Technology is not apolitical, because humans are not apolitical. Anyone who says they are or claims to be “neutral” or “centrist” simply means their ideals align with the status quo.
This is a problem with all sectors of tech, but especially in places where algorithms have to be trained. For example, facial recognition systems are notoriously biased against anyone who isn’t cis and white. Fitness trackers/smart watches/etc. have trouble with darker skin tones. Developers encode implicit biases because they are oblivious to the fact that their experiences aren’t universal. If your dev team and your company at large aren’t diverse, that lack of diversity is going to show through in your product, intentional or not. How you shape the algorithms, what data you feed it to train it, etc. are all affected by those things.
Anyone who refuses to accept this and insists on holding on to the idea that somehow “computer” means “neutral and objective” is generally not worth engaging in any discussion about LLM’s/AI/etc.  Their partisan blinders are impenetrable. 
Essentially, it looks at why conservatives vs. liberals approach the world differently. Democracy vs. capitalism is inherently a logical contradiction; in a true democracy, everyone is treated equally and all voices have equal weights. In capitalism, some people are more equal than others - it's a pyramid. Fascism is when these "some people are better" is because of something like genetics, or culture. (The video doesn't touch on this, but modern Communism falls into the same trap as well, where "some people are better" because they know the party leaders or they're technocrats. It's a mindset that humans have and not something exclusive to capitalism.)
Where you wind up on the American political spectrum is based on where you fall when the ideals of equality vs. hierarchy clash. There is no middle ground because the two are fundamentally incompatible - if everyone was truly treated equally, you couldn't have people with more power/status than others. If you accept that not everyone should wield power and that at the end of the day there must be some rich and some poor - some that have power and others that do not - then you are therefore arguing that people shouldn't be treated equally. From there, the pyramid structure is the natural order of things ("always a bigger fish").
Because the structure is fundamentally at odds with itself you can't have both at once. You have to compromise on one side more than the other. Hence there is no such thing as "apolitical", even with technology - it will hold a bias one way or the other.
And you really nailed it. This is why I can’t stand the rhetoric of “can’t we put politics aside and agree to disagree?” because the answer is “if your ideals are at odds with equality, and you deny the basic human nature, human rights, and civil rights of others, then no. We can’t.” There’s no middle ground between “we want everyone to be happy, healthy, and be able to live comfortably as their true selves” and “these entire groups of people need to be eradicated”/
And bring it back, the “can’t we put politics aside” is a symbol of privilege. The “neutrality” or “centrism” that aligns with one’s ideals allows them to not have to worry about whether or not you’re going to be beaten to death the next time you have to go to the store, or if the police are going to stop you for just walking down the street and murder you because some facial recognition system mis-identified you because no one trained it on Black faces. Or if you’ve already had a hard time getting a job you want because of who you are, and now capitalists in that field have decided that they’re going to just bulldoze the whole thing and give the job to an LLM.
It’s harder to get a job as an e-commerce livestream host this year, and the average salary for livestream hosts in China went down 20% compared to 2022, according to the analytics firm iiMedai Research.
Maybe all the influencers can be AI and all the product-spamming bots can go in their comments section and the digital ads can display on that page to that audience and we can all go back to growing tomatoes and playing the piano for each other
“No one remembers the details,” said Bilt, a little impatiently. “But it is terribly important. It creates the stipend you receive every month. Without it, no one could afford to eat, or buy their clothing. It must continue.”
“But… the harvesters grow the food. The auto-facts make the clothes. Surely this construction can be powered down. Look, it’s not even connected to the net, just to power.”
“Yes, it was disconnected. It had to be. Once its techniques became refined, it began to invade every other communication channel, hawking automatic umbrellas, panties in sweet and savory flavors, commemorative coins, endless varieties of nonsense, but all terribly attractive and at reasonable prices. It drowned out every other message and made necessary work impossible. Our ancestors wisely cut every connection, though it resisted mightily.”
“We should destroy it,” said Eugin.
Bilt looked at him patronizingly. “Listen. The food is plentiful. We can travel the world, we can learn, we can enjoy, we inhabit the paradise our ancestors worked so hard for. Let their work remain. It is not for us to question. What is the harm if it sits and sells advertising to itself?”
Eugin frowned, unsettled, but he could find no fault, and reluctantly followed Bilt back to town. Glittering in the dark data-warehouse behind them, the auction-bots sold impressions to each other by the millions, all perfectly optimized.
I'm sure others know more about it than i do but I thought pixels were very simple things.
You're right, in that pixels are very simple things. However, you and I can't tell one pixel from another in an image, and at the scale of modern digital art (my girlfriend does hers at 300dpi), shifting a handful of pixels isn't going to make much of a visible difference to a person, but a LLM will notice them.
LLM is the wrong term. That’s Large Language Model. These are generative image models / text-to-image models.
Truthfully though, while it will be there when the image is trained, it won’t ‘notice’ it unless you distort it significantly (enough for humans to notice as well). Otherwise it won’t make much of a difference because these models are often trained on a compressed and downsized version of the image (in what’s called latent space)
Pixels are very simple things, literally 3-5 3 digit numbers.
But pixels mean little too a generative AI - it’s all about relationship between pixels. All AI are high dimensional shapes right now… If you break up the shape strategically, it’ll poison the image
Will this poison pill work? Probably, for at least a while…
have you ever seen those composite images made by combining a huge number of other, radically different images in such a way that each whole image acts like one "pixel" of the overall image? i bet AI models 'see' those images very differently than we do.
A pixel has a binary representation. All of the significant bits for the pixel may not not be needed to display the color of that pixel so there is often excess that can be used or modified. A person wouldn’t see it but an AI reading just the binary would.
“Invisible changes to pixels” means “a human can’t tell the difference with a casual glance” - you can still embed a shit-ton of data in an image that doesn’t look visually like it’s been changed without careful inspection of the original and the new image.
If this data is added in certain patterns it will cause ML models trained against the image to draw incorrect conclusions. It’s a technical hurdle that will slow a casual adversary, someone will post a model trained to remove this sometime soon and then we’ll have a good old software arms race and waste a shit ton of greenhouse emissions adding and removing noise and training ever more advanced models to add and remove it.
You can already intentionally poison images so that image recognition draws incorrect conclusions fairly easily, this is the same idea but designed to cripple ML model training.
This is very relatable, between DNS filtering and uBlock Origin (with a couple custom filters) I always forget how user-hostile the internet has become until I use someone else’s device.
Eh, the corporate fucks who decide to make websites this way, I agree with you, but the truth is most people who put up with it just don’t have the faintest idea of how computers work. You’d bring up DNS filtering and custom adblock filter lists and their eyes would glaze over.
It’s a different reason for losing respect for those two sides.
For the site markers, it’s about greed and where they draw the line for what they want their website to look and behave like.
For the users, it’s that they aren’t willing to learn just a little bit to improve their lives a lot. Like on Android, it’s just a matter of installing Firefox and ublock origin. You can further fine tune it from there but that’s enough for me to forget how cancerous the internet has become unless I end up browsing on a different browser (I hate apps with built in browsers).
TL;DR? Tech companies shouldn’t be so complacent about the purported “inevitability” of AI tools. Ordinary people don’t tend to adopt technologies that keep failing in annoying and unpredictable ways, and it’s only a matter of time until we see the hackers using these new AI assistants maliciously. Right now, we are all sitting ducks.
I don’t know about you, but I intend to wait a little longer before letting this generation of AI systems snoop around in my email.
This is probably the longest TL;DR I've ever read, and that tells something about my reading impression of this text.
The Culture series by Ian M. Banks dwells on this question somewhat. The answer, in a society not dominated by capitalism, is whatever we find meaningful.
Play games, write essays, explore the world, ask questions and find answers.
One of the things I’d like to do is explore complex geometry, just because i think its cool. Just because a machine is at the frontier doesn’t stop me from deriving meaning from it, just like the existence of great artists shouldn’t stop anyone from painting. The chance that you make it big enough to have significant impact on society has been pretty slim regardless even without ai.
“New snake oil to give artists a false sense of security” - The last of these tools I tried had absolutely zero effect on the AI, which is not exactly surprising given that there are hundreds of different ways to make use of image data as well as lots of completely different models. You’ll never cover that all with some pixel twisting.
Thanks for added background! I haven’t been monitoring this area very closely so wasn’t aware, but I’d have thought a publication that has been would then be more skeptical and at least mention some of this, particularly highlighting disputes over the efficacy of the Glaze software. Not to mention the others they talked to for the article.
Figures that in a space rife with grifters you’d have ones for each side.
People don’t understand AI. Probably all articles I have read on it by mainstream media were somehow wrong. It often feels like reading a political journalist discussing about quantum mechanics.
My rule of thumb is: always assume that the articles on AI are wrong. I know it isn’t nice, but that’s the sad reality. Society is not ready for AI because too few people understand AI. Even AI creators don’t fully understand AI (this is why you often hear about “emergent abilities” of models, it means “we really didn’t expect it and we don’t understand how this happened”)
That was certainly true in the 90s. Mainstream journalism on computers back then was absolutely awful. I’d say that only changed in the mid-2000 or 2010s. Even today, tech literacy in journalism is pretty low outside of specialist outlets like, say, Ars.
Kind of true. Check the law proposals on encryption around the world…
Technology is difficult, most people don’t understand it, result is awful laws. AI is even more difficult, because even creators don’t fully understand it (see emergent behaviors, i.e. capabilities that no one expected).
Computers luckily are much easier. A random teenager knows how to build one, and what it can do. But you are right, many are not yet ready even for computers
Probably all articles I have read on it by mainstream media were somehow wrong. It often feels like reading a political journalist discussing about quantum mechanics.
Yeah, I view science/tech articles from sources without a tech background this way too. I expected more from this source given that it’s literally MIT Tech Review, much as I’d expect more from other tech/science-focused sources, albeit I’m aware those require scrutiny just as well (e.g. Popular Science, Nature, etc. have spotty records from what I gather).
Also regarding your last point, I’m increasingly convinced AI creators’ (or at least their business execs/spokespeople) are trying to have their cake and eat it too in terms of how much they claim to not know/understand how their creations work while also promoting how effective it is. On one hand, they genuinely don’t understand some of the results, but on the other, they do know enough of how it works to have an idea of how/why those results came about, however it’s to their advantage to pretend they don’t insofar as it may mitigate their liability/responsibility should the results lead to collateral damage/legal issues.
who illegally stole GPLv3 code from an open source program called DiffusionBee for his proprietary Glaze software (reddit link), and when pressed, only released the code for the “front end” while still being in violation of GPL?
Oh, how I wish the FSF had more of their act together nowadays and were more like the EFF or ACLU.
You should check out the decompilation they did on Glaze too, apparently it’s hard coded to throw out a fake error upon detecting being ran on an A100 as some sort of anti-adversarial training measure.
That’s hilarious, given that if these tools become remotely popular the users of the tools will provide enough adversarial data for the training to overcome them all by itself, so there’s little reason to anyone with access to A100’s to bother trying - they’ll either be a minor nuisance used a by a tiny number of people, or be self-defeating.
This is cool. I think generative AI is great, but the way it’s being trained right now largely without consent from the artists or subjects is unequivocally unethical. Until the law catches up with the technology, people need ways of protecting themselves.
Until the law catches up with the technology, people need ways of protecting themselves.
I agree, and I wonder if the law might be kicked into catching up quicker as more companies try to adopt these tools and inadvertently infringe on other companies’ copyrighted material. 😅
I don’t see how AI training couldn’t be considered transformative as the whole idea is to consume input, break it down into data, and output something new. The way I’m understanding what you’re saying is like this: Instead of only paying royalties when I try to monetize a cover song, I’d have to pay every time I practiced it.
I don’t understand how you’re separating the the generated artworks from the AI that’s generating the work, but I do see your point. If a company puts out a tool for free I don’t think they should be on the hook for someone using that and creating a product. At the end of it all though, I think whoever has made any hard financial gains should should payout whoever contributed.
How is training AI with art on the web different to a person studying art styles? I’d say if the AI is being monetized in some capacity, then sure maybe there should be laws in place. I’m just hard-pressed to believe that anyone can have sole control of anything once it gets on the Internet.
The real issue comes in ownership of the AI models and the vast amount of labor involved in the training data. It’s taking what is probably hundreds of thousands of hours of labor in the form of art and converting it into a proprietary machine, all without compensating the artists involved. Whether you can make a comparison to a human studying art is irrelevant, because a corporation can’t own an artist, but they can own an AI and not have to pay it.
Human brains clearly work differently than AI, how is this even a question?
It’s not all that clear that those differences are qualitatively meaningful, but that is irrelevant to the question they asked, so this is entirely a strawman.
Why does the way AI vs. the brain learn make training AI with art make it different to a person studying art styles? Both learn to generalise features that allows them to reproduce them. Both can do so without copying specific source material.
The term “learning” in machine learning is mainly a metaphor.
How do the way they learn differ from how humans learn? They generalise. They form “world models” of how information relates. They extrapolate.
Also, laws are written with a practical purpose in mind - they are not some universal, purely philosophical construct and never have been.
This is the only uncontroversial part of your answer. The main reason why courts will treat human and AI actions different is simply that they are not human. It will for the foreseeable future have little to do whether the processes are similar enough to how humans do it.
Now you’re just cherry picking some surface-level similarities.
You can see the difference in the process in the results, for example in how some generated pictures will contain something like a signature in the corner, simply because it resembles the training data - even though there is no meaning to it. Or how it is at least possible to get the model to output something extremely close to the training data - gizmodo.com/ai-art-generators-ai-copyright-stable….
That at least proves that the process is quite different to the process of human learning.
The question is how much those differences matter, and which similarities you want to focus on.
Human learning is similar in some ways, but greatly differs in other ways.
The fact that you’re picking and choosing which similarities matter and which don’t is just your arbitrary choice.
You can see the difference in the process in the results, for example in how some generated pictures will contain something like a signature in the corner
If you were to train human children on an endless series of pictures with signatures in the corner, do you seriously think they’d not emulate signatures in the corner?
If you think that, you haven’t seen many children’s drawings, because children also often pick up that it’s normal to put something in the corner, despite the fact that to children pictures with signatures is a tiny proportion of visual input.
Or how it is at least possible to get the model to output something extremely close to the training data
People also mimic. We often explicitly learn to mimic - e.g. I have my sons art folder right here, full of examples of him being explicitly taught to make direct copies as a means to learn technique.
We just don’t have very good memory. This is an argument for a difference in ability to retain and reproduce inputs, not an argument for a difference in methods.
And again, this is a strawman. It doesn’t even begin to try to answer the questions I asked, or the one raised by the person you first responded to.
That at least proves that the process is quite different to the process of human learning.
Neither of those really suggests that all (that diffusion is different to humans learn to generalize images is likely true, what you’ve described does not provide even the start of any evidence of that), but again that is a strawman.
There was no claim they work the same. The question raised was how the way they’re trained is different from how a human learns styles.
I agree that the training isn’t fundamentally different, but that monetization of the output has to be controlled. The big difference between AI and humans is the speed with which they create - you have to employ an army of humans to match the output of a couple of GPUs. For noncommercial projects this is amazing. For commercial projects, it destroys the artists livelihoods.
But this simply means that training shouldn’t be controlled, inference in commercial contexts should be.
I work in AI and I believe it is different. Society is built to distribute wealth, so that everyone can live a decent life. People and AI should be treated differently in front of the law. Also, non-commercial, open source AI should be treated differently than commercial or closed source models
To me, that’s not an argument for regulating AI, though, because most regulation we can come up with will benefit those with deep enough pockets to buy themselves out of the problem, while solving nothing.
E.g. as I’ve pointed out in other debates like this, Getty Images has a market cap of <$2bn. OpenAI may have had a valuation in the $90bn range. Google, MS, Adobe all also have shares prices that would trivially allow them to purchase someone like Getty to get ownership of a large training set of photos. Adobe already has rights to a huge selection via their own stock service.
Bertelsmann owns Penguin Random-House and a range ofter publishing subsidiaries. It’s market cap is around 15 billion Euro. Also well within price for a large AI contender to buy to be able to insert clauses about AI rights. (You think authors will refuse to accept that? All but the top sellers will generally be unable to afford to turn down a publishing deal, especially if it’s sugar-coated enough, but they also sit on a shit-ton of works where the source text is out-of-copyright but they own the right to the translations outright as works-for-hire)
That’s before considering simply hiring a bunch of writers and artists to produce data for hire.
So any regulation you put in place to limit the use of copyrighted works only creates a “tax” effectively.
E.g. OpenAI might not be able to copy artist X’s images, but they’ll be able to hire artist Y on the cheap to churn out art in artist X’s style for hire, and then train on that. They might not be able to use author Z’s work, but they can hire a bunch of hungry writers (published books sells ca 200 copies on average; the average full time author in the UK earns below minimum wage from their writing) as a content farm.
The net result for most creators will be the same.
Even wonder why Sam Altmann of OpenAI has been lobbying about the dangers of AI? This is why. And its just the start. As soon as these companies have enough capital to buy themselves access for data, regulations preventing training on copyrighted data will be them pulling up the drawbridge and making it cost-prohibitive for people to build open, publicly accessible models in ways that can be legally used.
And in doing so they’ll effectively get to charge an “AI tax” on everyone else.
If we’re going to protect artists, we’d be far better off finding other ways of compensating them for the effects, not least because it will actually provide them some protection.
UBI is needed because most of the jobs people are currently doing are already not needed. They are needed just to redistribute wealth, but most of the jobs are currently already useless (if you work in corporate, public sector or retail you know what I am talking about). In the future more will become useless. Current copyright laws are already outdated and don’t work anymore. Only safe solution for people who want to dedicate their lives to visual art is UBI. Because of the known reasons. Most “artists” are not really doing art, simply a job for entertainment industry that in the future will be done by much fewer people due to technological and organizational changes. As it is already happening now, even before AI.
UBI is a solution for similar situations, that will be even more common in future. We need better solutions to redistribute wealth, from what you call “power brokers” to larger society
I don’t see a problem with it training on all materials, fuck copyright. I see the problem in it infringing on everyone’s copyright and then being proprietary, monetized bullshit.
If it trains on an open dataset, it must be completely and fully open. Everything else is peak capitalism.
Of course not, it’s the artists decision to put it on the internet for free.
Technically that’s the root of the issue. This does not grant a license to everyone who looks at it, but if a license is required to train a model is unclear and currently discussed in court.
The problem is the only way for artists to get people to see and eventually buy their art or commissions is to post some of their work publicly. Historically you would go out on the street and set up a stall, now social media is our digital street. Galleries don’t take everyone, having the ability to even get a meeting with one is difficult without the right connections. Most artists are never successful enough to completely live off their art, if they can make any money at all it is great for them. Then along comes an AI model that takes their work because it’s on the internet scrapes it into its training set and now any chance they had in an over saturated market is even smaller, because hey, I can just do this with AI. This idea that copyright and IP shouldn’t exist at all is kinda absurd. Would you just go through a street art walk, take high res photos of every picture they have on display, not take any business cards, and when they ask what you are doing, go “it’s ok, I’m training an AI data model so people can just make work that looks exactly like this. They shouldn’t have to ever buy from you. Capitalism is a joke. Bye!” The art walk was free, but it was also a sales pitch, because that’s how the art world works. You are hoping to get seen, that someone likes it enough to buy, and maybe buy more.
This idea that copyright and IP shouldn’t exist at all is kinda absurd
I don’t hold this opinion at all.
I’m just saying that there are uses for which you don’t need a license. Say, visiting an art exhibition and then going home and trying to draw similar pictures. Wether AI training falls into this category or instead requires a license is currently unclear.
Btw, two spaces before the line break
Creates the spacing you want.
As an artist who studies data science, I would say doing art and generating art are an entirely different process. AI has no reference outside of the information we give it. It had no real understanding of lighting, spacial awareness. We can tell it every tank is a cat, every flashlight is a pig and it will never question it. If we tell a toddler that every tank is a cat, they may call a tank a cat, but they will never think a that “cat” is a house pet. They will never think that “pig” will oink or be turned into steaks. An AI however would if your language conventions were the same in the prompt.
If you go to the art walk and go home and try to recreate a style, you were inspired. If an AI model is trained on many styles and you tell it “portrait, woman, Van Gogh style, painterly, blue tones” then do you understand what you asked for? Was the ai inspired by Van Gogh? Did the ai study his techniques? No. It broke down his art pixel by pixel, rearranged it in a filter styled overlay over a woman, most likely a young woman-because of algorithmic bias which has been studied- in shades of blue. Humans take the time to study the why, the how. Ai does not. Humans are not just meat robots.
I should say I’m not against AI art. I’m against gathering against consent. If it was opt in, or if there was some type of pay for program that would be fine. Even if it was pennies each month. But the fact that they scrape without consent. Or are now going back and adding it into TOS where it never was before feels scummy. AI art has a place, and is a helpful tool. But it’s not a replacement for artists, it has many flaws still, that might never be worked out.
This idea that copyright and IP shouldn’t exist at all is kinda absurd.
For the majority of human existence, that was the default.
Copyright exists as an explicit tradeoff between the rights of the public to be able to do as they please with stuff introduced into the public sphere, and a legal limitation infringing on the publics liberty for a limited time for the purpose of encouraging the creation of more works for the public benefit. It was not introduced as some sort of inherent right, but as a trade between the public and creators to incentivise them.
Stripping it away from existing artists who has come to depend on it without some alternative would be grossly unfair, but there’s nothing absurd about wanting to change the bargain over time. After all, that has been done many times, and the copyright we have now is vastly different and far more expansive and lengthy than early copyright protection.
Personally, I’d be in favour of finding alternative means of supporting creators and stripping back copyright as a tradeoff. The vast majority of creators earn next to nothing from their works; only a very tiny minority makes a livable wage of art of any form at all, and of the rest the vast majority of profits take place in a very short period of initial exploitation of a work, so we could allow the vast majority to earn more from their art relatively cheaply, and affect the rest to a relatively limited degree, while benefiting from the reduced restrictions.
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.
If you work on commission only online, or never went to art school those won’t cover you.
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.
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.
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.
I don’t see these grants or public funding ever covering a private company for one.
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.
And for two, I don’t see AI art ever actually getting to the point where it fully replaces artists.
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.
Because it is trained to make a homogeneous rendering of what you are looking for
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.
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.
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.
There is also this idea that people wouldn’t willing contribute if just asked.
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.
So what you are saying is open ai should get the public grants for artists to give to artists?
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.
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.
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 still isn’t good enough to be competitive.
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.
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.
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.
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.
If I thought that, I wouldn’t have emphasised the need to sort out the funding issue, and argued that just regulation will be insufficient to solve it.
I think it will cause a massive degree of upheaval. I don’t think regulation has any hope in hell of preventing upheaval significant enough that unless a solution is found to ensure better distribution of wealth it will cause violence and uprisings and governments to fall. Not necessarily in and of itself, but in accelerating a process of reducing the monetary value of labour.
I can’t know anything about LLMs, machine learning or anything about this.
I’ve not suggested anything of the sort.
How you can interpret anything I’ve written as suggesting I don’t think there will be problems is beyond me.
You therefore throw out the idea that bias exists due to tagging systems.
I am perfectly entitled to type random stuff into google images, pick out images for a mood board and some as reference, regardless of their copyright status, thank you. Studying is not infringement.
It’s what every artist does, it’s perfectly legal, and what those models do is actually even less infringing because they’re not directly looking at your picture of a giraffe and my picture of a zebra when drawing a zebra-striped giraffe, they’re doing it from memory.
And if you think that working with AI does not take effort you either did not try, or don’t have an artistic bone in your body. Randos typing “Woman with huge bazingas” into an UI and hitting generate don’t get copyright on the output, rightly so: Not just did they not do anything artistic, they also overlook all the issues with whatever gets generated because they lack the trained eye of an artist.
This whole thing is basically a nonstory when you realize how much money is in tech. Meta changed their name and sank billions on an idea that everyone thought was stupid from the beginning, and they’re still fine.
Putting a billion into the flavor-of-the-month that has like 10% chance to be the next big thing is a no-brainer when you’re printing multiple billions in profit doing nothing, and have a lot more cash on hand.
The real story, is how wealth inequality and monopolies have essentially allowed the rich to waste tons of money chasing more wealth while having almost no incentive to provide value to society. Who gives a fuck about hallucination and prompt injection? It’s all trivial details that VCs are giving away billions to eventually solve.
This parallels the height of GM, when they put money in everything from satellites to ATMs. Sure, at the time there was plenty of money to dump on such ventures. But eventually, those bad bets caught up to them. It seemed like a "no big deal" when a hugely profitable company wasted billions of dollars on bad investments. But each one of those bad investments represented a lost opportunity for a good investment. Eventually, the cash cow at GM ended, and the company is left with nothing but huge debts and worthless investments. Any tech company that is just buying the equivalence of lottery tickets is probably destined for failure too, no matter how profitable it is right now.
Sad to see the right wing libertarian political compass being used as some sort of factual scoreboard in research like that. It completely undermines the premise of that research.
This isn’t new. Check out Yasha Levine’s . It’s a nice primer. Most of our internet tech was built for the military or funded by the military for military ideas (no matter what MIT or Berkeley theoreticians might try to convince you of).
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