A judge and jury are going to laugh in your face.
An exact copy is completely different than “produced new code based on everything it’s seen”. You can try your “it’s just an identity function derivative” if you want, but… judges and juries aren’t idiots. They know that a copy is a copy. You’re not going to pull the wool over their eyes
I am definitely not trying to conclude that copyright or licensing is bad.
I have read the scheduler implementations in a number of different operating systems. If I were to implement a scheduler in a operating system, would you say that there is a probability that my scheduler will be a derivative to some extent of those that I have read? How is this materially different from training a GPT on those same pieces of code, and then asking it to construct a scheduler?
I would argue that while there are differences, there are also similarities. That means that the dichotomy is not true.
I am saying sometimes GPT doesn’t do the thing you’re describing. Sometimes it produces exact copies of something that it was trained on.
When it does that (not a “superficially similar” one, but an exact copy) can OpenAI be held liable for copyright infringement?
Because it seems like they want to avoid liability on both ends. They don’t want to be liable for copyright infringement based on ingesting works, and they don’t want to be liable when their tools produces a *copy* of existing works.
I don’t think that’s an acceptable framework.
I’m arguing that copying is not allowed. And you’re arguing derivative works are not always allowed.
I originally thought you were arguing that derivative works are allowed, and that since copying was a derivative work, that copying was therefore also allowed.
Sorry for my misunderstanding of what you were originally saying.