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An MP3 or any similar format, is a piece of data that exists to create an audio reproduction of a specific work. This single and clearly intentional purpose is
by shkkmo 3y ago
An MP3 or any similar format, is a piece of data that exists to create an audio reproduction of a specific work. This single and clearly intentional purpose is quite different than the quite varied purpose of a trained generalist ML model.
This "transformational" aspect and lack of intent make it much harder to argue that fair use doesn't apply to training the model.
> but in a technical sense they do actually share a lot with the models behind LLMs and other generative ML projects
How so? The "encoding", "decoding" and storage all seem very, very different.
> such software could well be baked into the OSes of major desktop and mobile operating systems by that time
That seems silly. However, if it were to come to pass then models trained with a clear intent for the main use to be reproducing the works it was trained, then fair use in training the model becomes harder to argue.
I would argue that if the liability remains with the users of the model, then there will be demand for tools that check generated works for possibility of infringement.
However, the more the intended use(s) of the trained model differs from that of the copyrighted training material, the stronger that argument for fair use becomes.
I would argue that our approach to ML models should be more akin to a CD burner. It is something that could be used for piracy but if we don't put the responsibility for that on the manufacturers but rather on the users who choose to pirate. This makes sense because the fair use argument of a teacher using a ML model to generate content for their class is very different from a studio using a ML model to make content for a commerical work. If we make the model responsible for the possibility of making infringing content then we take away that flexibility.
- danaris 3y agoThe problem with likening taking other people's work as training data and reproducing it with an LLM to ripping a CD and sharing the files is the direction of power imbalance. In the music analogy, the "owner" of the original content whose copyright is being potentially infringed is a megacorporation making billions of dollars every quarter, with more lawyers than God. The person potentially infringing that copyright is you. It's me. It's random people everywhere. In the LLM case, the "owner" of the original content whose copyright is being potentially infringed is you. It's me. It's Neil Gaiman. It's Toby Fox. It's not just anybody, it's everybody. The entity potentially infringing that copyright is a megacorporation making billions of dollars every quarter, with more lawyers than God. I hope this makes clear why I think one is a problem and the other isn't.
- shkkmo 3y agoYou're making huge assumptions there. Specifically that LLMs are only trained by megacorps (not currently true) or that copyright is only held by individuals (also not currently true.) Besides those mistaken assumptions, I think you have thr copyright issue exactly backwards. Let's imagine the court decides that any computer processing of a work (that isn't intended to help present that work in a licensed manner) requires a special ML license from a each copyright holder. This automatically creates a huge moat for all the large AI companies that can afford that licensing and maybe even negotiate LLM exclusivity. Now you've created an even larger power imbalance by putting this domninant new technology into the control of large corporations. Additionally, legal disputes around copyright already tend to predominantly favor those with large legal budgets. Who is going to be more successful in finding and suing LLMs that use unlicensed content? It's going to be the large megacorp copyright holders. CoughDisneyCough.