| ▲ | dahart 8 hours ago | |||||||||||||||||||||||||
In the 2024 preface: > Copyright holders worry about how to exercise control over the use of "their" creative material for training models; but that begs the question of whether copyright holders ever had, or should have, a right to any such control. If a human can read a book and learn from it, and then write their own books, why shouldn't a computer? There’s a small amount of irony in an article that’s discussing copyright, and the invisible but critical context of information, then dismissing the context of copying when it comes to copyright, as well as confusing what copyright protects. I’m certain the author knows that copyright does not protect ideas, it does not protect “colour”, it deliberately only protects the “bits”. In US copyright law this is called the “fixation” of a work. The Berne Convention uses similar terminology: “works shall not be protected unless they have been fixed in some material form.” AI’s “learning” has a different colour than human learning. This has been debated at length on HN and elsewhere, and in the courts, but it’s definitely wildly misleading to compare ChatGPT training on all books ever written and then being distributed (for a profit) to everyone, to one human reading one book and learning something from it. | ||||||||||||||||||||||||||
| ▲ | aftbit 7 hours ago | parent [-] | |||||||||||||||||||||||||
More interesting to me is the "derivative work" concept. If a human sits down with a novel, reads it cover to cover, then writes their own novel which broadly has the same characters following the same plot in the same setting, but with slight differences in names and word choice, is that new work a derivative of the first for copyright purposes? What if they do the same thing for code? What if an AI does either or both of those? IP courts will have some truly novel questions before them this century. | ||||||||||||||||||||||||||
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