The point isn't about money. It's that copies were made, without license and without permission, and without any legal right to do so, of art, and then used to train a system which generates similar art. The first step, the copy, is illegal without a license, and even for most public images online, licenses and copyright notices (which must be preserved) are attached.
"Fair use" counters "without license and without permission" hard. The argument that training AI on scraped data is "fair use" and the resulting model outputs are "transformative works" has held up in courts. Anthropic got dinged for downloading pirated books, but not for throwing the ones they didn't pirate down the training pipeline.
Some countries, like Japan, have amended their copyright laws to make AI training categorically legal. Others are in "fair use clauses" grey areas with courts deciding case by case based on precedent and interpretation. So trying to latch onto copyright law is, as it always was, the wrong move. Copyright never favored the small guy. Stupid to expect that it suddenly will.
Nope. Nope. Nope. That has explicitly not been ruled on yet. Transformative means that you don't need a fair use defense. Anthropic has only gotten away with their outputs being called transformative so far because they put a dubiously effective filter in front to block the most egregious infringing outputs. No one has actually challenged this afaik.
And what about the artists that inspired them? There is no art in the world that sprang fully formed from one single person, without any influences.
Should we reshape our economy to ensure knowledge and artistic provenance is maintained perpetually?
This whole discussion is so weird to me. It’s like AI has freaked everyone out so much that the instinct is to run to the safety of Disney-esque complete control and perpetual monetization of every work.
Which is exactly the opposite of how art worked for the first several hundred thousand years. Really, we want to double down on the perverse incentives and tight control that IP owners have given us in the past 50 years?
Nope, humans are admitted for free :).
>And what about the artists that inspired them? There is no art in the world that sprang fully formed from one single person, without any influences.
As long as you are a human you get to be inspired all you want :)
You seem very invested in licking the boot of the trillion dollar corporations. Your fellow humans are concerned.
>Really, we want to double down on the perverse incentives and tight control that IP owners have given us in the past 50 years?
Isn't it interesting that the EXACT second that copyright law impedes billion dollar corporations it is thrown out the window, really makes you think huh?
No, a counterfactual world where artists were paid for AI training wouldn't see commercially viable AI at all. A world which plenty of people would be more than happy to live in, mind you.
AI relies on mass piracy worth Googols of dollars if you count like you would the million dollar iPod, but because AI surprised the copyright industry, it's now too late to enforce copyright like that.
It would still be "commercially viable", mind. I'm not sure how much would it stall the AI development in practice, but all the inputs of making AIs only get cheaper over time. So I struggle to imagine not having something like DALL-E 1 by 2030.
If we extend the counterfactual and allow for licensed media, we compress the timelines and raise the bar. The "best" image generation AIs of 2026 are now made by the likes of Adobe and locked behind some kind of $500 a month per seat Creative Cloud Pro Future subscription. Because Adobe is rich enough to afford big bulk licensing deals, while the likes of academia and smaller startups have to subsist on old public domain data, permissively licensed scraps and small carefully selected batches of licensed data that might block them from sharing the resulting weights with the licensing deals.
In the "counterfactual: licensed media" world, the local AI generation powerhouse of Stable Diffusion ecosystem probably doesn't exist at all. Big companies selling AI do. Their offerings cost a lot more and perform considerably worse than the actual AIs we have today. So you can't just go to a random website and get an image edited for a shitpost for free. But the high end commercial suites exist, they're used by the media and the marketing companies, and they are still way cheaper than hiring artists. The big copyright companies get their pound of flesh, but don't confuse that for the artists getting a win.
I think I've got whiplash from the way a lot of the tech scene has gone from 'IP troll outfits are malicious actors who make everything worse for everyone else' to 'IP troll outfits are an ethical and effective solution to exploitation in the AI industry'.
I'm not a huge fan of much of the generative AI industry, but is IP maximalism really the answer here? Before 2022 most of us would have agreed that DRM is generally a scourge for example, and the 'copyright industry' are a big part of pushing for the end of general-purpose computing in favour of DRM-controlled appliances. Personally I'd rather go in the opposite direction, copyright lasts for exactly thirty years and after that a work enters the public domain without exception, and I'd weaken anti-circumvention laws too.
Many of the people who rally against AI now used to rally against Napster being prosecuted by RIAA and the Big Mouse renewing copyright expiration dates once again.
It's not that they suddenly gained an appreciation for the copyright law. It's that they found something they hate more than the big record label megacorps - and copyright became a tool they think they can leverage against it. Very stupid, IMO.
You recon Disney and Shutterstock don't have enough images to make commercially viable AI?
Or for that matter, Facebook? Even just for photorealistic images from, you know, all the photos people upload.
> AI relies on mass piracy worth Googols of dollars if you count like you would the million dollar iPod, but because AI surprised the copyright industry, it's now too late to enforce copyright like that.
Not that I disagree that people use everything they can get their hands on for marginal improvements, they obviously do, but the copyright industry being "surprised" is the default state of affairs for infringement, and "piracy" is the wrong word because that's a law and the judges so far have ruled that training isn't itself a copyright offence, while also affirming that it is possible to commit a copyright offence by pirating training data.
I don't care about getting a millionth of a cent as an artist (which btw is a number *you* just pulled out of your imagination). I care about them paying a fair share instead of pocketing it, so the money stays in circulation instead of creating a new class of technofeudal lords.
These are the most opportunistic busiensses ever existed, created literally within months on top of years of research on NLP and decades of creation. And they provide nothing on return. This will be huge dent on humanity progress timeline.
Therein lies the problem. AI firms just bulldozed ahead and "just did it" with no consideration for the ethics or legality. (Nor for that matter, how they're going to get this data in the future now that they're pushing artists into unemployment and filling the internet with slop.)
There is no "imagined counterfactual", people just want AI firms to follow basic ethics and apply consent. Something tech in general is woefully inadequate at.
The counterfactual isn't offered by artists, but AI companies. "If we had to ask consent then we couldn't have made this". Okay, so? The world isn't worse off without OpenAI's image generator. Who cares, there's no economic value to these slop images, they're merely replacing stock assets & quickly thrown together MS paint placeholders.
Given how much of a shitshow this technology has always been (I refuse to mince words: This tech had it's "big break" as "deepfakes", and Elon Musk has escalated that even further. It's always been sexual harassment.) The actual net value to society is almost certainly negative.
I actually don't have an issue with training off the mass of everyones work if the models are open and free to build upon, it's locking them away and then throwing your toys out the pram when people try and do the same thing that bothers me.
Pre-training is: training a model from scratch on cheap data that sets the foundation of a model's capabilities. It produces a base model.
Post-training is: training a base model further, using expensive specialized data, direct human input and elaborate high compute use methods to refine the model's behavior, and imbue it with the capabilities that pre-training alone has failed to teach it. It produces the model that's actually deployed.
When people perform distillation attacks, they take an existing base model and try to post-train it using the outputs of another proprietary model.
They're not aiming to imitate the cheap bulk pre-training data - they're aiming to imitate the expensive in-house post-training steps. Ones that the frontier labs have spent a lot of AI-specialized data, compute, labor and hours of R&D work on.
This is probably not "fair use", because it directly tries to take and replicate a frontier lab's competitive edge, but that wasn't tested in courts. And a lot of the companies caught doing that for their own commercial models are in China. So the path to legal recourse is shaky at best. But what's on the table is restricting access to full chain of thought, and banning the suspected distillation attackers from the inference API. Which is a bit like trying to stop a sieve from leaking - but it may slow the competitors down at least.
Granted thats time and money but it's an absolute minuscule amount of human hours compared to the scraped data.
We know this for a fact because of parallelization, work of hundreds of millions vs the work of 20-100 even of OpenAIs team worked for the entire lifetimes of the current team and the lifetimes of the offspring of that team and the lifetimes of their offspring even with several lifetimes they still wouldnt have even made a dent in recreating that initial scraped training data.
It doesn't matter how many human hours went into making a Twitter shitpost. What matters is: how much value does it add to pre-training run, and how easy is it to substitute it for another data source.
"Cheap data" has low training value and is easy to replace. Twitter shitposts are worthless except in aggregate. "Expensive data" is what has high training value and is hard to replace. Things like SFT traces, domain expert RLHF guidance, RLVR bits - that's what the "moat" is.
What makes the dataset valuable isn't that the image 0012992 in it is precious and irreplaceable. It's that the index goes to seven digits. Pre-training is very much a matter of scale - and scraping is merely the easiest way to get data at scale.
People who complain about "artists not getting paid" must have in their imagination some kind of counterfactual where artists are being paid thousands for their contributions. That's not how it works. A counterfactual world where artists were paid for AI training is one where an average artist is 5 cents richer, an average image generation AI performs 5% worse, and the bulk of extra data spending is captured by platforms selling stock photos and companies destructively digitizing physical media.