An odd mix of geekery, fashion, equity and beauty. Oh, don't mind the wolves. They're harmless, mostly --Queer, gtfo if you think its a slur-- Age: my primary email accounts were made in the previous century.
recently my friend's comics professor told her that it's acceptable to use gen AI for script-writing but not for art, since a machine can't generate meaningful artistic work. meanwhile, my sister's screenwriting professor said that they can use gen AI for concept art and visualization, but that it won't be able to generate a script that's any good. and at my job, it seems like each department says that AI can be useful in every field except the one that they know best.
It's only ever the jobs we're unfamiliar with that we assume can be replaced with automation. The more attuned we are with certain processes, crafts, and occupations, the more we realize that gen AI will never be able to provide a suitable replacement. The case for its existence relies on our ignorance of the work and skill required to do everything we don't.
This is how they wrap surgical sets before sterilizing them (in a cloth not paper...god I wosh the cloth is a pain in the ass) except when they tuck the last bit in, they fold it over so the end is poking out of the box (like a pull tab).
If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
Like you, I'm sick to the back teeth of talking about AI. Like you, I keep getting dragged into discussions of AI. Unlike you‡, I spent the summer writing a book about why I'm sick of writing about AI⹋, which Farrar, Straus and Giroux will publish in 2026.
‡probably
⹋"The Reverse Centaur's Guide to AI"
A week ago, I turned that book into a speech, which I delivered as the annual Nordlander Memorial Lecture at Cornell, where I'm an AD White Professor-at-Large. This was my first-ever speech about AI and I wasn't sure how it would go over, but thankfully, it went great and sparked a lively Q&A. One of those questions came from a young man who said something like "So, you're saying a third of the stock market is tied up in seven AI companies that have no way to become profitable and that this is a bubble that's going to burst and take the whole economy with it?"
I said, "Yes, that's right."
He said, "OK, but what can we do about that?"
So I re-iterated the book's thesis: that the AI bubble is driven by monopolists who've conquered their markets and have no more growth potential, who are desperate to convince investors that they can continue to grow by moving into some other sector, e.g. "pivot to video," crypto, blockchain, NFTs, AI, and now "super-intelligence." Further: the topline growth that AI companies are selling comes from replacing most workers with AI, and re-tasking the surviving workers as AI babysitters ("humans in the loop"), which won't work. Finally: AI cannot do your job, but an AI salesman can 100% convince your boss to fire you and replace you with an AI that can't do your job, and when the bubble bursts, the money-hemorrhaging "foundation models" will be shut off and we'll lose the AI that can't do your job, and you will be long gone, retrained or retired or "discouraged" and out of the labor market, and no one will do your job. AI is the asbestos we are shoveling into the walls of our society and our descendants will be digging it out for generations:
The only thing (I said) that we can do about this is to puncture the AI bubble as soon as possible, to halt this before it progresses any further and to head off the accumulation of social and economic debt. To do that, we have to take aim at the material basis for the AI bubble (creating a growth story by claiming that defective AI can do your job).
"OK," the young man said, "but what can we do about the crash?" He was clearly very worried.
"I don't think there's anything we can do about that. I think it's already locked in. I mean, maybe if we had a different government, they'd fund a jobs guarantee to pull us out of it, but I don't think Trump'll do that, so –"
"But what can we do?"
We went through a few rounds of this, with this poor kid just repeating the same question in different tones of voice, like an acting coach demonstrating the five stages of grieving using nothing but inflection. It was an uncomfortable moment, and there was some decidedly nervous chuckling around the room as we pondered the coming AI (economic) apocalypse, and the fate of this kid graduating with mid-six-figure debts into an economy of ashes and rubble.
I firmly believe the (economic) AI apocalypse is coming. These companies are not profitable. They can't be profitable. They keep the lights on by soaking up hundreds of billions of dollars in other people's money and then lighting it on fire. Eventually those other people are going to want to see a return on their investment, and when they don't get it, they will halt the flow of billions of dollars. Anything that can't go on forever eventually stops.
This isn't like the early days of the web, or Amazon, or any of those other big winners that lost money before becoming profitable. Those were all propositions with excellent "unit economics" – they got cheaper with every successive technological generation, and the more customers they added, the more profitable they became. AI companies have – in the memorable phraseology of Ed Zitron – "dogshit unit-economics." Each generation of AI has been vastly more expensive than the previous one, and each new AI customer makes the AI companies lose more money:
This week, no less than the Wall Street Journal published a lengthy, well-reported story (by Eliot Brown and Robbie Whelan) on the catastrophic finances of AI companies:
The WSJ writers compare the AI bubble to other bubbles, like Worldcom's fraud-soaked fiber optic bonanza (which saw the company's CEO sent to prison, where he eventually died), and conclude that the AI bubble is vastly larger than any other bubble in recent history.
The data-center buildout has genuinely absurd finances – there are data-center companies that are collateralizing their loans by staking their giant Nvidia GPUs as collateral. This is wild: there's pretty much nothing (apart from fresh-caught fish) that loses its value faster than silicon chips. That goes triple for GPUs used in AI data-centers, where it's normal for tens of thousands of chips to burn out over a single, 54-day training run:
That barely scratches the surface of the funny accounting in the AI bubble. Microsoft "invests" in Openai by giving the company free access to its servers. Openai reports this as a ten billion dollar investment, then redeems these "tokens" at Microsoft's data-centers. Microsoft then books this as ten billion in revenue.
That's par for the course in AI, where it's normal for Nvidia to "invest" tens of billions in a data-center company, which then spends that investment buying Nvidia chips. The the same chunk of money being energetically passed back and forth between these closely related companies, all of which claim it as investment, as an asset, or as revenue (or all three).
The Journal quotes David Cahn, a VC from Sequoia, who says that for AI companies to become profitable, they would have to sell us $800 billion worth of services over the life of today's data centers and GPUs. Not only is that a very large number – it's also a very short time. AI bosses themselves will tell you that these data centers and GPUs will be obsolete practically from the moment they start operating. Mark Zuckerberg says he's prepared to waste "a couple hundred billion dollars" on misspent AI investments:
Bain & Co says that the only way to make today's AI investments profitable is for the sector to bring in $2 trillion by 2030 (the Journal notes that this is more than the combined revenue of Amazon, Google, Microsoft, Apple Nvidia and Meta):
How much money is the AI industry making? Morgan Stanley says it's $45b/year. But that $45b is based on the AI industry's own exceedingly cooked books, where annual revenue is actually annualized revenue, an accounting scam whereby a company chooses its best single revenue month and multiplies it by 12, even if that month is a wild outlier:
https://www.wheresyoured.at/the-haters-gui/
Industry darlings like Coreweave (a middleman that rents out data-centers) are sitting on massive piles of debt, secured by short-term deals with tech companies that run out long before the debts can be repaid. If they can't find a bunch of new clients in a couple short years, they will default and collapse.
Today's AI bubble has absorbed more of the country's wealth and represents more of its economic activity than historic nation-shattering bubbles, like the 19th century UK rail bubble. A much-discussed MIT paper found that 95% of companies that had tried AI had either nothing to show for it, or experienced a loss:
Anything that can't go on forever eventually stops. Trump might bail out the AI companies, but for how long? They are incinerating money faster than practically any other human endeavor in history, with precious little to show for it.
During my stay at Cornell, one of the people responsible for the university's AI strategy asked me what I thought the university should be doing about AI. I told them that they should be planning to absorb the productive residue that will be left behind after the bubble bursts:
Plan for a future where you can buy GPUs for ten cents on the dollar, where there's a buyer's market for hiring skilled applied statisticians, and where there's a ton of extremely promising open source models that have barely been optimized and have vast potential for improvement.
There's plenty of useful things you can do with AI. But AI is (as Princeton's Arvind Narayanan and Sayash Kapoor, authors of AI Snake Oil put it), a normal technology:
That doesn't mean "nothing to see here, move on." It means that AI isn't the bow-wave of "impending superintelligence." Nor is it going to deliver "humanlike intelligence."
It's a grab-bag of useful (sometimes very useful) tools that can sometimes make workers' lives better, when workers get to decide how and when they're used.
The most important thing about AI isn't its technical capabilities or limitations. The most important thing is the investor story and the ensuing mania that has teed up an economical catastrophe that will harm hundreds of millions or even billions of people. AI isn't going to wake up, become superintelligent and turn you into paperclips – but rich people with AI investor psychosis are almost certainly going to make you much, much poorer.
Gosh this is hard. Well, best to not beat around the bush. I’m just a little concerned that you’re one of those people who think that transmascs don’t…exist, because of the rhetoric of “who wouldn’t want to be a woman it is a superior experience in every conceivable way, they must be confused and have internalized misogyny”.
I’ve heard it happen and I just like— want to clarify?
kaledo-art
jacobvanloon
2087
yousharknotpass
turnnoffyourmind
theartofmadeline
germansingergirl
jbbartram-illu
