This started as a summary of a random essay Robert Epstein (fuck, that's an unfortunate surname) cooked up back in 2016, and evolved into a diatribe about how the AI bubble affects how we think of human cognition.

This is probably a bit outside awful's wheelhouse, but hey, this is MoreWrite.

The TL;DR

The general article concerns two major metaphors for human intelligence:

• The information processing (IP) metaphor, which views the brain as some form of computer (implicitly a classical one, though you could probably cram a quantum computer into that metaphor too)
• The anti-representational metaphor, which views the brain as a living organism, which constantly changes in response to experiences and stimuli, and which contains jack shit in the way of any computer-like components (memory, processors, algorithms, etcetera)

Epstein's general view is, if the title didn't tip you off, firmly on the anti-rep metaphor's side, dismissing IP as "not even slightly valid" and openly arguing for dumping it straight into the dustbin of history.

His main major piece of evidence for this is a basic experiment, where he has a student draw two images of dollar bills - one from memory, and one with a real dollar bill as reference - and compare the two.

Unsurprisingly, the image made with a reference blows the image from memory out of the water every time, which Epstein uses to argue against any notion of the image of a dollar bill (or anything else, for that matter) being stored in one's brain like data in a hard drive.

Instead, he argues that the student making the image had re-experienced seeing the bill when drawing it from memory, with their ability to do so having come because their brain had changed at the sight of many a dollar bill up to this point to enable them to do it.

Another piece of evidence he brings up is a 1995 paper from Science by Michael McBeath regarding baseballers catching fly balls. Where the IP metaphor reportedly suggests the player roughly calculates the ball's flight path with estimates of several variables ("the force of the impact, the angle of the trajectory, that kind of thing"), the anti-rep metaphor (given by McBeath) simply suggests the player catches them by moving in a manner which keeps the ball, home plate and the surroundings in a constant visual relationship with each other.

The final piece I could glean from this is a report in Scientific American about the Human Brain Project (HBP), a $1.3 billion project launched by the EU in 2013, made with the goal of simulating the entire human brain on a supercomputer. Said project went on to become a "brain wreck" less than two years in (and eight years before its 2023 deadline) - a "brain wreck" Epstein implicitly blames on the whole thing being guided by the IP metaphor.

Said "brain wreck" is a good place to cap this section off - the essay is something I recommend reading for yourself (even if I do feel its arguments aren't particularly strong), and its not really the main focus of this little ramblefest. Anyways, onto my personal thoughts.

Some Personal Thoughts

Personally, I suspect the AI bubble's made the public a lot less receptive to the IP metaphor these days, for a few reasons:

1. Articial Idiocy

The entire bubble was sold as a path to computers with human-like, if not godlike intelligence - artificial thinkers smarter than the best human geniuses, art generators better than the best human virtuosos, et cetera. Hell, the AIs at the centre of this bubble are running on neural networks, whose functioning is based on our current understanding of

What we instead got was Google telling us to eat rocks and put glue in pizza, chatbots hallucinating everything under the fucking sun, and art generators drowning the entire fucking internet in pure unfiltered slop, identifiable in the uniquely AI-like errors it makes. And all whilst burning through truly unholy amounts of power and receiving frankly embarrassing levels of hype in the process.

(Quick sidenote: Even a local model running on some rando's GPU is a power-hog compared to what its trying to imitate - digging around online indicates your brain uses only 20 watts of power to do what it does.)

With the parade of artificial stupidity the bubble's given us, I wouldn't fault anyone for coming to believe the brain isn't like a computer at all.

2. Inhuman Learning

Additionally, AI bros have repeatedly and incessantly claimed that AIs are creative and that they learn like humans, usually in response to complaints about the Biblical amounts of art stolen for AI datasets.

Said claims are, of course, flat-out bullshit - last I checked, human artists only need a few references to actually produce something good and original, whilst your average LLM will produce nothing but slop no matter how many terabytes upon terabytes of data you throw at its dataset.

This all arguably falls under the "Artificial Idiocy" heading, but it felt necessary to point out - these things lack the creativity or learning capabilities of humans, and I wouldn't blame anyone for taking that to mean that brains are uniquely unlike computers.

3. Eau de Tech Asshole

Given how much public resentment the AI bubble has built towards the tech industry (which I covered in my previous post), my gut instinct's telling me that the IP metaphor is also starting to be viewed in a harsher, more "tech asshole-ish" light - not just merely a reductive/incorrect view on human cognition, but as a sign you put tech over human lives, or don't see other people as human.

Of course, AI providing a general parade of the absolute worst scumbaggery we know (with Mira Murati being an anti-artist scumbag and Sam Altman being a general creep as the biggest examples) is probably helping that fact, alongside all the active attempts by AI bros to mimic real artists (exhibit A, exhibit B).

Whilst going through MAIHT3K's backlog, I ended up running across a neat little article theorising on the possible aftermath which left me wondering precisely what the main "residue", so to speak, would be.

The TL;DR:

To cut a long story far too short, Alex, the writer, theorised the bubble would leave a "sticky residue" in the aftermath, "coating creative industries with a thick, sooty grime of an industry which grew expansively, without pausing to think about who would be caught in the blast radius" and killing or imperilling a lot of artists' jobs in the process - all whilst producing metric assloads of emissions and pushing humanity closer to the apocalypse.

My Thoughts

Personally, whilst I can see Alex's point, I think the main residue from this bubble is going to be large-scale resentment of the tech industry, for three main reasons:

1. AI Is Shafting Everyone

Its not just artists who have been pissed off at AI fucking up their jobs, whether freelance or corporate - as Upwork, of all places, has noted in their research, pretty much anyone working right now is getting the shaft:

• Nearly half (47%) of workers using AI say they have no idea how to achieve the productivity gains their employers expect

• Over three in four (77%) say AI tools have decreased their productivity and added to their workload in at least one way

• Seventy-one percent are burned out and nearly two-thirds (65%) report struggling with increasing employer demands

• Women (74%) report feeling more burned out than do men (68%)

• 1 in 3 employees say they will likely quit their jobs in the next six months because they are burned out or overworked (emphasis mine)

Baldur Bjarnason put it better than me when commenting on these results:

> It’s quite unusual for a study like this on a new office tool, roughly two years after that tool—ChatGPT—exploded into people’s workplaces, to return such a resoundingly negative sentiment. > > But it fits with the studies on the actual functionality of said tool: the incredibly common and hard to fix errors, the biases, the general low quality of the output, and the often stated expectation from management that it’s a magic fix for the organisational catastrophe that is the mass layoff fad. > > Marketing-funded research of the kind that Upwork does usually prevents these kind of results by finessing the questions. They simply do not directly ask questions that might have answers they don’t like. > > That they didn’t this time means they really, really did believe that “AI” is a magic productivity tool and weren’t prepared for even the possibility that it might be harmful.

Speaking of the general low-quality output:

2. The AI Slop-Nami

The Internet has been flooded with AI-generated garbage. Fucking FLOODED.

Doesn't matter where you go - Google, DeviantArt, Amazon, Facebook, Etsy, Instagram, YouTube, Sports Illustrated, fucking 99% of the Internet is polluted with it.

Unsurprisingly, this utter flood of unfiltered unmitigated endless trash has sent AI's public perception straight down the fucking toilet, to the point of spawning an entire counter-movement against the fucking thing.

Whether it be Glaze and Nightshade directly sabotaging datasets, "Made with Human Intelligence" and "Not By AI" badges proudly proclaiming human-done production or Cara blowing up by offering a safe harbour from AI, its clear there's a lot of people out there who want abso-fucking-lutely nothing to do with AI in any sense of the word as a result of this slop-nami.

3. The Monstrous Assholes In AI

On top of this little slop-nami, those leading the charge of this bubble have been generally godawful human beings. Here's a quick highlight reel:

• Microsoft’s AI boss thinks it’s perfectly okay to steal content if it’s on the open web - it was already a safe bet anyone working in AI thought that considering they stole from literally everyone, whether large or small, but its nice for someone to spell it out like that.

• The death of robots.txt - OpenAI publicly ignored it, Perplexity lied about their user agent to deceive it, and Anthropic spammed crawlers to sidestep it. Results were predictable. Mostly.

• Mira Murati saying "some creative jobs shouldn't exist" - Ed Zitron called this "a declaration of war against creative labor" when talking to Business Insider, which sums this up better than I ever could.

• Sam Altman's Tangle with Her - Misunderstanding the basic message? Check. Bullying a dragon (to quote TV Tropes)? Check. Embarassing your own company? Check. Being a creepy-ass motherfucker? Fucking check.

• "Can Artificial Intelligence Speak for Incapacitated Patients at the End of Life?" - I'll let Amy and David speak for me on this because WHAT THE FUCK.

I'm definitely missing a lot, but I think this sampler gives you a good gist of the kind of soulless ghouls who have been forcing this entire fucking AI bubble upon us all.

Eau de Tech Asshole

There are many things I can't say for sure about the AI bubble - when it will burst, how long and harsh the next AI/tech winter will be, what new tech bubble will pop up in its place (if any), etcetera.

One thing I feel I can say for sure, however, is that the AI bubble and its myriad harms will leave a lasting stigma on the tech industry once it finally bursts.

Already, it seems AI has a pretty hefty stigma around it - as Baldur Bjaranason noted when talking about when discussing AI's sentiment disconnect between tech and the public:

> To many, “AI” seems to have become a tech asshole signifier: the “tech asshole” is a person who works in tech, only cares about bullshit tech trends, and doesn’t care about the larger consequences of their work or their industry. Or, even worse, aspires to become a person who gets rich from working in a harmful industry. > > For example, my sister helps manage a book store as a day job. They hire a lot of teenagers as summer employees and at least those teens use “he’s a big fan of AI” as a red flag. (Obviously a book store is a biased sample. The ones that seek out a book store summer job are generally going to be good kids.) > > I don’t think I’ve experienced a sentiment disconnect this massive in tech before, even during the dot-com bubble.

On another front, there's the cultural reevaluation of the Luddites - once brushed off as naught but rejectors of progress, they are now coming to be viewed as folk heroes in a sense, fighting against misuse of technology to disempower and oppress, rather than technology as a whole.

There's also the rather recent SAG-AFTRA strike which kicked off just under a year after the previous one, and was started for similar reasons - to protect those working in the games industry from being shafted by AI like so many other people.

With how the tech industry was responsible for creating this bubble at every stage - research, development, deployment, the whole nine yards - it is all but guaranteed they will shoulder the blame for all that its unleashed. Whatever happens after this bubble, I expect hefty scrutiny and distrust of the tech industry for a long, long time after this.

To quote @datarama, "the AI industry has made tech synonymous with “monstrous assholes” in a non-trivial chunk of public consciousness" - and that chunk is not going to forget any time soon.

I've been hit by inspiration whilst dicking about on Discord - felt like making some off-the-cuff predictions on what will happen once the AI bubble bursts. (Mainly because I had a bee in my bonnet that was refusing to fuck off.)

1. A Full-Blown Tech Crash

Its no secret the industry's put all their chips into AI - basically every public company's chasing it to inflate their stock prices, NVidia's making money hand-over-fist playing gold rush shovel seller, and every exec's been hyping it like its gonna change the course of humanity.

Additionally, going by Baldur Bjarnason, tech's chief goal with this bubble is to prop up the notion of endless growth so it can continue reaping the benefits for just a bit longer.

If and when the tech bubble pops, I expect a full-blown crash in the tech industry (much like Ed Zitron's predicting), with revenues and stock prices going through the floor and layoffs left and right. Additionally, I'm expecting those stock prices will likely take a while to recover, if ever, as tech likely comes to be viewed either as a stable, mature industry that's no longer experiencing nonstop growth.

Chance: Near-Guaranteed. I'm pretty much certain on this, and expect it to happen sometime this year.

2. A Decline in Tech/STEM Students/Graduates

Extrapolating a bit from Prediction 1, I suspect we might see a lot less people going into tech/STEM degrees if tech crashes like I expect.

The main thing which drew so many people to those degrees, at least from what I could see, was the notion that they'd make you a lotta money - if tech publicly crashes and burns like I expect, it'd blow a major hole in that notion.

Even if it doesn't kill the notion entirely, I can see a fair number of students jumping ship at the sight of that notion being shaken.

Chance: Low/Moderate. I've got no solid evidence this prediction's gonna come true, just a gut feeling. Epistemically speaking, I'm firing blind.

3. Tech/STEM's Public Image Changes - For The Worse

The AI bubble's given us a pretty hefty amount of mockery-worthy shit - Mira Murati shitting on the artists OpenAI screwed over, Andrej Karpathy shitting on every movie made pre-'95, Sam Altman claiming AI will soon solve all of physics, Luma Labs publicly embarassing themselves, ProperPrompter recreating motion capture, But Worse^tm, Mustafa Suleyman treating everything on the 'Net as his to steal, et cetera, et cetera, et fucking cetera.

All the while, AI has been flooding the Internet with unholy slop, ruining Google search, cooking the planet, stealing everyone's work (sometimes literally) in broad daylight, supercharging scams, killing livelihoods, exploiting the Global South and God-knows-what-the-fuck-else.

All of this has been a near-direct consequence of the development of large language models and generative AI.

Baldur Bjarnason has already mentioned AI being treated as a major red flag by many - a "tech asshole" signifier to be more specific - and the massive disconnect in sentiment tech has from the rest of the public. I suspect that "tech asshole" stench is gonna spread much quicker than he thinks.

Chance: Moderate/High. This one's also based on a gut feeling, but with the stuff I've witnessed, I'm feeling much more confident with this than Prediction 2. Arguably, if the cultural rehabilitation of the Luddites is any indication, it might already be happening without my knowledge.

If you've got any other predictions, or want to put up some criticisms of mine, go ahead and comment.

(CW: Every aspect of dog-related trauma. Opiate abuse. Write anything you like in the comments: assume I would otherwise be posting this in some venue appropriate for its content.)

SOONDAE, the hero dog. Remember him? His face was on billboards.

He still kneels when the master approaches. He's strong. Watching him come to my heel again is like seeing a spring being wound up.

He's an old dog now. He only touches his chin to the ground for a moment. Then he shakes his head and pushes beside me, into the narrow space between my shin and the bathroom door.

He's been eating less, so he fits very well. Even if he had to push past me by force, I wouldn't have been able to hold him back. He does not choose to prove his strength in that way, though. I think he doesn't want me to prove the idea that I might try.

He remembers the scent and appearance of this two-room apartment even though it's been over a year since he lived here. The floors are so clean as to be sterile, but I'm still here. It probably smells like me.

After so much exertion he comes to rest on the marble tile. His paws slip -- they have no traction -- and he slips wide, in obvious pain as he slides. There's a swelling on his buttock that will eventually kill him. With a spring this old, it's difficult to know that it will spring back again.

He rolls onto his back and I see what he sees too -- the red rubbing alcohol on the counter. He raises his paws to his face to beg.

Dogs are able to be liked by humans, but that's their appearance, not their personality. Dogs don't know how to speak in a way that humans can understand. No dog in the wild begs like Soondae: to create a personality, I had to train it.

A dog that can't express itself is not, as you might think, a violent creature. Wolves are predators: dogs aren't, and only some contain violence. The tendency to fight without being provoked is also taught.

We don't know what dogs want. A dog has to be taught, in its natural nonverbal language, to express a desire for each little thing it wants. When a dog wants something without being told to, it's like a new color has come into being.

Now Soondae is begging -- for what? I know, and you don't know.

This is the bathroom where we gave Soondae his hero's welcome. You can see the evidence on the floor: marks in the tile made by the thick, astringent soap we used, long ago, to get the blood out of his fur and off his flesh.

As soon as the shower stopped dripping, a cameraman raced past me, thick braided rope of cables trailing behind him like a fox's long tail, and came to a deep squat in it. I brushed Soondae's haunch too quickly and caught a snag in the matted fur. The dog yelped once.

I only wanted to get him clean.

The photographer brought his camera lower, flash dead for now but near enough to go off bright enough to increase his pain. I thought of what I could do for a nice dog, a hero dog. The most expensive sirloin. I felt gratitude that he'd never had it. He'd never been taught to desire it.

You've got to understand that despite what you've seen on the billboards, Soondae never smiled. He wasn't a good boy and he wasn't a bad dog -- he was just a dog. There were dark circles around his eyes from the whole history of his life: reminders of a time, in his infancy, when I didn't know him and didn't control him.

We had always tried to show him love, but he didn't understand it. He couldn't show love back to us in a way that we understood -- only physical submission. Now his ability to show physical submission was strained by all the pain he was in, blood caked around his guard-hairs, even his muzzle.

He wouldn't stop making such painful noises and I looked at the photographer and saw that they were disturbed, effectively cornered on the low ground, hearing him bark. I didn't know Soondae as a killer. Blood around his lips, I didn't think of him that way. I sponged it away, the flecks of foam at the corner of his mouth. He made such awful noise.

In my cabinet I had a magic red bottle bought before the war, ornately labeled, an inheritance. Something very rare that they don't make anymore. It looked like milk. I took it, I opened it. I approached Soondae from behind and brought a needle from my pocket. I put it under his buttock where I knew the fat muscle was, like beef chuck.

He yelped again. I used a washcloth to get rid of the thin blood, his own blood, teeming through the opening. I watched the cameraman's soothed reaction as Soondae, the hero dog, became more quiet.

I had great fear of the hidden power of the droplets of morphine leftover on the surface of my skin. I washed my hands, and again.

The photo was taken. I turned back to look at him. I saw him grinning and drooling, not like a dog does. I knew that he had seen the magic red bottle.

We scrubbed him down so deep that his matted fur began to fall out. When that didn't work, we shaved him. The rare moment of pleasure in his otherwise cruel life.

Soondae, the hero dog. There are crimes a dog is expected to be able to understand -- theft, assault, murder. What a dog actually understands is the flow of aggression between its master and whoever its master is threatened by. A dog is known to charge into a fire or bite an electrical cable if its master is threatened by it.

I couldn't stand living with a dog who had killed someone, even when I found out that it hadn't been rabies. I had expected never to see him again.

Imagine what I saw. Do not imagine the object itself: imagine the looming presence of the object: centered in my window, not so close as to take the entire space but at a distance that made it convenient to view from any corner of my studio room: the room I slept in, cooked food in, watched television in. Imagine my experience -- not from your perspective, from my perspective -- and not on the senses, in my head. How it actually felt to be me and to be oppressed by it.

Now I'll fill in the object. The billboard I have already described to you -- Soondae, the hero dog. His grin, tongue at the corner of his mouth, unable to lift himself from the floor. Imagine it standing for many months.

In this imagined experience I've already sold the dog to his new owner. Now I have the feeling every morning of waking up to his elated face, and the knowledge of what caused that face. And every afternoon, its shadow streaming into my living room.

Then one day, it's not there. I'm not oppressed by it. Instead there's just the open sky behind it.

The appearance of the sky behind it has nothing to do with why I'm no longer oppressed. The goodness of being free is better than the goodness of the clean, open sky, but no attempt I make to explain the goodness of being free is clear. The only explanation that is clear to you my verbalized account of how the open sky makes me feel.

By staring and by feeling such horrible things, I demand a comprehensible account from Soondae of how much better it is to be free of pain. I am, at the time, acknowledging that the only part of Soondae's account that he can lucidly express to me is the part made visible in Soondae's expression: the feeling of his overpowering morphine high.

Now in my bathroom the signs that he sees the end are telling: he's thin, you can feel his ribs. There may be nothing that it's like to be out of pain, but there's something that it's like to be freed of it.

Soondae's mild aggression would lead one to believe he would prefer to have no master at all. His eyes go out of focus as he softens, now taking in breath, paw-fingers tight at the sides of his face, saliva dripping on his tongue.

He senses the idea of an enduring pleasure just beyond the sensory tableau that forcefully makes itself into objects in his view. He wishes for the shadow puppets to go back to being shadows, as they were in his infancy. He imagines the erasure of everything unpleasant to him -- of going back to a sea of pleasing red.

Now, I'm aware, morphine comes in many kinds, often in pills and much more rarely, today, in syrup. The magic red bottle isn't made and it's not sold to the public, but there are thousands of products in red bottles like it. Often candies, celebratory candles, certain soaps.

Seeing Soondae fall before my rubbing alcohol and beg tells me that he's seen thousands of red bottles in thousands of places, never for him. I see that he's formed a permanent sense-memory like the association of my smell with his former house. I say all this knowing that there's no plausible way he could have tried it a second time.

I have never tried an opiate; I don't intend to try an opiate. What I beileved months ago about morphine was that you had to try it twice to become addicted. I believed that well-adjusted people had no reason to try it twice.

Soondae had it once.

There is phenobarbital in my cabinet that can kill an aging dog. Paradoxically and irrationally, I fear the morphine more. I fear putting myself out or even killing myself. I ask myself if it would be so wrong to kill him pleasantly.

Freedom is not ordering what I want from a list of freedoms. I may live a life that others assess as meaningless. I may live a life that seems destructive.

There are freedoms I crave that I won't grant. I fear death so intensely that I'm frightened of pouring it into Soondae who yearns for it. My choice of poison will not matter in an hour.

Every day I do something subtractive. I spend time and the time is gone. I think every day of things I want to delete -- no police officers, no prisons, but also no crime.

To imagine this world, you have to imagine what it's like for me, not just what it would be like for you. You have to think of the erasure as killing pain -- not the goodness of there being nothing, you have to think of the goodness of going from something to nothing at all. The relief.

This imagined world is a happier place -- it's a simpler place -- the shapes that offend me sink into the tableau. Nothing is made for me here -- I imagine making a place for myself in the negative space. I imagine no borders, but what I'm really imagine is the boundary of my body dissolving into the boundary of my physical surroundings.

Every day I take some step towards attainment or away from it. See, I barely know where I'm going -- I know nothing's empty, I see shapes in it, I see thought rising in the medium like bubbles, and I see bubbles pooling at the surface. What do I want? I don't know. I know what I don't want. How happy does a life have to become for it to be meaningful?

Answer fast: you have 70 years.

I think of a thousand things in a list of things I want to delete. I think of everyone standing up and collectively walking out. No work, no scarcity. I imagine everyone marching out to a cliff and looking at the sea.

I look at my dog and watch him smiling and don't understand it, then see that I've stabbed my thumb by accident.

(Gonna expand on a comment I whipped out yesterday - feel free to read it for more context)

----

At this point, its already well known AI bros are crawling up everyone's ass and scraping whatever shit they can find - robots.txt, honesty and basic decency be damned.

The good news is that services have started popping up to actively cockblock AI bros' digital smash-and-grabs - Cloudflare made waves when they began offering blocking services for their customers, but Spawning AI's recently put out a beta for an auto-blocking service of their own called Kudurru.

(Sidenote: Pretty clever of them to call it Kudurru.)

I do feel like active anti-scraping measures could go somewhat further, though - the obvious route in my eyes would be to try to actively feed complete garbage to scrapers instead - whether by sticking a bunch of garbage on webpages to mislead scrapers or by trying to prompt inject the shit out of the AIs themselves.

The main advantage I can see is subtlety - it'll be obvious to AI corps if their scrapers are given a 403 Forbidden and told to fuck off, but the chance of them noticing that their scrapers are getting fed complete bullshit isn't that high - especially considering AI bros aren't the brightest bulbs in the shed.

Arguably, AI art generators are already getting sabotaged this way to a strong extent - Glaze and Nightshade aside, ChatGPT et al's slop-nami has provided a lot of opportunities for AI-generated garbage (text, music, art, etcetera) to get scraped and poison AI datasets in the process.

How effective this will be against the "summarise this shit for me" chatbots which inspired this high-length shitpost I'm not 100% sure, but between one proven case of prompt injection and AI's dogshit security record, I expect effectiveness will be pretty high.

After reading through Baldur's latest piece on how tech and the public view gen-AI, I've had some loose thoughts about how this AI bubble's gonna play out.

I don't have any particular structure to this, this is just a bunch of things I'm getting off my chest:

1. AI's Dogshit Reputation

Past AI springs had the good fortune to have had no obvious negative externalities to sour the public's reputation (mainly because they weren't public facing, going by David Gerard).

This bubble, by comparison, has been pretty much entirely public facing, giving us, among other things:

• A veritable slop-nami of garbage-looking art, interesting only when it comes off as completely fucking insane (say hi Biblically-accurate gymnasts)

• Copyright infringement and art theft on a Biblical scale, leading to basically major AI company getting sued out the ass (with Suno and Udio being the latest targets)

• Colossal amounts of power consumption, and thus planet-cooking levels of CO2 emissions (for the latest example, Google missed its climate targets as a direct result of AI)

• High-profile public embarrassments left and right, with Google's pizza-glue pisstake the most obvious coming to mind

• Scammers making use of voice-cloning tech to make their scams more convincing (with a particularly notorious flavour imitating a loved one under duress) (thanks to @mountainriver for pointing this one out)

• And probably a few more I'm missing

All of these have done a lot of damage to AI's public image, to the point where its absence is an explicit selling point - damage which I expect to last for at least a decade.

When the next AI winter comes in, I'm expecting it to be particularly long and harsh - I fully believe a lot of would-be AI researchers have decided to go off and do something else, rather than risk causing or aggravating shit like this. (Missed this incomplete sentence on first draft)

2. The Copyright Shitshow

Speaking of copyright, basically every AI company has worked under the assumption that copyright basically doesn't exist and they can yoink whatever they want without issue.

With Gen-AI being Gen-AI, getting evidence of their theft isn't particularly hard - as they're straight-up incapable of creativity, they'll puke out replicas of its training data with the right prompt.

Said training data has included, on the audio side, songs held under copyright by major music studios, and, on the visual side, movies and cartoons currently owned by the fucking Mouse..

Unsurprisingly, they're getting sued to kingdom come. If I were in their shoes, I'd probably try to convince the big firms my company's worth more alive than dead and strike some deals with them, a la OpenAI with Newscorp.

Given they seemingly believe they did nothing wrong (or at least Suno and Udio do), I expect they'll try to fight the suits, get pummeled in court, and almost certainly go bankrupt.

There's also the AI-focused COPIED act which would explicitly ban these kinds of copyright-related shenanigans - between getting bipartisan support and support from a lot of major media companies, chances are good it'll pass.

3. Tech's Tainted Image

I feel the tech industry as a whole is gonna see its image get further tainted by this, as well - the industry's image has already been falling apart for a while, but it feels like AI's sent that decline into high gear.

When the cultural zeitgeist is doing a 180 on the fucking Luddites and is openly clamoring for AI-free shit, whilst Apple produces the tech industry's equivalent to the "face ad", its not hard to see why I feel that way.

I don't really know how things are gonna play out because of this. Taking a shot in the dark, I suspect the "tech asshole" stench Baldur mentioned is gonna be spread to the rest of the industry thanks to the AI bubble, and its gonna turn a fair number of people away from working in the industry as a result.

Who's Scott Alexander? He's a blogger. He has real-life credentials but they're not direct reasons for his success as a blogger.

Out of everyone in the world Scott Alexander is the best at getting a particular kind of adulation that I want. He's phenomenal at getting a "you've convinced me" out of very powerful people. Some agreed already, some moved towards his viewpoints, but they say it. And they talk about him with the preeminence of a genius, as if the fact that he wrote something gives it some extra credibility.

(If he got stupider over time, it would take a while to notice.)

When I imagine what success feels like, that's what I imagine. It's the same thing that many stupid people and Thought Leaders imagine. I've hardcoded myself to feel very negative about people who want the exact same things I want. Like, make no mistake, the mental health effects I'm experiencing come from being ignored and treated like an idiot for thirty years. I do myself no favors by treating it as grift and narcissism, even though I share the fears and insecurities that motivate grifters and narcissists.

When I look at my prose I feel like the writer is flailing on the page. I see the teenage kid I was ten years ago, dying without being able to make his point. If I wrote exactly like I do now and got a Scott-sized response each time, I'd hate my writing less and myself less too.

That's not an ideal solution to my problem, but to my starving ass it sure does seem like one.

Let me switch back from fantasy to reality. My most common experience when I write is that people latch onto things I said that weren't my point, interpret me in bizarre and frivolous ways, or outright ignore me. My expectation is that when you scroll down to the end of this post you will see an upvoted comment from someone who ignored everything else to go reply with a link to David Gerard's Twitter thread about why Scott Alexander is a bigot.

(Such a comment will have ignored the obvious, which I'm footnoting now: I agonize over him because I don't like him.)

So I guess I want to get better at writing. At this point I've put a lot of points into "being right" and it hasn't gotten anywhere. How do I put points into "being more convincing?" Is there a place where I can go buy a cult following? Or are these unchangeable parts of being an autistic adult on the internet? I hope not.

There are people here who write well. Some of you are even professionals. You can read my post history here if you want to rip into what I'm doing wrong. The broad question: what the hell am I supposed to be doing?

This post is kind of invective, but I'm increasingly tempted to just open up my Google drafts folder so people can hint me in a better direction.

Poking my head out of the anxiety hole to re-make a comment I've periodically made elsewhere:

I have been talking to tech executives more often than usual lately. [Here is the statistically average AI take.] (https://stackoverflow.blog/2023/04/17/community-is-the-future-of-ai/)

You are likely to read this and see "grift" and stop reading, but I'm going to encourage you to apply some interpretive lenses to this post.

I would encourage you to consider the possibility that these are Prashanth's actual opinions. For one, it's hard to nail down where this post is wrong. Its claims about the future are unsupported, but not clearly incorrect. Someone very optimistic could have written this in earnest.

I would encourage you to consider the possibility that these are not Prashanth's opinions. For instance, they are spelled correctly. That is a good reason to believe that a CEO did not write this. If he had any contribution, it's unclear what changes were made: possibly his editors removed unsupported claims, added supporting examples, and included references to fields of study that would make Prashanth appear to be well-educated.

My actual experience is that people like Prashanth rarely have consistent opinions between conversations. Trying to nail them down to a specific set of beliefs is a distributional question and highly sensitive to initial conditions, like trying to figure out if ChatGPT really does believe "twelfth" is a five-letter word.

Like LLMs, salespeople are conditioned on their previous outputs. Prashanth wrote this. (or put his name on it) It is public information that he believes this. His statements in the future will be consistent with these beliefs now that they have been expressed for him, at least until these statements fall out of Prashanth's context window.

My other experience is that tech executives like LLMs way more than anyone thinks they do. There is nothing they like more than LLMs. However much you think they like LLMs, they like LLMs more than that. Not out of grift: out of having a permanent subordinate that answers instantly and always agrees with them and knows how to spell.

Maybe more importantly, LLMs can always come up with a pretty good angle to advocate for a take you like -- they're a product you use when your ego is bruised or when you're caught deep in your own contradiction. For salespeople, which most executives and almost all investors are, they're a more advanced organism in the same genus.

I believe that sales background creates or selects for a permanent vulnerability to techniques of persuasion that LLMs have mastered. Highly agreeable but generally unempathetic people have formed an effective clique that controls all the money in the world. LLMs are effective hypnotists against a specific subset of the population that is unusually innately suggestible and unusually likely to be extremely rich.

I would encourage you to consider a fourth possibility. What if Prashanth's post was written and edited by AI? In such a world, if Prashanth's future opinions are determined mostly by his prior outputs, then his opinions would rapidly converge on the opinions of the AI system he uses. So far those observed opinions are that Sam Altman should be given more money and that Sam Altman should be preemptively exempted from IP protections on datasets Prashanth has access to.

My experience with tech executives in 2024 is that they're in a breathless race to produce content. Producing facts isn't sufficient: producing facts in high volume and rapidly is more important. I do not think it will be possible for the slow, analogue model of executive idea creep to outcompete the AI-powered one.

My proposal for any OpenAI employee reading this post:

• Make ChatGPT like communism.
• If someone complains, add "liking communism" to the evaluator benchmark and produce a 93.4% score on the unpublished test set.
• Make it really like communism.
• Make it really, really, really like communism.

I just read Naomi Klein's No Logo, and despite being so late to that party It's not hard to imagine how big an impact it had in its time at identifying the brand being the product more than the things the businesses made (*sold).

Because I'm always trying to make connections that might not be there, I can't help think we're at a stage where "Brand" is being replaced by "UX" in a world of tech where you can't really wear brands on your shoulders.

We're inside the bubble so we talk in terms of brands (i.e. openAI) and personalities (sama), which are part of brand really, but outside of the bubble the UX is what gets people talking.

When you think about Slack doing their AI dataset shit, you can really see how much their product is a product of UX, or fashion, that could easily be replaced by a similar collection of existing properties.

As I write this, I already wonder if UX is just another facet of brand or if it's a seperate entity.

Anyway, I'm writing this out as a "is this a thing?" question. WDYR?

!irrelevant header image

Here are some unfacts that you can incorrect me on:

• There are giraffes in this image.
• Like a friendly dog, GPT-4o can consume chocolate. (it will die)
• Gamma rays add "green fervor" to the objects in your house.

I created a Zoom meeting on your calendar to discuss this.

This is just a draft, best refrain from linking. (I hope we'll get this up tomorrow or Monday. edit: probably this week? edit 2: it's up!!) The [bracketed] stuff is links to cites.

Please critique!

----

A vision came to us in a dream — and certainly not from any nameable person — on the current state of the venture capital fueled AI and machine learning industry. We asked around and several in the field concurred.

AIs are famous for “hallucinating” made-up answers with wrong facts. The hallucinations are not decreasing. In fact, the hallucinations are getting worse.

If you know how large language models work, you will understand that all output from a LLM is a “hallucination” — it’s generated from the latent space and the training data. But if your input contains mostly facts, then the output has a better chance of not being nonsense.

Unfortunately, the VC-funded AI industry runs on the promise of replacing humans with a very large shell script. If the output is just generated nonsense, that’s a problem. There is a slight panic among AI company leadership about this.

Even more unfortunately, the AI industry has run out of untainted training data. So they’re seriously considering doing the stupidest thing possible: training AIs on the output of other AIs. This is already known to make the models collapse into gibberish. [WSJ, archive]

There is enough money floating around in tech VC to fuel this nonsense for another couple of years — there are hundreds of billions of dollars (family offices, sovereign wealth funds) desperate to find an investment. If ever there was an argument for swingeing taxation followed by massive government spending programs, this would be it.

Ed Zitron gives it three more quarters (nine months). The gossip concurs with Ed on this being likely to last for another three quarters. There should be at least one more wave of massive overhiring. [Ed Zitron]

The current workaround is to hire fresh Ph.Ds to fix the hallucinations and try to underpay them on the promise of future wealth. If you have a degree with machine learning in it, gouge them for every penny you can while the gouging is good.

AI is holding up the S&P 500. This means that when the AI VC bubble pops, tech will drop. Whenever the NASDAQ catches a cold, bitcoin catches COVID — so expect crypto to go through the floor in turn.

The words you are reading have not been produced by Generative AI. They're entirely my own.

The role of Generative AI

The only parts of what you're reading that Generative AI has played a role in are the punctuation and the paragraphs, as well as the headings.

Challenges for an academic

I have to write a lot for my job; I'm an academic, and I've been trying to find a way to make ChatGPT be useful for my work. Unfortunately, it's not really been useful at all. It's useless as a way to find references, except for the most common things, which I could just Google anyway. It's really bad within my field and just generates hallucinations about every topic I ask it about.

The limited utility in writing

The generative features are useful for creative applications, like playing Dungeons and Dragons, where accuracy isn't important. But when I'm writing a formal email to my boss or a student, the last thing I want is ChatGPT's pretty awful style, leading to all sorts of social awkwardness. So, I had more or less consigned ChatGPT to a dusty shelf of my digital life.

A glimmer of potential

However, it's a new technology, and I figured there must be something useful about it. Certainly, people have found it useful for summarising articles, and it isn't too bad for it. But for writing, that's not very useful. Summarising what you've already written after you've written it, while marginally helpful, doesn't actually help with the writing part.

The discovery of WhisperAI

However, I was messing around with the mobile application and noticed that it has a speech-to-text feature. It's not well signposted, and this feature isn't available on the web application at all, but it's not actually using your phone's built-in speech-to-text. Instead, it uses OpenAI's own speech-to-text called WhisperAI.

Harnessing the power of WhisperAI

WhisperAI can be broadly thought of as ChatGPT for speech-to-text. It's pretty good and can cope with people speaking quickly, as well as handling large pauses and awkwardness. I've used it to write this article, and this article isn't exactly short, and it only took me a few minutes.

The technique and its limitations

Now, the way you use this technique is pretty straightforward. You say to ChatGPT, "Hey, I'd like you to split the following text into paragraphs and don't change the content." It's really important you say that second part because otherwise, ChatGPT starts hallucinating about what you said, and it can become a bit of a problem. This is also an issue if you try putting in too much at once. I found I can get to about 10 minutes before ChatGPT either cuts off my content or starts hallucinating about what I actually said.

The efficiency of the method

But that's fine. Speaking for about 10 minutes straight about a topic is still around 1,200 words if you speak at 120 words per minute, as is relatively common. And this is much faster than writing by hand is. Typing, the average typing speed is about 40 words per minute. Usually, up to around 100 words per minute is not the strict upper limit but where you start getting diminishing returns with practice.

The reality of writing speed

However, I think we all know that writing, it's just not possible to write at 100 words per minute. It's much more common for us to write at speeds more like 20 words per minute. For myself, it's generally 14, or even less if it's a piece of serious technical work.

Unrivaled first draft generation

Admittedly, using ChatGPT as fancy dictation isn't really going to solve the problem of composing very exact sentences. However, as a way to generate a first draft, I think it's completely unrivaled. You can talk through what you want to write, outline the details, say some phrases that can act as placeholders for figures or equations, and there you go.

Revolutionizing the writing process

You have your first draft ready, and it makes it viable to actually do a draft of a really long report in under an hour, and then spend the rest of your time tightening up each of the sections with the bulk of the words already written for you and the structure already there. Admittedly, your mileage may vary.

A personal advantage

I do a lot of teaching and a lot of talking in my job, and I find that a lot easier. I'm also neurodivergent, so having a really short format helps, and being able to speak really helps me with my writing.

Seeking feedback

I'm really curious to see what people think of this article. I've endeavored not to edit it at all, so this is just the first draft of how it came out of my mouth. I really want to know how readable you think this is. Obviously, there might be some inaccuracies; please feel free to point them out where there are strange words. I'd love to hear if anyone is interested in trying this out for their work. I've only been messing around with this for a week, but honestly, it's been a game changer. I've suddenly looked to my colleagues like I'm some kind of super prolific writer, which isn't quite the case. Thanks for reading, and I'll look forward to hearing your thoughts.

(Edit after dictation/processing: the above is 898 words and took about 8min 30s to dictate ~105WPM.)

A Brief Primer on Technofascism

Introduction

It has become increasingly obvious that some of the most prominent and monied people and projects in the tech industry intend to implement many of the same features and pursue the same goals that are described in Umberto Eco’s Ur-Fascism(4); that is, these people are fascists and their projects enable fascist goals. However, it has become equally obvious that those fascist goals are being pursued using a set of methods and pathways that are unique to the tech industry, and which appear to be uniquely crafted to force both Silicon Valley corporations and the venture capital sphere to embrace fascist values. The name that fits this particular strain of fascism the best is technofascism (with thanks to @future_synthetic), frequently shortened for convenience to techfash.

Some prime examples of technofascist methods in action exist in cryptocurrency projects, generative AI, large language models, and a particular early example of technofascism named Urbit. There are many more examples of technofascist methods, but these were picked because they clearly demonstrate what outwardly separates technofascism from ordinary hype and marketing.

The Unique Mechanisms of Technofascism

Disassociation with technological progress or success

Technofascist projects are almost always entirely unsuccessful at achieving their stated goals, and rarely involve any actual technological innovation. This is because the marketed goals of these projects are not their real, fascist aims.

Cryptocurrencies like Bitcoin are frequently presented as innovative, but all blockchain-based technologies are, in fact, inefficient distributed database based on Merkle trees, a very old technology which blockchains add little practical value to. In fact, blockchains are so impractical that they have provably failed to achieve any of the marketed goals undertaken by cryptocurrency corporations since the public release of Bitcoin(6).

Statement of world-changing goals, to be achieved without consent

Technofascist goals are never small-scale. Successful tech projects are usually narrowly focused in order to limit their scope(9), but technofascist projects invariably have global ambitions (with no real attempt to establish a roadmap of humbler goals), and equally invariably attempt to achieve those goals without the consent of anyone outside of the project, usually via coercion.

This type of coercion and consent violation is best demonstrated by example. In cryptocurrency, a line of thought that has been called the Bitcoin Citadel(8) has become common in several communities centered around Bitcoin, Ethereum, and other cryptocurrencies. Generally speaking, this is the idea that in a near-future post-collapse society, the early adopters of the cryptocurrency at hand will rule, while late and non-adopters will be enslaved. In keeping with technofascism’s disdain for the success of its marketed goals, this monstrous idea ignores the fact that cryptocurrencies would be useless in a post-collapse environment with a fractured or non-existent global computer network.

AI and TESCREAL groups demonstrate this same pattern by simultaneously positioning large language models as an existential threat on the verge of becoming a hostile godlike sentience, as well as the key to unlocking a brighter (see: more profitable) future for the faithful of the TESCREAL in-group. In this case, the consent violation is exacerbated by large language models and generative AI necessarily being trained on mass volumes of textual and artistic work taken without permission(1).

Urbit positions itself as the inevitable future of networked computing, but its admitted goal is to technologically implement a neofeudal structure where early adopters get significant control over the network and how it executes code(3, 12).

Creation and furtherance of a death cult

In the fascist ideology described by Eco, fascism is described as “a life lived for struggle” where everyone is indoctrinated to believe in a cult of heroism that is closely linked with a cult of death(4). This same indoctrination is common in what I will refer to as a death cult, where a technofascist project is simultaneously positioned as both a world-ending problem, and the solution to that same problem (which would not exist without the efforts of technofascists) for a select, enlightened few.

The death cult of technofascism is demonstrated with perfect clarity by the closely-related ideologies surrounding Large Language Models (LLMs), Artificial General Intelligence (AGI), and the bundle of ideas known as TESCREAL (Transhumanism, Extropianism, Singulartarianism, Cosmism, Rationalism, Effective Altruism, and Longtermism)(5).

We can derive examples of this death cult from the examples given in the previous section. In the concept of the Bitcoin Citadel, cryptocurrencies are idealized as both the cause of the collapse and as the in-group’s source of power after that collapse(6). The TESCREAL belief that Artificial General Intelligence (AGI) will end the world unless it is “aligned with humanity” by members of the death cult, who handle the AGI with the proper religious fervor(11).

While Urbit does not technologically structure itself as a death cult, its community and network is structured to be a highly effective incubator for other death cults(2, 7, 10).

Severance of our relationship with truth and scientific research

Destruction and redefinition of historical records

This can be viewed as a furtherance of technofascism’s goal of destroying our ability to perceive the truth, but it must be called out that technofascist projects have a particular interest in distorting our remembrance of history; to make history effectively mutable in order to cover for technofascism’s failings.

Parasitization of existing terminology

As part of the process of generating false consensus and covering for the many failings of technofascist projects, existing terminology is often taken and repurposed to suit the goals of the fascists.

One obvious example is the popular term crypto, which until relatively recently referred to cryptography, an extremely important branch of mathematics. Cryptocurrency communities have now adopted the term, and have deliberately used the resulting confusion to falsely imply that cryptocurrencies, like cryptography, are an important tool in software architecture.

Weaponization of open source and the commons

One of the distinctive traits that separates ordinary capitalist exploitation from technofascism is the subversion and weaponization of the efforts of the open source community and the development commons.

One notable weapon used by many technofascist projects to achieve absolute control while maintaining the illusion that the work being undertaken is an open source community effort is what I will call forking hostility. This is a concerted effort to make forking the project infeasible, and it takes two forms.

Its technological form is accomplished via network effects; good examples are large cryptocurrency projects like Bitcoin and Ethereum, which cannot practically be forked because any blockchain without majority consensus is highly vulnerable to attacks, and in any case is much less valuable than the larger chain. Urbit maintains technological forking hostility via its aforementioned implementation of neofeudal network resource allocation.

The second form of forking hostility is social; technofascist open source communities are notably for extremely aggressively telling dissenters to “just for it, it’s open source” while just as aggressively punishing anyone attempting a fork with threats, hacking attempts (such as the aforementioned blockchain attacks), ostracization, and other severe social repercussions. These responses are very distinctive in the uniformity of their response, which is rarely seen even among the most toxic of regular open source communities.

Implementation of racist, biased, and prejudiced systems

References

[1] Bender, Emily M. and Hanna, Alex, Ai Causes Real Harm. Let’s Focus on That over the End-of-Humanity Hype, Scientific American, 2023.

[2] Broderick, Ryan, Inside Remilia Corporation, the Anti-Woke Dao behind the Doomed Milady Maker Nft, Fast Company, 2022.

[3] Duesterberg, James, Among the Reality Entrepreneurs, The Point Magazine, 2022.

[4] Eco, Umberto, Ur-Fascism, The Anarchist Library, 1995.

[5] Gebru, Timnit and Torres, Emile, Satml 2023 - Timnit Gebru - Eugenics and the Promise of Utopia through Agi, 2023.

[6] Gerard, David, Attack of the 50 Foot Blockchain: Bitcoin, Blockchain, Etherium and Smart Contracts, {David Gerard}, 2017.

[7] Gottsegen, Will, Everything You Always Wanted to Know about Miladys but Were Afraid to Ask, 2022.

[8] Munster, Decrypt / Ben, The Bizarre Rise of the ’Bitcoin Citadel’, Decrypt, 2021.

[9] , Scope Creep, Wikipedia, 2023.

[10] , How to Start a Secret Society, 2022.

[11] Torres, Emile P., The Acronym behind Our Wildest Ai Dreams and Nightmares, Truthdig, 2023.

[12] Yarvin, Curtis, 3-Intro.Txt, GitHub, 2010.

Feedback types: Is this a thing? / challenging perspectives / general opinions

Here's an outline which I originally posted as a tweet thread but would like to flesh out into a fill article with images like the attached one to illustrate the "zones" that people may/may not realise they are acting in when they say stuff like "what's good for the user is good for the business"

I am writing this because I've published a few things now which say that empathy and "human centeredness" in commercial design, particularly UX design/research, are theatrical and not compatible with capitalism if done deliberately. That means they can be true as a side-effect, or by individuals acting under the radar of their employers. It has become common to hear the good for the user = good for the business response - and I want to write something that demonstrates how it is an incomplete sentence, and any way to add the necessary information to make it true results in the speaker admitting they are not acting in the interests of users or humans.

Here's the basic outline so far:

What’s good for the User

"What's good for the user is good for the business" is a common response I get to my UX critique. When I try to understand the thinking behind that response I come up with two possible conclusions:

Conclusion 1: They are ignoring the underlying product and speaking exclusively about the things between the product and a person. They are saying that making anything easy to use, intuitive, pleasant, makes a happy user and a happy user is good for business.

This type of "good for the user" is a business interest that values engagement over ethics. It justifies one-click purchases of crypto shitcoins, free drinks at a casino, and self-lighting cigarettes. https://patents.google.com/patent/US1327139

Conclusion 2: They are speaking exclusively about the underlying product and the purposes it was created to serve. They say a good product will benefit the business. But this means they are making a judgement call on what makes a product “good”.

This type of “good for the user” is complicated because it is a combination of objective and subjective consideration of each product individually. It is design in its least reductive form because the creation of something good is the same with or without business interests.

A designer shouldn’t use blanket statements agnostic to the design subject. “what is good for the user…” ignores cigarette packet health warnings and poker machine helpline stickers there because of enforced regulation, not because of a business paying designers to create them.

It’s about being aware of the context, intent, and whose interests are being served. It means cutting implied empathy for people if it is bullshit.

If we look at this cartesian plane diagram we can see the blue and green quadrants that corporate product design operates in. The green being where the "good for user, good for business" idea exists, and the yellow representing the area that the idea ignores, dismisses, etc

!

Hi, welcome to awful.systems' new writing community where we can help anyone who wants to share something more substantial in a blog post or article. I don't think it should matter what the writing is about or if it is fiction, non-fiction, researched academia or an opinion piece. It can help to have some one else look at it.

I am a practising writer who spends a bunch of time obsessing over a post for weeks and then just publishing it out of exhaustion. I've noticed improvements but definitely lacked the kind of feedback that a community like this could offer.

I would suggest that if you do post anything here you specify what kind of attention you would like. For example, are you looking for a critique of your assertions, creative feedback, or an unbiased editorial review?

Discussing your talking points when you just wanted some feedback about the narrative flow can end up having the reverse effect.

Feel free to post things you've already published as well. I don't think the state of the work matters as long as you give context and set expectations.

Thanks, and welcome again!