AI's aren't sentient. They can't "steal."
Programmers and institutions select the data with which to train the model. They take art and writing from artists and authors without credit or payment. The software then remixes and mimics what it is given.
Displacing agency by attributing intent to the AI is exactly how people and institutions erase human action in the creation of technology. It also leads to further perceptions of technology as acultural, unbiased, and, in essence, magical.
@Manigarm This is an interesting point, and certainly correct.
It's also exactly how humans learn to become artists and writers - by studying, mimicking, and eventually adding to the existing body of work. We don't generally consider that theft, unless the copying is exact or deceptive.
Yet AI feels somehow different, much more like plagiarism. Perhaps it's that the ONLY input an ML system has is others' art, with no real-world human experience of its own to contribute.
In my high school arts classes, when we did reproductions of renowned art, it was known as a "Master's study" to attempt to learn, first hand, how the original creator may have gotten to an end product by attempting to mimic their output as precisely as possible.
I do not know if that nomenclature is widespread?
Steve Jobs uttering "good artist copy, great artists steal" can be attributed at least as far back as Picasso. Others cite T.S. Eliot: https://quoteinvestigator.com/2013/03/06/artists-steal/
@Manigarm It seems relevant that similar discussions seem to have occurred throughout history every time a new artistic medium is introduced, especially those involving some kind of automation.
Is photography art? What about music played on synthesizers? Acrylic paints? And so on. Much impassioned hand-wringing about the "end of art" with all of these, all of it seeming very silly in retrospect.
I'm only mostly comfortable saying that someone who writes his name on a urinal is not thereby making art.
I'm ENTIRELY comfortable saying that someone who commissions an artist to make a bunch of pictures is not the one making art, and that this doesn't change if you replace the (actual) artist with a machine.
@byterhymer Didn't the Steve Jobs version of that aphorism famously end, at least by implication, with "but not from me"?
I also think the comparison to training an AI and human learning, while somewhat clever, ultimately misses the mark. A human studying the old masters (or any other source of inspiration) is making conscious decisions about what to emulate.
They're not making a spreadsheet of every element of every artwork they've ever seen and picking out the elements with the strongest statistical correlation with keywords they were given.
@mattblaze @Manigarm I think photography is another useful reference--the photographer doesn't create the imagery they capture from nothing, but they choose what to photograph, tuning parameters of the camera (which they probably didn't build either), making tweaks to an image after the fact, etc.
We don't have as much trouble assigning a creator in those instances--are the AI designers like the camera makers? are the images input into the model like the made objects that appear in a photo?
@zalcarik @Manigarm Yes, I think photography is a good example. When I make a photograph (and I use the word "make" quite deliberately instead of "take"), I'm trying to produce art. We can argue about whether it's good art or bad, but there's no longer any serious question, here in the 21st century, done with intention, that photographs can be art.
Why is selecting the input and curating the output of an AI system any different?
@ShadSterling I think that's a common misconception, these AI models almost never work in a way analogous to that. To carry on the analogy about finding a photo spot (where "I" am acting like the AI now), it would be if I looked at the google image results to learn what the place looked like, then stepped over to a canvas and painted a picture of what I remembered.
A novel work is being created, but yes also one that is intrinsically derivative of the work of others.
@ShadSterling But that's pretty on par with what human artists need to do. Consider not the scenic photo spot, but instead something like a dragon--there's no real-world example an AI or human could draw from, they need to make reference to existing art.
I think that's all still mostly tangential to the issue of authorship and creative/artistic input. The AI/camera are backboxes, that take inputs and allow for creative input in turning those inputs to outputs.
@ShadSterling That video elides much of what's being considered here though, namely the actual representational/encoding part of the network. The part you're looking at is the part of the model that turns the abstract representation into an image.
It's not analogous to the creative neural activity performed by a human artist, but rather the series of motor functions needed to move a hand across a page to draw a line.
@ShadSterling Perhaps the most significant departure from your analogy is that the images are not in the model. It doesn't combine different amounts of images it's seen before, it combines different amounts of abstract concepts that it learned from images it's seen before.
When it creates a landscape it doesn't find 100 landscapes in its training set and weight them accordingly, it proceeds from landscape to some combination of mountain-ness, hill-ness, and tree-ness, and so on.
@zalcarik I would have preferred that the video include more about the intermediate data; if you know of one that covers that similarly succinctly I'd like to see it
The AI has nothing like motor functions or abstract concepts like "hill-ness" (or even lines); AIUI it has something like probabilities of pixel value relationships associated with words or phrases, and it's generating an estimate of the most likely image similar to how language models generate an estimate of the most likely text.
@sehe I can see an argument for "less valuable", but aren't there still analogues with photography? cliché photo spots, etc. "If you want a nice picture of the skyline, you go to this overlook at sunset" sort of thing.
I think that's still in the realm of good/bad or impressive/lazy, it's on a continuum that's still within the art-space. Even if the act of discovery is constrained in different ways, can't we still identify a sense of human authorship?
@sehe I think a lot of this is confounded by the fact that the technology is so new that we're being inundated with a lot of, essentially, amateur art. So much of what I see from AI art feels like what I produced when I first discovered all the stuff I could do manipulating random noise textures on a computer.
We're still figuring out how to be expressive with this new suite of tools. But I do think the ability to be expressive is there, even if the tendency is towards banal expression for now
@zalcarik Oh yes. The problem is more short-term. In the short term people will mistake the AI for the original artistry that was used as prompt and training.
It becomes malicious when copy-cats are using established artist's names to *sell* AI-generated works - basically swindling artists and buyers alike.
The problem isn't that AI cannot be used constructively. Nor that humans would be redundant. The challenge is, how do artists survive in the presence of predatory competition. #ethics
@zalcarik Another comparison would be: nobody would mind that mediocre painters would have employed the camera obscura to get the scene right.
However, it would be a problem if they then passed it off as the work of a renowned painter. It's a brand protection problem, where previously required skills were a natural barrier to infringement.
Nothing new, just new in these particular areas and extents.
@mattblaze
Honestly, a lot more artists do small scale sales in middle-class contexts than do sales to the rich, and in that context, their work is bought for a more utilitarian understanding of decorativeness+meaning, much closer to the illustration case. But what I mean around labor and value-accrual is on the other end. None of these systems work without the training data, and there derivative works that conversation compressed versions of that training data, and yet the value accrues entirely to an intermediary. Artists have the right to set their own rates for derivative works licensing. I'm not usually an IP maximalist, but there's a meaningful distinction between access to culture on an individual basis and the creation of a system intended to evolve to a point where the work of the people from which its creators are stealing is entirely replaced.
Something entirely based on theft from other people cannot be art. An original tuned prompt absolutely can have artistic merit, but the artistic merit and "artness" of the result rests almost entirely on a) the work of the ML engineering team, and b), much more heavily, on the source material. Now, there's of course a long tradition of artists working with general purpose software and having that software considered a tool or at most (e.g. with reactive projection mapping installations and touchdesigner or max) a medium, so we can ignore the first. However the last is and always will be an intrinsic component, massively more important than anything involved in prompt engineering. The prompt engineering has contributed almost none of the art and should receive almost none of the value.
It would be perfectly possible, if any of these companies cared, to create a fair licensing structure and modeling systems that could provide a proportional attribution distribution across the source material derived from each prompt, paid out in accordance with derivative work prices determined by the rights holders. Until they do this, it's nothing but theft.
@dymaxion @mattblaze If we said somehow that we didn't want to let any copyrighted art be consumed by AI, and it was a successful influence on culture, are we not just washing out all innovation from the last 90s years? Will artists have to chase that fashion to stay relevant? If AI replaces artists, does that just push them more into the fine art world of catering to the rich?
Can they be pushed more that way? They're already just about entirely there.
@mattblaze @Manigarm I think a substantial part of the reason also comes down to market effects.
What makes plagiarism grate for creators (artists, writers etc) is that their work is high-intensity, and they object to plagiarists in part because those plagiarists avoid the costs of developing the creative talent/expertise to produce cheaper alternatives and that impacts the creator's ability to get ROI on their work. AI does that to an *insane* scale, essentially annihilating the whole market.
@Manigarm @Pwnallthethings @mattblaze I guess what I’m trying to say is that “it’s harder for humans to do this than machines” isn’t enough of an argument.
But trying to define what the missing “this” is, that question’s going to take you straight into the hardest problems of consciousness and computer science. I don’t envy the person trying to win that fight, long term.
Dr. Holly Walters
Matt Blaze
グレェ「grey」
Steve Bellovin
Linebyline→mastoart.social
std::polar
zalcarik
ShadSterling
Eleanor Saitta
Quinn Norton
Denial 🐔 Shown
TJ McIntyre
Pwnallthethings
Jed Brown
Matthew Green