I find this problem quite difficult to solve: 1. If I as a human request a website, then I should be shown the content. Everyone agrees. 2. If I as the human request the software on my computer to modify the content before displaying it, for example by installing an ad-blocker into my user agent, then that's my choice and the website should not be notified about it. Most users agree, some websites try to nag you into…
I don't think people have a problem with an LLM issuing GET website.com and then summarising that, each and every time it uses that information (or atleast, save a citation to it and refer to that citation). Except ad ecosystem, ignoring them for now, please refer to last paragraph. The problem is with the LLM then training on that data _once_ and then storing it forever and regurgitating it N times in the future wit…
The "social contract" that has been established over the last 25+ years is that site owners don't mind their site being crawled reasonably provided that the indexing that results from it links back to their content. So when AltaVista/Yahoo/Google do it and then score and list your website, interspersing that with a few ads, then it's a sensible quid pro quo for everyone.
LLM AI outfits are abusing this social contract by stuffing the crawled data into their models, summarising/remixing/learning from this content, claiming "fair use" and then not providing the quid pro quo back to the originating data. This is quite likely terminal for many content-oriented businesses, which ironically means it will also be terminal for those who will ultimately depend on additions, changes and corrections to that content - LLM AI outfits.
IMO: copyright law needs an update to mandate no training on content without explicit permission from the holder of the copyright of that content. And perhaps, as others have pointed out, an llms.txt to augment robots.txt that covers this for llm digestion purposes.
EDIT: Apparently llms.txt has been suggested, but from what I can tell this isn't about restricting access: https://llmstxt.org/