A new tool lets artists add invisible changes to the pixels in their art before they upload it online so that if it’s scraped into an AI training set, it can cause the resulting model to break in chaotic and unpredictable ways.
The tool, called Nightshade, is intended as a way to fight back against AI companies that use artists’ work to train their models without the creator’s permission.
[…]
Zhao’s team also developed Glaze, a tool that allows artists to “mask” their own personal style to prevent it from being scraped by AI companies. It works in a similar way to Nightshade: by changing the pixels of images in subtle ways that are invisible to the human eye but manipulate machine-learning models to interpret the image as something different from what it actually shows.
I agree that copyright lasts far too long, but the idea I can post a picture today, and in a hour it’s in an AI model without my consent bothers me. Historically there was a person to person exchange. But now we are so detached from it all I don’t think we can have that same affordance of no types of protections. I’m not saying one person can solve this. But I don’t see UBI or anything like that ever happening. As a person who has lived on disability most of their life, people don’t like to share their wealth with anyone for any reason. I’ve never been able to sell art for a living and am now going to school for data science. So I know about both ends of this. Just scraping without consent is unethical and many who do this have no idea about the art world or how artist create in general.
I doesn’t need to be full on UBI. In a lot of countries grants mechanisms and public purchasing mechanisms for art already make up a significant proportion of income for artists. Especially in smaller countries, this is very common (more so for literary works, movies and music where language provides a significant barrier to accessing a bigger audience, but for other art too). Imagine perhaps a tax/compulsory licensing mechanism that doesn’t stop AI training but instead massively expands those funding sources for people whose data are included in training sets.
This is not stoppable, not least because it’s “too cheap” to buy content outright.
I pointed out elsewhere that e.g. OpenAI could buy all of Getty Images for ~2% of their currently estimated market cap based on a rumoured recent cash infusion. Financing vast amounts of works for hire just creates a moat for smaller players while the big players will still be able to keep improving their models.
As such it will do nothing to protect established artists, so we need expansion of ways to fund artists whether or not inclusion of copyrighted works in training sets becomes restricted.
Those grants, and public purchases make up a significant portion of income for established main stream artists. If you work on commission only online, or never went to art school those won’t cover you.
These large tech companies become so highly valued at the start because of venture capital and then in 5-10 years collapse under their own weight. How many of these have come up and are now close to drowning after pushing out all competitors? Sorry if I’m not excited about an infusion of cash into a large for profit company that is just gobbling up anything anyone posts online without consent to make a quick buck.
I’m not against AI. I’m against the ethics of AI at the moment because it’s awful. And AI leans into biases it finds and there are not a lot of oversights on this.
There’s no reason it has to stay like that. And most people in that position are not making a living from art as it is; expanding public funding to cover a large proportion of working artists at a better level than today would cost a pittance.
MS, Apple, Meta, Google etc. are massively profitable. OpenAI is not, but sitting on a huge hoard of Microsoft cash. It doesn’t matter that many are close to drowning. The point is the amount of cash floating around that enable the big tech companies to outright buy more than enough content if they have to means that regulation to prevent them from gobbling up anything anyone posts online without consent will not stop them. So that isn’t a solution. It will stop new entrants with little cash, but not the big ones. And even OpenAI can afford to buy up some of the largest content owners in the world.
The point was not to make you excited about that, but to illustrate that fighting a battle to restrict what they can train on is fighting a battle that the big AI companies won’t care if they lose - they might even be better off if they lose, because if they lose, while they’ll need to pay more money to buy content, they won’t have competition from open models or new startups for a while.
So we need to find other solutions, because whether or not we regulate copyright to training data, these models will continue to improve. The cat is out of the bag, and the computational cost to improving these models keeps dropping. We’re also just a few years away from people being able to train models competitive to present-day models on computers within reach of hobbyists, so even if we were to ban these models outright artists will soon compete with output from them anyway, no matter the legality.
Focusing on the copyright issue is a distraction from focusing on ensuring there is funding for art. One presumes the survival of only one specific model that doesn’t really work very well even today and which is set to fail irrespective of regulation, while the latter opens up the conversation to a much broader set of options and has at least a chance of providing working possibilities.
I don’t see these grants or public funding ever covering a private company for one. And for two, I don’t see AI art ever actually getting to the point where it fully replaces artists. As of right now it is good. But it doesn’t understand space or lighting at all. Because of how AI works I’m not sure it ever will. Because it is trained to make a homogeneous rendering of what you are looking for, even if you use a base image, most people have an image that is lit heavily in the front, but because of this it never is able to render shadows correctly. Unless they hire people who are artist or art critics to finely train the data set, which I doubt they will, then the more you look the more uncanny valley the images get. They also have a hard bias in all of their images they generate. Which is difficult to overcome.
AI is an amazing tool, but it is a poor replacement in total. The people who act like it is a total replacement are like the people who in 2015 told us self driving cars were just one year away, and have been saying it every year since. Maybe when quantum computing becomes the standard for every person AI will be able to. But there is just a fundamental misunderstanding of art, artistic process, how art get made people seem to have.
Open AI might be sitting on Microsoft money, but how many other companies has Microsoft gobbled up over the years? Open AI if it starts to struggle will just fall under the Microsoft umbrella and become part of its massive conglomerate, integrated into it. Where are our AR goggles that we are supposed to all be wearing, Microsoft and Google both had those? So many projects grow and die with multiple millions thrown at them. All end up with crazy valuations based on future consumer usage. As we all can’t even afford rent.
There is also this idea that people wouldn’t willing contribute if just asked. The problem is no one has even asked. Hugging Face is an open source distro people willingly contribute to. And so many people upload images to Creative Commons which could be used. I’ve done it with many of my photos which I have no problem being used in a data set, for commercial use even. But my commercial images, no please. The idea that you can’t train smaller models on the vast array of Creative Commons images and public domain, you absolutely can. You can also ask people to contribute to your data set and give credit to them. A lot of people are angry at lack of credit.
There is no reason for any of this to be private enterprise if they are going to blatantly steal copyright images when sources like Creative Commons exists, not give any credit to the people they steal from, and sometime even steal from places they shouldn’t even have access to.
Companies are by far the largest recipients of public funding for art in many countries and sectors. Especially for e.g. movie production in smaller languages, but also in other sectors.
I do agree it won’t fully replace artists, but not because it won’t get to the point where it can be better than everyone, but because a huge part of art is provenance. A “better Mona Lisa” isn’t worth anything, while the original is priceless, not because a “better” one isn’t possible, but because it’s not painted by Da Vinci.
But that will only help an even narrower sliver than the artists who are making good money today.
It will take time, but AI will eat far more fields than art, and we haven’t even started to see the fallout yet.
Diffusion models are not trained “for” anything other than matching vectors to denoising to within your own tolerance levels of matching to what you are looking for. Accordingly, you’ll see a whole swathe of models tuned on more specific types of imagery, and tooling to more precisely control what they generate. The “basic” web interfaces are just scratching the surface of what you can do with e.g. Controlnet and the like. It will take time before they get good enough, sure. They are also only 2 years old, and people have only been working on tooling around then for much less than that.
OpenAI is just one of many in this space already. They are in the lead for LLMs, that is text-based models. But even that lead is rapidly eroding. They don’t have any obvious lead for diffusion models for images. Having used several, it was first with the recent release of DallE 3 that it got “good enough” to be competitive.
At the same time there are now open models getting close enough to be useful, so even if every AI startup in the world collapsed this won’t go away.
That’s fine, but that doesn’t fix the financial challenge.
So what you are saying is open ai should get the public grants for artists to give to artists?
I understand it isn’t trained for anything, I have done training with them. The training leads to homogeneous outcomes. It had been studied as well. You can look it up.
Dall-e 3 still isn’t good enough to be competitive. It is too uncanny valley. I’m not saying people have to be the masters. I don’t know where you get that from, every one who touts this tech always goes to that. It is a tool that can be useful, but it is not a replacement.
Asking and crediting would go a long way to help fix the financial challenge. Because it is a start to adding a financial component. If you have to credit someone there becomes an obligation to that person.
No. What in the world gave you that idea? I’m saying artists or companies employing artists should get grants, just like is the case for a large number of grants now. I’m saying I’d like to see more of that to compensate for the effects being liberal about copyright would have.
There is no “the training”. There are a huge range of models trained with different intent producing a wide variety in output to the point that some produces output that others will just plain refuse.
Dall-E 3 isn’t anywhere near leading edge of diffusion models. It’s OpenAI playing catch up. Now, neither Midjourney or Firefly, nor any of the plethora of Stable Diffusion derived models are good enough to be competitive with everyone without significant effort either, today, but that is also entirely irrelevant. Diffusion models are two years old, and the pace of the progress have been staggering, to the point where we e.g. already have had plenty of book-covers and the like using them. Part of the reason for that is that you can continue training of a decent diffusion model even on a a somewhat beefy home machine and get a model that fits your needs better to an extent you can’t yet do with LLMs.
If there is a chance crediting someone will lead to a financial obligation, people will very quickly do the math on how cheaply they can buy works for hire instead. And the vast bulk of this is a one-off cost. You don’t need to continue adding images to teach the models already known thing, so the potential payout on the basis of creating some sort of obligation. Any plan for fixing the financial challenge that hinges on copyright is a lost cause from the start because unless it’s a pittance it creates an inherent incentive for AI companies to buy themselves out of that obligation instead. It won’t be expensive.
I feel like you are one of the people who feel that AI is just going to be the future with no real problems to anyone who matters. We can’t stop it, we can’t regulate it in any way whatever; and people should just move out of the way, give up and if they can’t find a place in the new world, die already. Artists don’t matter, writers don’t matter and anyone impacted by this new system doesn’t matter. The algorithm is all that matters.
Because I don’t use the exact correct wording, I use a short hand that is easier for my brain to remember, and you are pedantic, I can’t know anything about LLMs, machine learning or anything about this. Because I don’t say it has a training set of a large model of images that are tagged in specific ways that they can take out antagonistic images or images that create artifacts and refine the model in appropriate ways. You therefore throw out the idea that bias exists due to tagging systems.
Honestly I don’t care if you don’t think I know anything about this. You are a stranger on the internet and this conversation has gone on too long.