Putting aside the way you're saying it, your comment has a valid and common misunderstanding of LLMs.
LLMs don't just naturally output a single suggested word (or token) each iteration. Instead, they output a value (roughly, a probability) for every possible word. It seems obvious to simply pick the top (i.e. best) suggestion each time. Then your objection makes sense: watermarking would violate this.
Of course people have tried this! The problem is, in practice this makes the LLM much less "creative" than if you randomly pick one of its suggestions (weighted by the numbers it assigned them). You can artificially increase the value higher-value outputs to reduce the chances of it saying something really odd, and this parameter is called "temperature". A higher temperature allows lower-probability choices (therefore seemingly more creative but perhaps less accurate) and a lower number vice-versa. Either extreme works poorly, and picking a good number is part of optimising an LLM.
LLMs don't just naturally output a single suggested word (or token) each iteration. Instead, they output a value (roughly, a probability) for every possible word. It seems obvious to simply pick the top (i.e. best) suggestion each time. Then your objection makes sense: watermarking would violate this.
Of course people have tried this! The problem is, in practice this makes the LLM much less "creative" than if you randomly pick one of its suggestions (weighted by the numbers it assigned them). You can artificially increase the value higher-value outputs to reduce the chances of it saying something really odd, and this parameter is called "temperature". A higher temperature allows lower-probability choices (therefore seemingly more creative but perhaps less accurate) and a lower number vice-versa. Either extreme works poorly, and picking a good number is part of optimising an LLM.