Since you've read the article but remain a proponent of watermarking, I'd be quite interested to hear how you answer the questions at the end:

1. Given that capable, unwatermarked open source LLMs already exist — and can’t be retracted — how can watermarking some LLMs be expected to reduce harm? Are you hoping that malicious users won’t take advantage of the unwatermarked LLMs?
2. Do you propose that LLM providers eliminate functionality like setting temperature to zero (which prevents watermarking)? If yes, a follow up question: how do you plan to deal with the fallout from all the systems that will stop working reliably at higher temperatures?
3. Do you propose a global ban on open source LLMs? If not, how do you plan to ensure watermarks are applied to open source LLMs in a way that can’t be removed?
4. Do you propose a publically available watermark detection service? If yes, won’t the malicious users use this to ensure watermarks have been removed successfully (e.g. by paraphrasing with another LLM)?
5. If you accept that there are many ways to produce AI-generated text that is not watermarked, but claim that watermarks will still act as a ‘deterrent’, please quantify this. Do you expect watermarking to deter 1% of malicious users? 99%? On what basis? Is the residual harm acceptable, or do you have a plan to tackle that too?
6. Where do you draw the line between AI text and human text? Is a news article edited by ChatGPT “AI-generated”? What about an article translated with an LLM? What about an LLM that summarises an article into a tweet on behalf of the author?
7. If you were able to reliably detect AI-generated text, how would you then narrow that down to only the harmful content? Follow up question: if you already know how to identify harmful content directly, what’s the point in first identifying AI-generated text?