Just like a translation of a book is a derived works of the original. Or a binary compiled output is a derived works of some source code.
> In copyright law, a derivative work is an expressive creation that includes major copyrightable elements of ... the underlying work.
A trained model fails that on two counts, doesn't it? Both the "includes" part, and the fact that a model is itself not an expressive work of authorship.
There's nothing creative about the act of a compiler, it is automatic, just like the training run of an LLM.
And no part of the original source code is in the binary output.
And yet, binaries are a derived work from the source code that went into them.
So something is up! I am not a lawyer though.
It's not about whether the binary includes the raw text of the source, but whether it copies the expressive content. Anything expressive (i.e. copyrightable) in a compiled binary must have come from the sourcecode, so that's what makes it a derived work.
But the same isn't true of LLMs, which are more like "data about their inputs", than "a transformed version of their inputs".
Translation of a book is non-transformative and retains the original author's artistic expression.
As a counter example - if you write an essay about Picasso's Guernica painting, it is derivative according to our colloquial use of the term, but legally it's an original work.
Genuinely curious: for anyone who thinks AI obviously violates copyright, how do you resolve this? E.g. do you think the violation happens during training or inference? And is it the trained model, or the model output, that you think should be considered a derived work?