alt Hacker NewsCan someone help me understand how exactly this watermarking of text works?
Given that text is, well, text, and not some kind of binary format, I don't see how any watermarking can work unless you insert characters which are invalid under Unicode. I further don't really understand how this won't be perceivable by assistive technology (the "watermark" will just appear as either unreadable characters, or if the watermark is mixed thoroughly enough into the text, it will scramble the text to any speech synthesizer and will make it really really obvious). Thus, I don't see how this wouldn't be insanely trivial to remove. And this is before we get into things being put on the clipboard. Sure, I can press the "Copy" button at the end of each response, but what I can also do is manually select the response and copy it, or only copy partial selections, or any number of other things. How does this "watermark" (or any "watermark" technology) take into account this?
So, really, to summarize this: I see no way of this actually being technologically achievable unless we revise the very core of how computers work and encodings for textual information. So I'm very curious as to how this is actually supposed to work.
Replies
it's a statistical way. like for example maybe in your above paragraph claude maybe writes "Thus, I don't see how this wouldn't be insanely <easy>(instead of trivial) to remove" and then also says like "And this is before we <analyze> things being put on the clipboard." or maybe the i just says the word "the" in a certain pattern or frequency.
you can then consistently like figure out if it was claude that wrote the sentence. it is easy as you noted if you just get another ai to read it and then rewrite it.
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Have a look around for token biasing, or green lists. It's based on a nudge to the choice of the next token (which can always be drawn from a set of possibilities which are all probable enough).
At first I thought this approach was just the "LLM flavour" of writing, but it's way more subtle, especially as the bias is applied uniquely for each token position.