• they/them...for now

weird depressed person trying to make a game? actually not sure. yeah i should probably more thoroughly interrogate my appreciation of the referenced video game character


arborelia
@arborelia

I think I'm taking a risk writing this post, because unfortunately it's going to involve nuance. I want you to know up front, I'm probably on the same side of the issue as you. I think generative AI in the 2020s is destroying the public sphere and we need to do a lot of different things to stop it.

If you end up reading this post and thinking that I'm making a slippery-slope argument that says generative AI is inevitable and you should give up and let it take over our culture, please back up and read this. Holy shit no I am not saying anything like that. I do not think we should give up. I think we should target it, say what's bad about it, and stop it.

The thing that's been bouncing around my mind is that, if you take such a hard-line position that you want to "ban AI" without being able to say what you mean by that, you are not going to be effective enough at opposing it. I understand taking a nuance-free position as a tactic, especially if your position is that "well I don't understand this and I shouldn't have to understand this, I just know it's bad", but I don't think that works as the only tactic.

Here's the outline of what I mean:

  • The definition of AI is constantly changing
  • Many AI techniques in the past have been normalized to the point where it sounds really silly to call them "AI"
  • If today's generative AI follows that trend and gets normalized, that would be a problem, even though this sounds like recency bias
  • Something changed in the 2020s that made generative AI more dangerous and insidious, and if we pin down what changed, we will be able to oppose it better. There were warning signs before, but the call to action is now.

I don't want this to be a cohost meta post. I know things about AI and its history. I don't know things about how to run a web site. Even though the cohost meta is why I've been thinking about it, please don't ask me to turn this into a strong recommendation about how to run a web site.

Some background on me: I wrote an often-quoted post in 2017 warning about how the default state of AI training, the thing you get when you implement it exactly like the textbook says, is to be racist. Many people thought before that that "whoops, AI turned racist" was just a wacky thing that happened to Microsoft Tay and wouldn't happen to them. I also wrote a follow-up post about how Google's "Perspective AI", which they promoted as the default way to moderate a web site instead of having humans do it, was exactly the kind of racist-by-default implementation I described. I used to run an AI system called ConceptNet. I don't think it changed the world, and my proudest thing about ConceptNet is the silly bots and games that people made with it. I don't work in the AI industry anymore.

Things that used to be AI

Anyway. Perhaps you want AI to go away. You want there to be no more AI-generated posts and you want to shun, or possibly ban from a community, anyone who posts them. Does this mean you want to disallow:

  • Commentary on a chess game with the strategic value of moves annotated
  • Photos taken with a phone camera
  • Posts written with assistive speech-to-text
  • Google Maps directions
  • Posts written using spell check
  • Posts typed or swiped on a phone's on-screen keyboard

I don't think you mean those. And now there's a chance you're upset, because what the hell, those clearly aren't AI, why would I even bring them up unless I'm trying to obfuscate an important issue?

They used to be AI!

Phone cameras use AI image recognition to make photos sharper than the lens can actually support, and make human faces prettier. The iPhone propagated it first. A blogger who wrote about the statistics of online dating noticed that iPhone users got laid more. Android phones had to make a big push to catch up, around the time of the Pixel 3.

One of the pitches my research group made for the technology we were working on, in grad school, was that you'd be able to do better T9 texting on your phone, because the AI system could understand what words you were likely to mean, not just what words are in the dictionary. It's amusingly short-sighted in retrospect that we were just talking about T9.

Giving directions on a map was the first major assignment in undergraduate AI class in the '00s.

Spell check was considered AI when it was first developed. It is an example in the 2nd and 3rd edition of the most definitive AI textbook, Russell and Norvig.

Playing chess well was absolutely AI, and I don't just mean in the non-overlapping magisteria of "game AI". In the '70s, people believed that a computer that could win at chess would have proved its intelligence. It was a topic of mainstream AI discourse in the '90s when Deep Blue beat Kasparov (not through any new techniques, just by computing more things faster). The current chess engines include techniques that came from generative AI, even though the most they generate is strategic lines of chess moves.

And fairly recently, the thing people thought of when they thought of AI was a pattern-matching voice assistant like Siri or Alexa. (Amazingly, these things that used to kind of work have been invaded by modern generative AI to the point where they don't work anymore, they just fake it the way any generative model does.)

The easy position to take would be to say "well, everyone who called those things AI was wrong. ChatGPT and Stable Diffusion are AI, and those older things weren't." I'll caution you: if you take that position, you are taking the same position as AI-promoting techbros. They don't think old AI was AI either! They think they invented AI in the 2020s! "None of that previous junk was AI, we're finally making real AI" is part of their bullshit sales pitch!

By denying that anything that happened in the 2010s or earlier is "real AI", the AI promoters can dismiss all the previous concerns like the ones I wrote about. Moreover, they can dismiss Timnit Gebru, Emily Bender and Margaret Mitchell. They were just writing about silly computer toys in the bad old days, they say, and nothing they say has any relevance to "real AI", which happens to have all been created after three influential women were run out of the industry for raising the alarm.

"Stop quibbling over definitions, I know it when I see it"

Another position you might take on harmful generative AI is the old canard about pornography: "I know it when I see it."

In 5-10 years, there is a chance that you won't know it when you see it. I'm not saying this is inevitable, and in fact it's dystopian as fuck, but I'm saying it's possible enough to be worried about. Our cultural memory about technology such as AI is so short.

Warning: dystopian speculation

In 2030 the generative AI discourse may still be going on, and you'll say, look, the problem is clearly with this generative AI app that generates VR porn of your crush. Clearly it's not just about generating text or images. Those aren't AI, everyone does that, how could you even write anything without it.

In 2035 it may be, look, the problem is with the robots that brutalize protesters and striking workers, clearly the problem isn't the VR porn app that everyone has, why would you waste your breath on a silly old thing like that.

If AI stops being "AI" the moment it's half a decade old, then all the concerns with current AI can be dismissed and swept under the rug just by the passage of time. Nonspecific calls to ban generative AI can be completely neutered by making a technique so common that it's not called AI anymore. You do not want let them run out the clock, and you really don't want to reward making the bad thing common.

This dystopia is not inevitable. I think defining the problem is part of stopping it.

2020s AI is not just the natural progression of technology

I'm glad you get here, because here's the part where I make the point that I'm risking all this nuance to make. There is a noticeable change in the generative AI technologies that are currently ruining the world, and if we can describe what changed, we can describe how to oppose them.

Here are things that changed:

  • Training data was collected with the clear non-consent of its subjects. In 2010, if you heard an AI was being trained to understand language based on something you wrote, your reaction might be "huh, neat", or maybe "what?". In 2024, your reaction is probably "FUCK NO, I did not agree to this, make it stop", and there's a good reason for it, because we've seen what they intend to do with that trained AI.

  • Users do not want the technology. When AI was a phone camera that made you sexier, people wanted it. When it let people accomplish tasks with their voice, they wanted it. For the most part, people do not want the generative AI slop that's being shoved into everything. Most people do not want to read authoritative-sounding lies instead of search results, see art with no artist, listen to pop music sludge made by nobody, or talk to a fake phone agent that is not capable of understanding anything. Companies keep putting AI into products even though it makes customers distrust the product. They are fighting a battle to normalize this decade's generative AI that they are not certain to win.

(As an exception, a sizable minority of people like and trust ChatGPT. I have no idea why. I hope we can pop that bubble.)

  • They are fighting against a resurgent labor movement. Bosses are so determined to put AI into everything, at all costs, because they need to undermine the power that workers have. They are scared and they need to be more scared.

  • They are fighting against the joys of being human. The message of AI has largely shifted from "this will improve your life and give you more for leisure and creativity" to "you'll have to use this no matter what, and your leisure and creativity are obsolete". And we can hear them. Unlike the prior history of AI, ordinary people can see how much it sucks, how they want to put our interests in a blender and make a gray sludge out of them, how they want to make a machine draw for them because they won't even put in the effort to learn to draw. We are now all Hayao Miyazaki, who was shown an early generative AI and said "I strongly feel this is an insult to life itself".

  • The theft and plagiarism is obvious now. Large-scale scraping of training data can no longer be written off as "oh, it's just an AI experiment, it doesn't matter." We know it does matter. This has put us, unusually, on the same side as massive copyright holders like Getty Images and music labels. A strong interpretation of copyright is an uncomfortable tool to fight AI, but it's a tool we can use.

  • The energy use is unsustainable. These large generative AIs don't run on normal computers using normal amounts of power. They're unsustainable for the environment, and also unsustainable for the companies to be able to afford what they're doing. OpenAI loses money on every interaction even though they don't have to pay for their externalities. They shouldn't be able to do this forever.

What I am advocating for

I'm sure many of these suggestions are going to be obvious. I still want to suggest them. It's important to have targeted ways to resist generative AI.

  • Unionize. This is the best tool we have. Capital owners want to replace creative workers with AI slop using the work those workers did, and the workers who are able to stop this are the ones who are unionized. A line we can draw against the AI boosters is: "You can't use our work to do this. Go do the work yourself." And they won't do the work themselves because they don't know how to do work.

  • Make modern generative AI unwelcome in your communities, for these reasons. Not just because it's "AI" which has always been a squishy word for "things computers can't quite do yet", but because it's fucking fake, stolen and dehumanizing. Messing around and making computers do new things isn't the problem. The huge capitalist pressure to make all available computing power do one thing that most people don't want is the problem.

  • Support and celebrate the imperfections of being human. Every time you correct someone's grammar, there's a risk that they turn to ChatGPT to write for them next time. Support weird unprofessional writing. Support art that is poorly drawn in a human way. Support imperfect music made by real people with a tune in their heart.

  • Demand sources. Demand credit. Even if someone labels something as generative AI, they ought to be challenged on what their sources are, whose words are being used without credit, whose art is being collaged together. Of course they'll give stupid answers and credit products as if they were people, but stay firm and don't accept those answers. "Stable Diffusion didn't make the thing, Stable Diffusion is the machine you used to steal the thing, so who is it stolen from? Who are the recording artists who made the sounds that Suno is making? Oh, you don't know, is it because you plagiarized it?" Do not let up on this. The problem is not something as banal as copyright, it's that they are taking credit for something they didn't make, or assigning that credit to their imaginary corporate friend.

  • Make the companies pay for environmental harm. Just like cryptocurrency before them, the large generative AI companies are benefiting from unnaturally cheap electrical power, and political action can change this. Environmental action is slow and frustrating, but it's at least one avenue of attack. They should be paying for their externalities.

  • Destroy Google. Okay, I don't have a specific plan for how to do this, but it would sure help.

  • Oh and of course mercilessly mock the people who distract from the real problems by making up a sci-fi AGI god. But we've been able to mock them for a long time, since long before generative AI was the present danger it is now.

Keep AI weird?

As a minor point, I think it can be good to celebrate weird, low-power, niche experiments that cannot imitate a human and are not trying to, like in the '10s when we used things like Deep Dream and GPT-2 to generate uncanny absurdism and posted curated examples of it. "AI" could be taken in a different direction. That kind of stuff is still possible and a single home computer can do it. Turn down the model size, turn up the weird. Put some effort into doing something different so we can skip the racism and sexism and stuff this time.

Even better is the bespoke templated stuff whose model is entirely transparent, like "Cheap Bots Done Quick", Inspirobot, and friends.

Maybe the time of absurdist computer-generated memes is over anyway. Maybe generative AI made them terminally uncool. If so, I won't miss them too much. But they shouldn't be the target, I think.


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in reply to @arborelia's post:

broadly agree, and the point about how many things we all broadly like used to be called "AI" is important. but two things:

  • if your main area of differentiation between today's "AI" and yesterday's "AI" is that right now data is being taken without express permission, that is not a very rock-hard defense. adobe et al (and some music companies, I very strongly suspect) are training models with only data they already own the copyright to. should we accept use of these models freely because nobody's work was "stolen"? well, no. the labor issues with this potential model are exactly the same (they're gonna try to replace people with these) and they're still going to output slop. I don't think this is a useful criteria for what we should accept and what we should reject.

  • you do not want to be on the same side as massive copyright holders. you absolutely do not want copyright to be strengthened to the point where the law alone would actually stop generative AI from being feasible to train. i do not think it is just an "uncomfortable tool in the fight against AI;" it is handing enormous slop-generating companies a cudgel and giving them the opportunity to look like saints for brandishing it. i have spent too much time researching modern music copyright cases to feel any other way about this

These are good points, particularly the one about Adobe.

It was just a couple of months ago when Adobe had the PR crisis over their terms of use, and they tried to reassure people, "we're not feeding your work into generative AI. Except for when we feed Adobe Stock into Adobe Firefly™, our amazing generative AI that is good".

They wanted to draw a line between harmful and harmless generative AI, and they drew it in a really precise place that was advantageous for them.

So how can we draw the line knowing that Adobe is on the wrong side of it, the side that is normalizing turning human art into slop?

I still think it's relevant that the people who contributed to Adobe Stock didn't actually agree to this. I mean, they agreed to some clickwrap terms, not knowing that this would happen, which is not the same as actually consenting to it. In some cases, users uploaded work that wasn't even theirs, sometimes work that was generated by a different generative AI, to Adobe Stock.

This would be a hard legal argument to make against Adobe, but it's still a moral argument.

honestly, i don't think we should draw a line to try to fence out adobe - i think it is cleaner to say "look, these models suck no matter what because they're making material conditions worse for both consumers and workers who are getting their jobs replaced, regardless of how the data is gathered"

also not a legal argument but i think it's a convincing moral one for a lot of people, and definitely galvanizes resistance from labor. this also leaves room for the "weird ai" stuff you mention to exist, and i agree with you that it should exist

nods - I appreciate the original post a lot, but yeah, these were two things that stuck out to me and I'm very glad that you addressed them.

I also get the feeling that some (perhaps not all, but at least some) people who are being mercilessly mocked for "making up sci-fi AI gods" are actually trying to argue something along the lines of the first point - that focusing on copyright is like trying to shoot a moving target, because the models are getting more powerful to the point that they won't need to scrape and steal work to operate anymore. That the models are evolving alarmingly quickly, and that the more powerful they get, the more potential they have for doing harm in ways that we haven't even thought of. I feel like a Terminator-esque robot overlord takeover is probably not the most likely of these possibilities - but it's worth considering if that's what the people in question are actually talking about, or if they're talking about something else, something that is relevant.

TBH, even in a hypothetical world where everyone could be assured of a decent quality of life regardless of their job or lack thereof, I think it would be good to curtail how big and powerful AI can get. Again, not because I think it'll become sapient and decide to nuke everyone, but because the bigger anything is, the more catastrophically it can fuck things up. And the more complex anything is, the more likely it'll fuck things up.

fun tidbit re: Deep Blue/Kasparov, i remember reading that actually the reason why it was able to beat him was that it made an error. it made a chess move that didn't make any sense, and Kasparov overthought it, and made his own error, and the machine took the game. Literally won by mind games.

At this point, i think chess is a solved game at the expense of ~equivalently the power consumption of Ireland, so it doesn't really matter for your point. doubly so because focusing on "the AI wasnt actually as smart as they say" detracts from the issue. but i thought it was funny

Destroy Google. Okay, I don't have a specific plan for how to do this, but it would sure help.

Tariffs and Protectionism. The PRC and the ROK already do it.
Google (and Microsoft) are foreign entities towards which the Central Government already is openly hostile, and it needs to grow the balls to build the public opinion to allow it to break up their IT sector.
The State already fucks with them and puts down other major IT companies, so we know it can do it.

I think a good point of leverage for breaking it is to:

point out the ads antitrust suit they lost,

point out how it's mingling with web search (they showed ads pressured search into giving worse results to show ads),

and then point out that they're doing things that seem like they'd qualify for anti-trust action now with Search: exclusive deal with Reddit regarding scraping and search-indexing pages, preventing alternatives from having equal footing.

under the guise of AI

and that's even something legislators and judges can understand when said that way

The thing that's been bouncing around my mind is that, if you take such a hard-line position that you want to "ban AI" without being able to say what you mean by that, you are not going to be effective enough at opposing it.

I'll go even stronger than this: if you take a hard-line position and want to "ban AI" without defining why it's bad, the opposition will choose things it can knock out as low hanging fruit and pretend they were your reasons.

"look, we got rid of the copyright infringement (now that our model is complete and we have enough money to legitimately pay. lowballing of course )"

"look, it no longer makes porn of your crush (because we banned all '18+' content"

etc

i feel very strongly that IP law should not be considered an "uncomfortable ally", it should be considered a poisoned well. strengthening the power of copyright would not help independent artists or to prevent AI slop from being generated, it would just center all of the power of that on big media corporations who can train their own models and/or copyright their own artstyle.

imagine a world where nintendo can sue every pokémon fanartist ever for "style infringement" on ken sugimori's art. the proposals to try and strengthen copyright by making "art style" a component of IP would do that and it would be devastating.

ai slop isn't great, but strengthening copyright to oppose it would be so, so much worse.

More than that, I think it's extremely shortsighted of any independent artist to assume such a system of "style copyright" would deem them worthy of the copyright to their "own style" or subject matter. Human artistic expression is unique, sure, but it follows patterns and themes. Statistically, someone made a similar piece before you at some point. The only alternative is to claim your artwork is so unique that nobody in history has made anything like it... which is a bit much, I think.

And all of this would be determined by copyright lawyers and such, not people with an appreciation for the arts, so subtleties would be lost.

Heavy sigh, yeah re Google. You can use alternatives for some things, some are easier than others, and some are trading the evilglobocorp1 for evilglobocorp2. My favorite alternative is @fastmail, a seriously fantastic paid email service with better filtering and rules than gmail by a thousand goddamn miles. And it is FAST. So much good to say about fastmail.

The common joke about "AI" when I was a CS undergrad years ago was "if it works reliably it's called an algorithm; if it doesn't, it's called artificial intelligence". The sentiment remains true, but mainstream usage has poisoned the word "algorithm" and more or less inverted its meaning from "a precise step-by-step procedure" into "an opaque and unknowable machine-learning model", so it's not as rhetorically sharp as it once was.

For my own writing, I prefer to use terms like "LLMs" and "GANNs" over "generative AI", because it nails the discussion down to real-world techniques with tangible faults and failure modes (i.e. being completely fucking useless for most purposes) rather than the hypothetical future technologies that enthusiasts like to pitch. It's like public transit via flying car versus trains: the trains have imperfections but exist, and the cars appear perfect (to gullible marks) because they don't exist.

Personally, my own distrust and dislike of AI extends further than the latest wave of generative models. I think the recent developments ought to recolor our opinions on earlier AI tech, even if it seems mundane by now. If I had to try to pin down where to draw the line, it would roughly be at "AI is bad if it's a black-box model that has been trained on a data set" (yes, I'm aware that this casts a VERY wide net).

There may be no putting that genie back in the bottle, but maybe we can get some guardrails. One I'd suggest--that sadly has no chance in hell of coming true even though it feels like common sense to me--is "AI companies are required to publish their training data". A more modest version that miiiight gain acceptance is "AI companies are required to publish their holdout data" (I don't know how to apply that rule to generative models though, just classifiers). Like, can we get the barest amount of accountability -- can a third party audit whether or not your model even does what you claim it does?

I certainly don't mean to come across as saying that older AI systems were morally good. In a lot of cases, they sure aren't. I mentioned the AI moderator "Perspective AI", which is both mundane and evil.

When it comes to requiring companies to publish their data, at least enough to independently audit their system: that would be great. If only. I feel like academic conferences and publications could try to have some leverage here, if they had a spine, but I guess you don't get conferences sponsored by having a spine.

I got very disillusioned with academia when conferences would give talk slots to corporations who would just boast about an AI tool they have and you don't. I was shocked that Google and Microsoft could get away with giving an irreplicable sales pitch, when everyone else was supposed to convey verifiable knowledge.

Totally agree. I classify a wide range of black-box machine learning as essentially professional malpractice. The harm of LLMs and GANNs is not of a fundamentally new and different nature, but the generality of these techniques makes them (mis)applicable on a disturbing new scale.

The burden of proof ought to be on machine learning proponents to demonstrate that their models robustly capture a pattern, but somehow now that LLMs are good at lying convincingly it seems like the public at large expects critics to be able to prove that models don't work correctly without access to any information about how they were made or are operated. Truly absurd.

I hope when you say that stuff about "art being collaged" etc., you're being metaphorical, but I would encourage not using that kind of framing. I've seen people come to the mistaken conclusion that image generation literally works by storing images, digitally cutting them up, and pasting them together, such that the original image could be plucked out of the source code like an asset in a video game.

While I agree that the provenance of datasets is important (e.g. the LAION 5B dataset includes nonconsensual sensitive medical records, which I think on its own is reason not to use it), I believe misrepresenting the function of the technology undermines one's point.

Optimizing a similarity function to an existing image is a form of copying that image, even if the design can't land on an exact copy of anything and obfuscates which images are involved.

I experimented briefly with one of the web-based DALL-E implementations (the one they renamed to "Craiyon" because its results were shitty enough to be bad for their DALL-E brand). I asked it for something like "Billy Joel with bottles of malt liquor taped to his hands" (because the phrase "Billy Joel Forty-hands" had come up in conversation for some reason, and I probably would have gotten something more literal and eldritch if I asked for it in that form).

The image I got largely consisted of both album covers for "The Essential Billy Joel" and a Wikimedia Commons image for "bottle".

What changed since then is mostly a matter of how many compressed images it's approximating similarity to.