing output is because they're already poor writers. This is the load bearing reason.

I was bulding a small interpreter and writing an article in ~markdown yesterday with Fable. And while it codes like a pro, it writes like a sixth grader.

Let's see how these watermarking stats hold up if/when llms start writing well.

Some here are arguing that mechanisms used by LLM providers already derail the goal of "the very best, most precise words at every single decision point", therefore the author is misguided.

The author has expressed a preference. Assume that there is a sequence of tokens, such that it is considered the absolute best by the author. This particular method of watermarking makes it less likely to generate that sequence, by definition.

I feel their argument would have been clearer and stronger if they had spent more time exploring the alternatives, and whether these alternatives would be just as effective. It is trivially easy to remove invisible tokens.

Like it or not, there is a public good to being able to identify AI generated content, and a small degredation in quality is tolerable in my opinion.

I don't think anybody has to worry about this issue though. Manual writing, coding, and proof reading continues to be an option. Where AI output is nothing to be ashamed of, the tools are available. For everyone else, there will be LLM providers that ignore EU law.

If the author has preferences on their "own writing" that conflict with Anthropic's, then they should actually write it themselves rather than paying Anthropic to do it. Private companies don't owe you anything, even less so when they're beholden to laws in foreign jurisdictions.

>Assume that there is a sequence of tokens, such that it is considered the absolute best by the author

You can't assume that because if that was the case he'd already know what sentence to write, because that's what that means.

The notion of a best sentence requires a final cause, an end to write to. By their very nature that's not how LLMs work, so you can't 'degrade' them on that front. They can't lose a property they didn't have.

If we wish to use “the very best, most precise words at every single decision point” then I will note that “writing” is not the best word for what LLMs are doing. A more precise synonym might be “generating”, in which case this essay becomes “Watermarking is a perversion of text generation” - which is true, albeit somewhat trivial.

This scheme has a fatal flaw, the same secret key is used for watermarking and detection. This means you need to trust that Anthropic:

* Shows the real result from their detector instead of manipulating them, you have no way to verify * Has good enough security to prevent a key leak * Rotates keys to reduce the impact of a leak (once a key is leaked anyone can rewrite text to look more/less claude generated and it becomes useless) * Will not secretly give watermark-less access to governments or high profile corporate users * Will not use multiple secret keys to track individual users. This one might be less realistic because embedding ~32 bits of signal would probably affect quality a lot more than 1 bit.

And don't forget that the detection API will work as an oracle. If it detects your content you can send it to a different model and try again until it comes back clean.

>in areas where there is an arbitrary choice between particular words or terms within the code, the watermark can be used, such as comments within code.

I wonder if this is why Opus 5 keeps writing excessively long comments, even though I keep instructing it not to (both in chat, CLAUDE.md, and in its memories)

Opus 5 does not have the watermark yet. Only models released from now on.

A question not addressed here is whether there exists any solution to the EU requirement that doesn't suck.

If the same red/green algorithm described in the article is applied to generated code, I cannot imagine how that does not degrade code quality (probabilistically, not at every point).

I agree with the substance of this article, and disagree with the author's reaction to it.

The part I agree with:

It is true that watermarking can be done by "just" swapping one PRNG for another, and it is even true that with today's LLMs, it is possible that this will not degrade the output. But it has a cost, and as things improve, that cost will matter. You are intentionally reducing the degrees of freedom in the output, and using those bits of entropy for a purpose that does not improve the quality. If you maximize your tradeoff of bits for quality, those extra bits lower the ceiling of what's possible. It's a very simple information theoretic argument, and the only plausible argument against it (that we're using those bits so inefficiently now that the new PRNG is no worse than the old) only holds in the short term.

I also agree that having TOS that forbid removing the watermarking is deeply, deeply problematic. Hell, the whole essay is well-written and persuasive, and gives good reasons why this is a poor approach.

What I disagree with, and the reason for this comment, is the entitlement.

> The idea that anything other than my needs should factor into the generation of text for me is patently offensive.

This attitude is what is patently offensive for me. This is the argument that the world is beholden to my interests. It says that worrying about negative externalities is immoral. It's another form of certain people being above the law, shareholder profit maximization über alles, might makes right, we have to do it or someone else will, "we just help people connect", {code,a gun,roofie} is just a tool.

So I agree that the watermarking has a cost. But you can't leave out that it is an attempt to reduce negative externalities of AI. Whether it's a realistic or worthwhile attempt is a whole other debate (and Gruber does a good job of debating just that in the latter part of the essay), but saying that the user's needs are the only thing that should ever be considered is reprehensible.

It's no more a perversion of writing than the act of using an LLM to write in the first place.

I've been seeing a lot of the same questions about watermarking over the last week, so I made this playground that lets you try out 3 different watermarking schemes (including a version of SynthID-Text) on your own text: https://watermark.keito.me/ to understand it experientially myself. I found it illustrative to try different examples like code, text rewriting, etc. to see how it affected the tokens. Playing around with the detector is interesting too to see how much of the watermark can remain in edited text. I hope this is helpful for others too.

I'm doing a fiction project using AI to write the framework, then fixing it. AI writes terrible fiction. Every single sentence in the project is approved and/or changed by me. And I like em dashes for this project. I've been using em dashes since TeX came out.

The question is: does this make my project "AI" or does it make it mine?

People use professional editors all the time. But they agree to give up any copyright in their edits. If I approve a change made by an editor, it becomes mine. But there is this idea that approving an AI sentence still make it AI.

I think writing is the killer use case for local LLMs.

We've had so many advancements in LLM samplers for improved text generation (off the top of my head: min-P, adaptive-P, XTC, DRY, p-less, Top-H, Top-n-Sigma, and so many more) but hosted LLM APIs only provide three basic knobs: temperature, top-k and top-p which are old as the mountains in LLM years at this point.

One thing that doesn't help the local LLM case is that all the popular VC backed local LLM wrappers also only support the same three ancient knobs because I suppose they're more preoccupied with their next fundraise than with keeping up with the advances in tech.

This post makes no sense. You can either care about writing and write things yourself, or you can not care and farm it out to a model. There is no third option where you care about writing and farm it out to a model.

I guess I understand the complaint, but LLMs are already crap at writing, IMNSHO. And, yes, maybe this will make them marginally more crap, but in my mind we're talking the difference between a 30% grade and a 29%.

Doc Searls, the long time Editor-in-Chief of the Linux Journal, brings an editors viewpoint to this, and mixes in a number of other voices.[1]

Many writers use AI to edit their own words, and this watermarking poisons the well for that use.

I think the backlash from this could be the seed that undoes their attempted 2 Trillion IPO this fall.

[1] https://doc.searls.com/2026/08/17/you-can-hear-the-squeak-of...

As the algorithm tries to keep the stenography in place this will mean if you specifically ask for a different phrasing of one paragraph, other parts of the document will need to change to keep the supposedly impossible to detect AI watermark in place? Won't people also just quickly do analysis on this to figure it out and remove the watermark - it's hard to do this for individual messages but when you can create an infinite number of messaging to train on, I'd think analysis of how the signal works will be quite trivial.

He's complaining that a coin-flipping synthetic text extruder is using an unfair coin. The text generated by an LLM is already adulterated. His objections are so much titling at windmills.

This was nice but without hard evidence. I'll bet if nobody were to have said anything, nobody would nave noticed. That doesn't make it right, but it might be less intelligible and intrusive than the claims here.

Also this:

"> I want any LLM I use to choose the very best, most precise words at every single decision point."

I don't think the author quite appreciates the level of randomness here.

This is more subtle then Claude changing prose.

Again - I suggest that the author would have to run a test on themselves to determine if they can actually find a difference.

Using LLMs for prose that matters is already a perversion of writing.

It's good to be the King.

And what I mean by that is that companies that are at the top tend to make anti customer decisions because they have lost the concept that pleasing customers matters as priority one.

> Someone with the secret key can determine which list a word will be on at each token generation point (which is how the watermarking is detected); those without the secret key cannot.

How is this supposed to work in an actual lawsuit? Will Anthropic offer some sort of tool / (paid?) webservice to check for watermarks using that "secret key", and a judge is supposed to just believe whatever that tool's verdict is? And then it takes the EU another 20 years to understand what a silly idea this was?

I have no doubt they can benchmax their way into believing the differences caused by watermarking are imperceptible. But I'm skeptical there won't be a drop in quality that puts them at a disadvantage relative to competitors that don't do this. This adds a new constraint changing predicting the next token to predicting the next token that carries the watermark. It's hard to see how this can avoid making the watermarked output <= the desired output in quality.

I just don't like the idea of an AI company saying that they've added a secret signature that isn't verifiable by any third party to all responses. And we're supposed to both take them at their word, and feed them all the content we want to check so they can continue gobbling up a bunch of fresh works. What is to stop them from saying "Oh yeah, that is ours. We signed it. Trust us."

The obvious conflicts here are wild.

His argument for needing it to write every word at its best is weak. The black box within can change quality at every moment based on many factors they he hasn’t known about, say system prompt, or other harness adjustments. Models get better every 2 months, and they write better, but he is comparing to what?

The real argument should be watermarking itself. I don’t want my shit water marked if I ask you to just rephrase a certain part.

While I like that LLMs won't be able to produce the entire internet anymore, I am worried that the real reason for this move is for Anthropic to claim everything is theirs even though they STOLE humanity's collective knowledge including billions in private property worth of knowledge (or maybe even trillions), and all they do is regurgitate it, but now with a watermark on top as if it was theirs.

Are we now going to live in a world in which people bitch and moan about large private corporations' LLM text generation service and whether it's good or bad etc.? As though they're supposed to be benevolent and serve the public interest? They're not and they don't. Also, write your own damn text.

> "My error was believing Anthropic"

The error is rearranging part of one's life around Anthropic.

They chose the wrong word "watermarking." Perhaps they find the statistics _after_ a certain amount of text is generated at scale, so that it doesn't affect the fidelity or integrity of the LLMs output.

There is evidence this exists already, and it's why "I have to be honest..." and "This is the right lens, ..." keep popping up.

Probably would be cheaper too. Maybe I am missing something?

I was using Claude yesterday and the "advice" it was giving me quickly became confused and irrelevant to the prompt, even though there was not much text in the context window. Speculation: since Claude re-reads the entire chat at every turn, the "minimal" text revisions required by watermarking quickly compound such that even Claude can't follow the discussion.

I really don't think Anthropic has the leverage to pull this kind of thing off in the face of competition. OpenAI doesn't do it (yet), Grok doesn't do it, neither does Deepseek. I'm sure the latter two have plans to intentionally never do it.

Who is even asking for this? Sounds like something some obsessive internal employees would push on the world.

> The idea that anything other than my needs should factor into the generation of text for me is patently offensive.

And this attitude is incompatible with any models produced by frontier labs. Your needs will always be subordinate to and in service of the needs of the corporation that produced the model. And we haven't even gotten to ads yet.

Heck. The entire process itself of LLM text generation is a perversion of writing.-

Further heck: It can be said it ain't even writing.-

Best writer I’ve ever seen not understand writing. Proof positive that you needn’t understand something to produce lots of it!

There will be services online that copy/paste (or you provide) the text from ai, they OCR it to get rid of watermarking, then feed it back to you for a fee.

The premium upgrade will be "obfusicators" that further modify the text sporadically to make it look more like a human wrote it.

Students for one, will gladly pay.

> the only acceptable answer for why an LLM should choose bananas instead of pineapple (or coconut, or guava, or papaya...) is that it has determined that it’s the best fit for the intended meaning, tone, and sentiment of the text.

It already fails. It randomly picks between close candidates. To help fool people into believing in intelligence claim, I guess.

Get fucked? Really? As if the quality of machine-generated prose were somehow sacred?

Is Gruber only now waking up to the idea that LLM companies do not give a shit about the quality of the writing they generate? That they're disdainful of the entire concept of writing as a profession? What rock has he been under?

If you care one iota for the quality and craft of your writing, you would already recognize that any degree of AI "processing" obliterates stylistic choices. You're left with readable text, but it's fluffy, meandering, and has a cadence to the writing that screams to the reader "every second you spent on this was wasted."

> I want any LLM I use to choose the very best, most precise words at every single decision point.

No, you don't. If you wanted that, you would set the temperature parameter to 0. But that would lead to less desirable results, not better. LLMs do not set the temperature to 0; they typically set it 0.4-0.7.

Humans have been inserting benign noise into their writing without affecting the signal for thousands of years. They called it "style".

Apparently superfluous descriptions, unnecessary words, and paragraph footnotes are all fine, but gumbel softmax (or whatever's going on here) isn't.

"possibly build tools to take a chunk of writing and try to remove your fingerprint from it, i.e, protect anonymity,"

The standard procedure to do this, is to chain translations to other languages and back. The message remains, but the wording will pick up some noise. --Dec 30, 2008.

I predict we will soon see more AI providers implement watermarking, because it allows them to filter out AI generated data from their training sets. That is probably the real reason why they implement it. Gruber just doesn't get it.

As a university professor, back in the early days of this when students were just copy / pasting output directly I was really hoping the model builders would implement steganographic fuzzy hashes.

Not that it's the ideal solution. But it would be really neat.

"The more words in the text, the more accurate the analysis will be that the text was generated by a specific AI model or not."

And this is why the latest Claude models blather so much more. All for the sake of this "watermark."

LLM inference already isn't deterministic, the watermarking technique only limits the space of possible random seeds. There is no reason to believe that this subset of seeds somehow produces lower quality output.

Ai is a perversion of writing. A useful one, but still.

I don’t see how this makes it worse.

> It’s unacceptable for a tool to sacrifice an iota of clarity, coherence, meaning, quality, etc. for the purpose of embedding hidden clues within the text to suggest its provenance.

Yeah, that about sums it up!

The watermark is based on stylometry - and we all know Claude has a style. But it doesn’t have to - everyone knows caveman - so not sure there is enough room in all cases for it to work.

Fundamental misunderstanding of what AI is and what it does if this watermark is preversion of what AI is already doing.

Not sure about the strength of that particular argument, but can't say I have any faith in this being used to benefit end consumers.

Somehow they'll find a way to use this for regulatory capture

What a strange take. LLMs themselves are a perversion of writing. I couldn't care less about the implementation details of the PRNG they use for next-token sampling (well, as long as they're not stuffing a user ID in there).

gruber is really out of his element with ai commentary, I fully support the general skepticism but he's seemingly arguing against something he doesn't quite grasp

What's gonna be a real trip, is when you can tell which LLM produced it by the subtle pattern recognition you'll have developed to catch the watermarks

Is this 'best word' with us in the room right now?

https://en.wikipedia.org/wiki/Oulipo

So the watermark can be removed by rearranging words and choice of words. This seems trivial to bypass with a local model. If I understand this correctly.

Why does everyone love AI and is impressed by AI quality but when the time comes to admitting that they use the magical AI, no one wants the watermark?

How Claude's text watermarking works

https://news.ycombinator.com/item?id=49303350

Gruber was a good voice in the industry but this article misses the mark in a lot of ways.

A company the size of Anthropic would not voluntarily jeopardize their massive valuation if they didn’t feel the resulting output would maintain a similar level of quality as before. Is there a similar worry that their system prompt, which is injected at the start of every conversation also influences token generation in an artificial way?

If regulation will ruin Claude as a product, market forces will fill the void. There are also a ton of open weight models to choose from. It’s going to be okay.

I keep seeing an irritating misconception in this space, which is that the alternatives chosen by these algorithms are supposed to mean the same things as what they're displacing. That's not true, and not how LLM generation works. Complaints that two different choices don't mean the same thing miss the entire point.

Great question buried at the bottom:

> Also, what happens if another major global market makes it unlawful for AI to secretly watermark generated text?

People are very upset, especially in the arts, that Anthropic is changing the text to watermark it, but isn't that missing the point a little bit? They're not changing _your_ text whose every word you've carefully chosen for the exact effect, they're changing text that they're generating, i.e. text you've already chosen to give up control over. LLMs can't understand emotional nuance anyway.

The phrasing of the announcement implying that phrasing and diction don't change the meaning of text is insultingly dismissive of the whole field of literature, and I can see why people might take it as an afront, but the actual technology shouldn't have a negative impact as far as I can see. It seems to me that this one is more of a PR problem than something with real-world impact.

any watermarking ai researchers who can explain this?

what if the llm should

- repeat something verbatim (important in a compaction prompt)

- there is just one correct order of tokens for a somewhat long chain (a certain sequence of control signals)

- provide a diff of 2 inputs

without punctuation or whitespace wiggle room?

how does the drifting work?

does it postpone the drifting and drift stronger later?

what if max_tokens is set to a low number?

in what way does this not affect output quality?

Doesn't this require the whole message history including the system prompt for them to check for the watermark?

Claude is already a perversion of writing.

You would think that if the EU is requiring this, then why not just implement this for the EU users.

I'd encourage reading this paper, and literature on scaling laws in autoregressive models: https://arxiv.org/abs/2303.11156

Total variation distance has been measured to decrease as you scale a model, and that is the primary mechanism "watermarking" as discussed in the Anthropic announcement relies on. It becomes more difficult to reliably detect text as a fixed sample count without tweaking the distribution further. Either way, it's a minor problem that will be addressed over time, compared to the issue of who can detect this without guessing or developing their own sets: providers not releasing a way to detect any such watermarks without going through them makes this entire approach hostile to the public. The EU regulation on this subject is interesting, although again most certainly not the primary driver for these practices:

"1.1.2: Signatories will ensure that AI-generated or manipulated content is marked with an imperceptible watermark, with the exception of very short text. For free-form text longer than 200 tokens, watermarking still needs to be applied, even though it may have lower reliability compared to that of watermarking very long text"

A proper, effective and useful law would have required providers to regularly release datasets to run your own verification on any text released within a fixed interval of time, presumably once out of rotation. Instead, it only talks about exposing an user interface going through their own services:

"Signatories will ensure access to their detection solution through a user interface appropriate for the audience of end-users that may eventually be exposed to the content generated or manipulated by their AI system. [...] Any restriction to the access will be limited in time until more reliable and robust detection mechanisms have emerged and have been adopted as the state of the art for detection mechanisms for the watermarking of free-form text evolves."

Most interestingly, in line with the EU's mass-surveillance program, an alternative solution to watermarking where it may not be sufficient is also suggested, although only optional for now:

"Where appropriate and taking into account potential trade-offs related to privacy and security, as well as scalability challenges and costs, Signatories may implement as an optional supplementary measure fingerprinting or logging solutions for AI-generated or manipulated content which allow for checking whether content has been generated or manipulated by their AI system. For example, direct logging may be appropriate for text content, whereas fingerprinting approaches may be preferable for audio and visual content."

Plagiators are having a fit these days

Fix it for you:

Generative AI is a perversion of writing

I assume this means Gruber has fully embraced generating his blog, but is too embarrassed to admit it?

There is no very best token to choose at each decision point. It is context dependent and subjective.

I don’t understand how this works for anything but prose. Is that the point? In any code or structured output, there just isn’t the flexibility, and depending on how the user requests the output be constrained there is even less (“answer only True or False”). So is it just chat responses? If I ask the API to tell me a story about Alice and Bob then it watermarks it, but when I ask it some implausibly constrained thing like write a story about Alice and Bob with each word starting in rotation with the letters alicebob, does it try to do so and hope there are roughly équiprobable tokens regularly?

Text watermarking is another EU rule made without real world input. The Union is stuck on major economic crises (electricity prices for instance) because nobody can agree on anything. However, the bureaucracy forces tech into a privacy nightmare. Brussels cannot bring together its own members but it loves pretending it can govern the internet.

I will be happy to move off Anthropic given the chance. They are burning all of their good will.

Then then don’t use Claude ? What’s wrong with all these people getting vendor locked in.

I wonder if this watermarking system to lead to an increase in tortured phrases, believed to be caused by plagiarism evasion tools that change random words to applicable synonyms.

https://arxiv.org/abs/2107.06751

I wonder how much they tested on non-English languages with fewer synonyms.

What a stupid take. Generating text with an LLM is already a ‘perversion’ of writing. Tweaking the last random-choice step doesn’t meaningfully change that at all.

I almost never post a comment here, but everything about the author's position is offensive and self entitled. I am so enraged that I can't even beging to formulate a response without resorting to very bad language. It's sad, because until now I respected the author. But clearly, and sadly, he has been afflicted with AI brain rot, and is likely in some stage of withdrawal. I wish him a speedy and safe recovery.

Just copy Claude’s output and shove it into Gemini and ask to rephrase.

It’s super ironic to see this many bots on this thread. Sorry dang.

Not telling someone you used AI is a perversion of writing. Also agree that an AI proofreader should not claim authorship, but in most other cases, the AI is not reading your mind, it's only watermarking its own usage, and we kind of need more of that.

you can remove AI company invisible text watermarks at www.demarkify.com - and also perform other tonal text changes like removing AI lexical tells

Reminder: your favorite distilled model does not treat you, the customer, as an adversary and mess with your output.... May the free market win.

I know (and understand why) a lot of people cheer the EU’s increasingly vast regulatory environment as being “pro consumer” but I’m really tired of said regulations being inflicted on the rest of the world. If this is what Europeans want for themselves that’s fine. But I no more want their regulations to be the de facto world’s any more than I want China’s.

The first thing that came to my mind was "security theater." Making people think that AI is detectable could have the same effect as actually making it detectable.

Mind that even in their first example, "The results of the study were quite (important | significant | substantial | notable)", the meaning is by no means interchangeable.

"Important" refers to impact, "significant" to the statistical qualities of the underlying hypothesis, "substantial" to the work involved, and "notable" is a referential judgement by the speaker. The implied normalization of words and their respective meaning also marks one of the mechanisms how "slop" is typically creeping into the productions of "broad verbose interchange replicas" (it's all interchangeable, and a choice isn't really that, a choice, isn't it?).

The objection seems to be that Claude will always write worse prose than a human writer, even if the writing Claude generates is understandable.

Yeah, John. We're all OK with that.

Wait are we supposed to be mad because clankers are displacing human creative workers, or mad because clankers don't do their level best when producing creative works because they are forced to watermark text? Or is it that they use all the water (I know they don't but are we supposed to be mad about it still)?

I can't keep up with the current Chinese psycop. There should be some kind of status page like whywewantamericatofailataitoday.ai so we can keep up with it.

A lot of that rant is nonsense. Is Gruber also outraged that a RNG is already involved in everything LLM produce with a non-zero temperature? Surely it already leads to widespread use of “non-optimal words”. Simply the idea that there is a single optimal choice, down to every single word, to convey a meaning and anything straying from that is adulteration is laughable. It’s very difficult to take seriously an argument based on this kind of foundation.

He had a very similar rant a couple of days ago when he somehow thought that they would use invisible characters. It’s just as useless.

Posting for visibility a reminder that this type of watermarking is comically easy to beat. See Scott Aaronson's 2023 research in which he coined the term "pineapple attack": one must simply prompt the model to add the word "pineapple" after every other word and then do a search + replace to remove the word, to obliterate the watermark altogether.

https://www.youtube.com/live/2Kx9jbSMZqA?si=0QgCPBX2_KPZ0QTU...

I think it's pretty dishonest of Anthropic to frame their watermark as EU regulation compliance. The EU regulation, from my understanding, requires AI content to be labeled for human viewers. In the meanwhile the Anthropic new release on the watermark says this.

> The difference between watermarked and un-watermarked text will not be distinguishable to readers

https://www.anthropic.com/news/claude-text-watermark

Which is to say, it does not actually meet the EU AI act requirements which require transparency to humans. Not to mention that if the detection requires access to the base models, it makes anthropic the only entity who gets the say on if a piece of text comes out of Claude. Anthropic is both the player and the referee here.

If there is one takeaway you should have from this fiasco it is that you should be wary of using tools that doesn't serve your needs and your needs only.

Watermarks are context poisoning.

If you don’t like it don’t use it

I'll be honest, who fucking cares? Why would you use AI to write for you and then complain that people know AI wrote the code?? If you know people wouldn't like it, why even try!?

How does this work for code?

you can remove AI company watermarks at www.demarkify.com

is that why everything Claude writes lately sounds like a riddle?

I needed another reason to cancel my Claude sub. Thanks Anthropic!

This is akin to adding a giant watermark on things one would made with a free product "Made with XXX". Except you're paying $200/month for it, and there's no way to disable that watermark.

I don't disagree with EU regulations, but I strongly believe the onus should be on the content publisher, not the toolmaker. If the toolmaker watermarks whatever his tool produces, it opens a giant can of worms that cannot be closed. That means anything and everything you make with this tool is no longer fully yours, it contaminates everything and makes your work traceable. Who wants that?

I was already annoyed by the fact that Claude marked everything it did on my repos under its own account (I didn't ask for any of this), but now everything is invisibly marked, even the code. Not that I care that my writing would be watermarked, since I'd rather write my stuff myself, but code? No thanks.

Meanwhile I'm running a DeepSeek V4 Flash or Pro, or a Qwen3.8, and it writes my code without a peep. Resulting repos are clean, just the way I want them. No 'Claude' account, no watermarking, nothing. I won't be looking back after having tried these new models. Whoever makes good models that don't broadcast their maker will get my business.

This watermarking will simply push people more towards Chinese models. Keep pushing in the wrong direction Anthropic. Doing this right before an IPO is a great idea.

Gruber is a smart, thoughtful man. This is a bizarre take from him.

It exhibits an undeveloped understanding of LLMs, and a righteous view that generated prose should assimilate... which should be offensive to organic intelligence.

Issues with the proprietary nature of Anthropic's watermarking aside, we will look back on this as a 'thank god' moment in the history of LLMs.

Imagine using a random word generator and getting upset that the random words it generates are not truly artisanal random words.

Wow, never has a single article revealed the incompetency of a tech writer.

This is the yet another embarrassing idea from the EU they came up with, if they could focus less on dumb things and more on providing real support to the development of technology maybe we could have more healthy competition that will eventually lead to better overall technology in the hands of everyone instead of acting like dumb chickens and not just being passively useless but also stopping the real labs from doing the real work into doing this bs

"Anthropic's . . . Claude is a Perversion of Writing."

FITFY.

I have no sympathy for writers whining about what the AI is doing to 'their' writing. It's only your writing when you write it. There's any easy way to avoid this: don't fucking use it. Use you own brain.

... If watermarking is a perversion of writing, what does that make 'writing' with an LLM?

The author makes a lot of great points. I find it surprising that somebody who has such a nuanced appreciation for the subtleties of language would be in the crowd complaining about the watermarking policy. I expected this kind of complaints from mostly students interested in academic dishonesty, who generally don't have enough command over written language to notice the slight decrease in output quality.

Whole watermark thing is just bullshit. What if I add a watermark text and another AI as well. How many watermarks and who is the real creator. It just doesn't make sense. I ll eat my shoes if this concept is still a thing in 6 months

A) without water marking, llm will poison the open internet and poison their own source of fresh new material. B) without watermarking, it potentially exposes an infinite deluge of garbage getting to people , fostering hate, eventually leading to dis-engagement, ergo destroying their training pipeline. C) ...Sadly, them water marking the claude chats with absolute dementia levels of output text is beyond me, i seriously can't tolerate this bullshit "randomly replace words with "similar" words", bs anymore, the output that claude makes right now is outright *corrosive* to my eyes, eventually leading to their training pipeline dying if devs dis-engaging ( of the 3 i think this one is the worst )

I think they need to get their shit-together and realize this is a death warrant for the tech ( in my opinion ).

The same absolute morons who gave us cookie consent strike again.

I swear, one of those days I will get into politics just to fight those two things, and the cottage industry of batshit crazy lawyers that gave birth to those things.

Such a stupid regulation. Don’t make the rest of the world suffer because of one dumb law passed for a fractional share of users.

This also, just another precedent of anti-user, pro Authoritarian, from LLM companies.

It's because the individuals who write those laws are literally trying to shove neo-Nazi policies into EU practice. I wonder how many people would make policies like this if they and their families were publicly identified and criticized as neo-Nazi elements in society.

You think someone will write Nazi-promoting AI policy like this when society is encouraged to look at their families as examples of neo-Nazi corruption? When their wives' and kids' friends spurn them while their families engage in obvious criminal activity to harm world productivity?

Critics need to be more precise.

They just want to prevent their own slop being fed back into their AIs.

I think this would be a good guard on websites to use it as another content protection layer.

This is the obvious solution to watermarking text in a way that isn't easily removed by a dumb tool.

The output quality will likely suffer as stated in the article although this can be mitigated to an extent by only enabling it on more irrelevant filler text while leaving the more functional sections untouched.

The solution using Unicode tricks amounts to malicious compliance as only the most unsophisticated users are going to fail to remove the AI watermarks when trying to pass off AI slop as their own prose.

The real solution here is not having stupid EU–tier laws in the first place.

Great, now Claude will sound even more generic. It’s not only annoying - it’s also dumb. We are all correct to push back on this load-bearing issue

Awwww, little blogger can’t write his slop anymore without rest of the world knowing that he’s not the author?

"My writing is my work, and Anthropic's current strategy is aggressively writer-hostile."

Tl;dr the author is upset that the slop generator will generate slightly different slop, and calls this perversion of the text, ironically missing the fact that the entire technology takes existing human work and perverts it in order to give him the output that he seemingly enjoys.

Perhaps it's not actually irony, perhaps it is hypocrisy.

This isn't to say there aren't correct statements in the article, but its framed very strangely.

So Anthropic goes on the shit list with Sony Blu-ray and its cinavia watermarking.

No, machines being used to replace human writing is a perversion of writing. Some might call it worse than cannibalism[0]. If you're only noticing now because Anthropic is changing things behind your back, well... I've got some bad news for you, but the entire cloud-hosted subset of the AI space, especially Anthropic, is premised on the fact that doing things behind your back to their models is socially preferable, or worse, should be outright mandated.

While I generally hate legal mandates to stab your customers in the back, in my opinion there is no harmless way to use AI and mandatory text watermarking is a good bare minimum. The EU probably made the right call. The entire AI space - open models included - is predicated upon worker exploitation, replacement, and deskilling; we should at least be able to know how much of our media diet has Anthropic's fingerprints on it.

A lot of hay is made over the pretraining process in which copious amounts of stolen data are trained on; but parallel to this is a huge data labeling and human feedback operation staffed almost entirely by people in third-world countries with robust English as a Second Language (ESL) programs. The thing is, AI models already watermark their text, they just happen to do so with the textual watermarks of the Indians and Nigerians that the AI companies hired to do RLHF because they were cheap. That's why certain AI models love the word "delve" so damned much. It's neocolonialism, designed specifically to do the kind of replacement the anti-immigrant idiots keep screaming their heads off about[1].

Furthermore, as we've seen with Hank Green, even non-cannibalism-adjacent AI usage is a recipe for worker deskilling and AI psychosis. The other half of the RLHF pipeline is to turn a pile of compressed text into a chatbot that feeds you a steady drip of unsourced information while praising you every time you spot one of its lies and never saying no[2]. This is a recipe for addicting your customers.

Also, this might just be because this is on daringfireball.net, but I can't help but think the author has an axe to grind against the EU because the EU mandated Apple sign third-party app stores. The fact that he's balking at Anthropic not going along with gating the watermarks to just the EU seems downstream of this - "why aren't you maximally attempting to resist the EU?"

[0] https://www.youtube.com/watch?v=YCPAIg7RUq8

[1] To be clear, upwards of none of the far-right have actually clued into the fact that AI is trained by underpaid immigrants, mainly because it doesn't fit the narratives the people running the far-right want to push. There are some AI robotics companies that are even very explicit that their robots are there primarily to launder foreign labor into rich companies and make permanent labor arbitrage.

[2] Continuing on from [1], the far-right actually really loves AI specifically because it rarely says no to even stupid ideas, even if it's also a manifestation of everything they claim to hate.

Man this watermark nonsense is all over the place

Now for the human generated watermark. Timez to addd the speelling mistakes, decreaze the usegage of big words and proper gramicaly usuage. Wish I was joking.

Using AI is the only perversion here And what a self-reporting from all the AI bros!

The objection isn’t that normal sampling is somehow pure. It’s that watermarking uses token choice to carry an additional, covert signal. The quality cost may be small on average, but it is still an optimization constraint unrelated to meaning or style—and it turns ordinary prose into provenance metadata. The more serious questions are detection reliability, false positives, and what happens after human editing. https://prachub.com/

> because the nature of the watermarking algorithm requires it to sometimes increase the probability of selecting a worse word choice and decrease the probability of selecting the model’s best choice.

... and the opposite is also true, sometimes it will increase the probability of choosing the "best" word choice. So watermarking makes the LLM quality better then? /s

> My initial speculation was that maybe they’d hide invisible non-printing Unicode characters in the text.

Or just em dashes? /s

tl;dr:

> It’s unacceptable for a tool to sacrifice an iota of clarity, coherence, meaning, quality, etc. for the purpose of (watermarking)

And an example of the impact of watermarking on word choice [0]:

> The results of the study were quite [important || significant || substantial || notable]

The meaning of the sentence to changes slightly even in just this tiny example. Imagine the degradation when applied across an entire response!

[0] https://declaude.org/watermarking/

What is even the point of watermarking AI slop supposed to be? All it does is provide people with the false implication that anything which is not watermarked must not be AI-generated.

I struggle to see how this could possibly be useful unless there's some sort of psy-op going on to trick people into uncritically accepting anything lacking a watermark as not being AI-generated.

I recently found there was no website covering a historical subject, with sites begging to be visited. The information was scattered and not presented in the form people would find most useful (a map).

A couple of days later it was up with the most comprehensive review of the available info summarised and referenced ready for a human researcher to explore.

This was only possible due to AI. It would have taken me weeks to chase it down and summarise it, so it would never have happened. Let's get off our high horse about AI writing.

This (Anthropic's "watermark" stance, I mean) is so fundamentally ludicrous that I have assumed it is a (wholly insincere, but arguably pragmatic, at least from their perspective) attempt to deal with the EU and their latest misguided, ham-fisted attempt to solve a real-world problem by drenching the entire world with more regulatory slop[1].

The "watermark" can be trivially defeated, but may be enough to satisfy the letter of the law, and like many people here, I would argue that if you are letting Claude write for you, you've already accepted getting the literary equivalent of turd soup, so the harm is — or at least could be — fairly minuscule.

[1]: https://digital-strategy.ec.europa.eu/en/policies/code-pract...

(FWIW I have a more favorable view than most people seem to of the EU's efforts to at least try tackle problems like this — but predictably, the bureaucratic "solutions" they come up with don't work, but do make things objectively worse)

Respectfully, you are all missing the point.

Watermarking is bad not just because of the principled stance that your tool should not be working against your own interests (the passionate argument in TFA), but specifically because it lends credence to the idea that AI detection is a valid and possible thing to do perfectly.

As technologists of course we know "oh well yes but with some confidence interval we can detect AI token bias across a large corpus of text." To JimBob in charge of publishing your paper or reviewing your PhD submission, all he knows is "anthropic says AI detection is possible so this 30% chance your paper was written by AI means you've plagiarized." Do you really think you're winning the argument with the certified, law-approved plagiarism detection machine? No, you're not, and your career is over.

It's irresponsible to develop watermarking because it is not anywhere close to a perfect science, but it will be treated like one by people with the power to ruin your lives. Even if you've never touched AI in your life, your paper is going through the "maybe it says you cheated" box, and you better hope those dice don't come up snake eyes.

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