> anything that a computer does can be construed as making a copy.
but that's not the point of contention. The training data set has been granted the right to be distributed (by virtue of it being available for viewing already - it's not hidden or secret). The proof is that a human can already view it manually. Let's call this 'public'.
The question is, whether using this public training dataset constitutes creating a derivative work. Is the ML model sufficiently transformative, that the ML model is itself a new work and thus does not fall under the copyright of the original dataset?
>but that's not the point of contention. The training data set has been granted the right to be distributed (by virtue of it being available for viewing already - it's not hidden or secret). The proof is that a human can already view it manually. Let's call this 'public'.
This is wrong. My paintings are publicly available (especially going by your definition [which I'm confused by the origin of?]). Taking a photograph of my paintings is still a copyright violation. I hope we can ignore all the legal kerfuffle about personal use, as it has no bearing on our discussion. Again -- all of this boils down back to what I've said before: Bare human consumption does not constitute as making a copy, nearly everything else does.
Your second point -- a copyrighted work automatically granting someone else any rights (especially distrubtionial rights) by just being available to be consumed -- is even more wrong. I'm not going to go further into that, as you can very easily prove yourself wrong by googling it.
>The question is, whether using this public training dataset constitutes creating a derivative work
I'm not well versed in the US copyright laws, but I would assume (strongly so) that this would not be the case. I -- again, for US copyright law -- assume that for something to be considered a derivative work, it needs to include (or be present in other ways) copyrightable (!) parts of the original work(s). In other words, the original work needs to "shine through" the derivative work, in one way or the other. The delta of parameter changes of a ML model would (imo) not constitute such a thing.
Problems with derivative works will come into play when considering the things ML models produce.
But the AI is (supposedly) not making a copy of your painting. It is ingesting it, and adjusting it's internal "model of what a good painting looks like" to accommodate the information it gleaned from your work. This seems more similar to what a human might do, when they draw inspiration from another's work. The question is - to what extent does the exact image of your painting remain within the AI's data matrices? That, no-one knows for sure.
> But the AI is (supposedly) not making a copy of your painting.
You are mixing up the two things that I've mentioned in my original comment. You have to differentiate between creating a copy and creating a derivative work. Both of those things matter, when talking about AI, but the former is way more cut clear.
>The question is - to what extent does the exact image of your painting remain within the AI's data matrices?
And the answer is: It's irrelevant. The model has to be ingested with a copy of something. That's all that matters. The AI could even reject learning from that something. By the time that something reaches the AI to even do something with it, it's been copied (in the literal sense) who knows how many times, each of those times being a copyright violation.
I see what you're saying, though could you not say the same thing about the browser's internet cache? That copies the file from it's original server, to the user's local machine in order to display it efficiently.
The poster is wrong about what constitutes a copy (for the purposes of distribution). The temporary copy that resides in your browser's memory, or local caches, aren't considered violations unless they are publicly accessible.
I would put the same criteria to the copy made for the purpose of AI training. As long as you have the right to view the image, you would also have the right to ingest that image using an algorithm.
but that's not the point of contention. The training data set has been granted the right to be distributed (by virtue of it being available for viewing already - it's not hidden or secret). The proof is that a human can already view it manually. Let's call this 'public'.
The question is, whether using this public training dataset constitutes creating a derivative work. Is the ML model sufficiently transformative, that the ML model is itself a new work and thus does not fall under the copyright of the original dataset?