[calny]

This is a really interesting point, and you're right to say it's complicated. I'm sort of an anti-IP hawk (I actually rep defendants in IP cases) and personally agree with it. But the US Copyright Office's position on GenAI supports the opposite view:

> Nor do we agree that AI training is inherently transformative because it is like human learning. To begin with, the analogy rests on a faulty premise, as fair use does not excuse all human acts done for the purpose of learning. A student could not rely on fair use to copy all the books at the library to facilitate personal education; rather, they would have to purchase or borrow a copy that was lawfully acquired, typically through a sale or license. Copyright law should not afford greater latitude for copying simply because it is done by a computer. Moreover, AI learning is different from human learning in ways that are material to the copyright analysis. Humans retain only imperfect impressions of the works they have experienced, filtered through their own unique personalities, histories, memories, and worldviews. Generative AI training involves the creation of perfect copies with the ability to analyze works nearly instantaneously. The result is a model that can create at superhuman speed and scale. In the words of Professor Robert Brauneis, “Generative model training transcends the human limitations that underlie the structure of the exclusive rights.”[0]

I disagree with the Copyright Office here, but ofc they're the Copyright Office and I could be wrong. More broadly I'm struggling with how to permit and incentivize creation of powerful generative models while not screwing creators in the process. There are startups and other efforts trying to address this through novel licensing, etc., but AFAIK there's no great solution. I'm also cautiously optimistic that there will be some decentralized and/or federated options. It's complicated indeed.

[0] https://www.copyright.gov/ai/Copyright-and-Artificial-Intell...