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this post was submitted on 04 Jan 2024
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Programming
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I think the “learning” process could be similar, but the issue is the scale.
No human artist could integrate the amount of material at the speed that these systems can. The systems are also by definition nothing but derivative. I think the process is similar, but there is important nuance that supports a different conclusion.
I don't think the scale matters. Do we treat human artists that only read 10 books or watched 10 movies before creating something different than the ones that consumed 1000 or 10000? For me the issue of who controls it is much more important. If something like ChatGPT were truly open-source and people could use it any way they want, I would have zero issues with the models being trained on everything that is available. We desperately need less copyright instead of more. Right now I think going after the big AI models with copyright is a double-edged sword. It's good to bring them down, but not at the cost of strengthening copyright.
If these systems could only reorganize and regurgitate 1000 creative works, we would not be having this conversation. It’s literally because of the scale that this is even relevant. The scope of consumption by these systems, and the relative ease of accessibility to these systems is what makes the infringement/ownership question relevant.
We literally went through this exercise with fair use as it pertains to CD/DVD piracy in the 90’s, and Napster in the early 2000’s. Individuals making copies was still robbing creative artists of royalties before those technologies existed, but the scale, ubiquity, and fidelity of those systems enabled large-scale infringement in a way that individuals copying/reproducing them previously could not.
I’m not saying these are identical examples, but the magnitude is a massive factor in why this issue needs to be regulated/litigated.