> No, other people did. They wrote about it, and LLM can sometimes use that. Once they no longer write about it, what then?
It can read the code? Historical discussions around it? Commit histories?
> But even then, people aren't entitled to the knowledge "created" by doing the work. If attribution and compensation were tackled in earnest, if you could only train on the materials of the people you pay to produce those materials, it might be much quicker and cheaper to just learn CSS.
OSS code and people’s public writings are available to anyone all the time. Common Crawl, the open source web crawl dump, has been around for over a decade. No one had any problem with these systems being developed on them, until they finally started to become useful, so what’s the sort of legal or ethical framework you’re pointing to?
> It can read the code? Historical discussions around it? Commit histories?
Assume everybody is now using LLM because they're better, and because the people who created artisanal things in their free time out of sheer generosity no longer have free time, or any food at all, or simply no longer feel generous. And the few people who are such specialists that they would be slowed down by them only do proprietary work, for lots of money.
What then? LLM learning from LLM doesn't really work, does it?
This is not intended as some kind of gotcha, to me this is a huge elephant on the couch.
> No one had any problem with these systems being developed on them, until they finally started to become useful, so what’s the sort of legal or ethical framework you’re pointing to?
That it's perfectly fine for people to say "I was fine with that, but I'm not fine with this". They can give you detailed explanations for their individual decisions, every single one of them, but there is no point in discussing them in aggregate because that aggregate is an abstraction. And they're optional, too, it's not like people have to give an explanation, and aren't simply free to change their mind for no or for bad reasons.
still though, whats causing the old code to disappear? the old discussions to disappear?
theyve already been added to all the big labs' datasets, its not like its going anywhere.
but even moreso, accessibility tools exist because people need them, and will make it known when the accessibility is broken.
the screen reader is still gonna expose an api or have observable outputs.
There's very real forcing functions that will keep making useful content about what people want and need from accessibility tools, and how to interact with existing tools.
you're still building for people and the harness operator as time goes on, will probably be the actual user, and will push the LLM to adjust the code to be great for them
> Assume everybody is now using LLM because they're better, and because the people who created artisanal things in their free time out of sheer generosity no longer have free time, or any food at all, or simply no longer feel generous. And the few people who are such specialists that they would be slowed down by them only do proprietary work, for lots of money.
> What then? LLM learning from LLM doesn't really work, does it?
Oh what no that’s exactly how it works, even today. RL with verification is done with synthetic data and rejection sampling. If something can’t get done purely with an agent that needs to get done it’s done with human help, this will always be the case it will just get rare-er.
> That it's perfectly fine for people to say "I was fine with that, but I'm not fine with this".
Agree with you there, but there’s a theme or insinuation (not saying you’re saying this) that these companies “stole work” (which definitely a lot of copyright violations sure), but it’s just unclear to me what principles or legal frameworks these companies or institutions should have used to develop the technology. I don’t really even know whether I mean to imply it’s not unethical, moreso I’m looking for a steel man argument to this. But of course people are entitled to their value systems and judgements and to point out real harm.
> there’s a theme or insinuation (not saying you’re saying this) that these companies “stole work” (which definitely a lot of copyright violations sure), but it’s just unclear to me what principles or legal frameworks these companies or institutions should have used to develop the technology.
Oh, I'm absolutely one of the people saying that a lot of companies stole a lot of work, and that it would be better to dissolve them and make all their assets public domain, than to stand for it.
The legal and moral framework is to ask for permission, accept "no". The same framework they use against you in an instant, with an army of lawyers, when you do to them what they did to everybody.
None of this in principle, technically, requires slurping up everything and ignoring consent, that just made it quicker and cheaper, that's why they did it. While they did that, I'm sure other labs made progress in the same direction at much smaller pace, in a defensible manner, of which they should get to keep the fruit.
> It can read the code? Historical discussions around it? Commit histories?
And if everyone bunkers up and all that open content dries up starting in 2026, let's say, what happens?
It won't happen, for two reasons. One is that great deal of open-source software and hobbyist knowledge sharing has never been driven by financial reward anyway and people will continue to do it anyway. Finer grained controls over opt-outs would be great (the equivalent of a search engine 'nofollow' would be great and will hopefully come with time).
Many kinds of technology faced this kind of tragedy of the commons argument in the past and it never bears out. Printing presses copied manuscripts, search engines copied and indexed web pages, open-source software was incorporated into commercial products, Wikipedia repackaged knowledge produced elsewhere.
In almost all cases the total amount of creation increases because the technology lowered costs, expanded audiences, or created new forms of value. The speed of creation of new 'View Source' outpaces the number of people pulling back.
> great deal of open-source software and hobbyist knowledge sharing has never been driven by financial reward anyway and people will continue to do it anyway.
A lot of open-source software was supported by developers having stable well-paying jobs that didn't burn them out and afforded them enough free time to work on passion projects on the side, so that even if their company wasn't directly supporting their OSS development, there was still an indirect link.
Not only is this likely to increasingly change in the future as people need to spend more time navigating the disruption AI will have on labor, it already visibly has been changing over the past year.
One of the top posts on HN today is someone leaving open source and tech completely to work at Home Depot -- while this is an extreme case it isn't wholly unique to what I'm seeing in many places since 2025.
> In almost all cases the total amount of creation increases because the technology lowered costs
But this doesn't lower the cost of learning and writing CSS, it just scoops up some of it and offers that cheaply, and even that only because it's offered below cost. If anything I'd say it increases the cost, because now you don't get paid to get and be good at what an LLM is supposedly good enough at, and have less free time to do it anyway. You may not even have a computer because your current one broke and you can't afford a new one.
It will happen and it already started to happen. It started to happen even before LLM, when google started to hide smaller personal blogs in its search result. Expectation of the monetary reward has nothing to do with it, discoverability does. Culture of creating content does not exist when people cant see what others created and know no one will see what they created. A lot of smaller open source was monkey see monkey do thing - we have seen other open source projects and wanted something like that. Likewise with tutorials, we have seen other people write cool tutorials and felt like creating own and showing it out.
That is not the dynamic with LLM. You see LLM output, but original creator is hidden. And if you write your own, no one will find it. Worst, other people will tell you "LLM could have write it" in reaction ... so people wont bother.
> search engines copied and indexed web pages
Notably, search engines sent people toward web pages. And when search engines stopped doing that and started to copy content, those original pages started to die out.
> Printing presses copied manuscripts
Printing press made dissemination easier. It is an equivalent of early internet, not of LLM.
> open-source software was incorporated into commercial products
Commercial product using open source library had different user then the library it is using. And crucially, it is not hiding that library from the library user.
> Wikipedia repackaged knowledge produced elsewhere
Yes, and we collectively create less encyclopedias. They are not worth writing and checking for correctness anymore, so we don't do that all that much anymore.
Well that historical content and code still exists right? Are you just saying “what if we’re in a world of walled gardens now that OSS dies because people don’t want their work stolen” in which case: these companies will get data and they don’t need OSS anymore. It’s already webcrawled or licensed or commissioned, they pay people to generate novel traces when they need it or at the very least sets of prompts and tests for verification. Then synthetic data gets added to the training set, the ones that are verified.
That sounds like it would reduce the blazing progress of the last decades to a snail's pace, some twilight where software is just average, as it always was and always will be. That people will always do the thing the opposite of which is now incentivized doesn't convince me, basically. If just using the LLM gets you ahead in a time of severe pressure, then most people will do that, and by the time anyone realizes they kinda need a FEW people to actually be able to reason about something from start to finish, it might be to late.
We're not such a smart species. It's not like we managed so far. We're just adding unsolved problems, and distract ourselves with even bigger problems. The world could have been fed and clothed by the mid 20th century and we could have solved climate change by the 1980s (talking out of my ass here but with confidence in my general point with that), but instead we now throw everything into the furnace. in the hopes it will create a deus ex machina, like in that very bad Isaac Asimov story. I think we are absolutely capable of lobotomizing ourselves (as a species) like a toddler playing with an electrical socket shocking itself. I don't say this to be snarky, I honestly think we're that unserious and ignorant about what we do and the environment we do it in.
But I also really should look into what you answered about LLM learning from themselves, I heard it mentioned before but I still have no real clue. I will try to rectify that. I mean, I really, really want to be wrong on this, only a monster wouldn't.
> by the time anyone realizes they kinda need a FEW people to actually be able to reason about something from start to finish, it might be to late.
I dont think it will be "too late" by any reasonable definition. All those things are learnable and companies that will really need to overcome it, will. But, they wont be open with their knowledge. Learning/training will be expensive and once people acquire it, they wont share it like open sources and programming tech blogs did.
This is super hilarious :-)))
Do you think creating the orders of magnitude of content the internet produced organically and which LLM creators are stealing is cheap? If they actually have to pay for content creation while competing with content creators on the you know, content creation front via LLM-generation, the entire business model of LLMs collapses.
You can't have the mountains of data needed for LLMs in the decades to come, if your LLMs put the writers and artists out of work.
It’s literally how these models are trained today. They of course use open source data but that’s no longer the most important source, it’s high quality prompts and verifiable tests and a lot of inference compute. They also have massive flywheels from users from which they can mine good data or at the very least again good prompts which can be just as important.