All it would take for AI to completely collapse is a ruling in the US saying these companies have to licence the content they used to train these tools.

They simply would never reach a sustainable business model if they had to fairly compensate all the people who wrote, drew, edited, sang or just created the content they use.

Simply being forced to respect attribution and licenses would kill them. Will that ruling ever happen? Maybe not. Should it? I think so.

@thelinuxEXP To play the devil's advocate a bit here, but people also learn in a similar way. You have to read to learn how to write. You have to listen to music to learn how to make your own, etc.

I think there are at least 2 main differences. The first one is that a human can only produce so much work on their own, while AI can mass produce.

@thelinuxEXP The other one how derivative the work is. This is hard to tell. A lot of the work that humans produce is derivative too. It's just that we don't normally publish most of it.

With AI somebody can craft an elaborate prompt to make the AI generate very derivative work and then publish it or claim that it's bad.

I'm not on the side of big tech here, but I want to point out that the question is more complex and more nuanced than just "copying is bad".

@ivt @thelinuxEXP i think there is also the fact that, as far as i know, no one has been able to prove ai has ever been creative. it does a whole lot of remixing, but it's not creation, as it's only imitating other art. humans do that too, but they have feelings and life experiences to add onto the art they imitate -- we're not making new songs based solely on previous songs we've heard!

@yukijoou @thelinuxEXP Creativity is hard to define and even harder to measure. I don't think it's suitable to base policy on that.

AI is one of the most dynamic fields right now. Things change in months. Basing policy on its current status (e.g. how it learns, or how it works) is also pointless.

My current thinking is that we should focus on what it produces and whether that is original, rather than on how it was trained.