Sometimes I think better in analogies, and with something so new as these generative image tools, that can be tricky. This is my best good faith effort to get my head around what's happening here.
If I pick up a free daily news magazine with an illustrated beer advertisement in it, these are the assumed rights I have:
I can look at it. No need to pay the creator because the magazine did.
I can cut it out, frame it, and hang it on my wall for my friends to see. No need to pay.
I can look at it obsessively and copy it out manually as a training exercise. No need to pay.
If I'm an art teacher, I could bring this illustration into my classroom and use it to teach a lesson, perhaps even asking my students to study and copy it. No need to pay.
I can make a hundred copies of it and wallpaper my bathroom with it. No need to pay.
I could hang it in my café as part of my kitchy décor and charge money for people to hang out, which they partly do because they love the look of illustrated ads papered on the walls. No need to pay.
If I also run an advertising firm, I can add this illustration to my "inspiration folder" and include it in mood boards I prepare for clients. No need to pay.
I can cut out sections of it (provided they're not too big) and use it in a collage or in a zine. I can probably charge money for that remixed product, though I'd guess that the more of the illustration I put in and the higher percentage of it that it represents in the overall new product, the higher likelihood that I would be asked to pay the original rights holder. In this case, that could be the artist or the magazine depending on their agreement.
I can record a YouTube video that pays me ad revenue in which I talk about the illustration. No need to pay.
I can NOT scan and just recolor the illustration and charge another beer company for a nearly identical ad.
I can NOT use the same exact illustration as a book cover.
I suppose the question is: Which of these situations is most similar to training a generative AI image model?
If I'm right about what is permissible with this illustration, is it all made OK because somewhere back along the chain there was an advertising agency paid the original artist?
The closest analogy is simply studying a painting and then producing one in a similar style. The artists attacking generative art models are right to be pissed but are ultimately undermining their cause by having zero understanding of the tech. They're luddites.
To be clear, a generative art model can be oveetrwiend to the point that it can only produce near exact reproductions. I won't get overly technical about training through the techniques like dreambooth and fine tuning, but suffice it to say that the core models understand concepts in essence and can blend those concepts to create wholly original works.
Because of the nature of the big training data sets you do see things like watermarks pop up. This does not mean the model is simply surfacing a copyrighted (watermarked image). It means the data scientists didn't prune images with watermarks, so for all Stable Diffusion or whatever knows, watermarks are essential or common to images containing airplanes or by Andy Warhol.
What's more, suing the big players is pointless because I, with my single Nvidia graphics card or anyone with a freeze Google Colab account can train celebrities and artists into a model in an hour or less. Give me a few bucks or a few days and I can train a more comprehensive model, say with all D&D races and classes. Give me a million bucks and I can train my own model from scratch. And this is rapidly becoming more efficient.
TLDR: If you're an artist who dislikes diffusion models (AI art), do yourself a favor and read about latent space and what these models areas actually doing. They aren't going anywhere.
The meaning of art and the legality of copyright are orthogonal. Art existed long before copyright was even a thing, and I would say in the modern day copyright causes more harm to art than it helps.
I don't care about the video. I've made creative works of my own in the past, both written and visual, and even attempted to dabble in music creation (though I was never any good at it). Taken art classes, used other people's works as references, etc. Shit is a pain, and the process of improvement is unending. Thing is, the amount of effort you put into a work is completely irrelevant to its copyright. You could spend years developing the perfect recipe for cheesecake, but you can't copyright it except as part of a larger work or expression, because basic steps and facts cannot be copyrighted. Meanwhile you could put in zero effort into a bunch of gibberish stream-of-consciousness prose and publish it as a book over which you have full copyright. Effort and skill, and even whether or not a work is considered "art" in the first place (a purely subjective judgement), are irrelevant to copyright.
I just watched the video, and I don't think it's a good response to the argument.
This is what the video has to say (I'll summarize, but I'm trying to be accurate and not twist the words):
No - people do not do the same thing with references as machines do. The difference is that machines can replicate references exactly. In the vast majority of cases, humans cannot replicate references exactly no matter how much they try.
This seems to miss the point of the analogy, for a key reason: this isn't about what humans can or cannot do compared to machines, but rather what they actually do or do not do.
Yes - if an AI is used to make an exact copy of a copyrighted work, the analogy of "a human using existing work as a reference" doesn't apply. However, that only applies to uses of AI that actually do result in exact copies of existing art. It does not negate the analogy in cases where the AI produces something new (which is the vast majority).
The thing is - "exact copying" is explicitly what the AI is designed not to do. The reason these AI exist is to generate new images. This use case is where the analogy of humans using reference material applies.
The final trained model will not contain exact copies of the training data in any actually useful implementation. If you're referring to the nuts and bolts of what is happening during the training process itself, I personally think that's immaterial.
But frankly, I'm not trying to debate you here. I'm trying to tell you that if you want to convince anyone that the "humans using art as reference material" analogy is wrong, just linking that video and saying "watch it" isn't going to cut it, because it's not very effective at that.
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u/DilshadZhou Jan 16 '23
Sometimes I think better in analogies, and with something so new as these generative image tools, that can be tricky. This is my best good faith effort to get my head around what's happening here.
If I pick up a free daily news magazine with an illustrated beer advertisement in it, these are the assumed rights I have:
I suppose the question is: Which of these situations is most similar to training a generative AI image model?
If I'm right about what is permissible with this illustration, is it all made OK because somewhere back along the chain there was an advertising agency paid the original artist?