The talk was sold out, but here's the text of my lecture. I'm very grateful to UW for the opportunity, and for a lovely visit to Seattle!

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I'm a science fiction writer, which means that my job is to make up futuristic parables about our current techno-social arrangements to interrogate not just what a gadget *does*, but who it does it *for*, and who it does it *to.*

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What I *don't* do is predict the future. *No one* can predict the future, which is a good thing, since if the future were predictable, that would mean that what we all do couldn't change it. It would mean that the future was arriving on fixed rails and couldn't be steered.

Jesus Christ, what a miserable proposition!

Now, not everyone understands the distinction. They think sf writers are oracles, soothsayers.

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Unfortunately, even some of my colleagues labor under the delusion that they can "see the future."

But for every sf writer who deludes themselves into thinking that they are writing the future, there are a hundred sf fans who believe that they are *reading* the future, and a depressing number of those people appear to have become AI bros.

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The fact that these guys can't shut up about the day that their spicy autocomplete machine will wake up and turn us all into paperclips has led many confused journalists and conference organizers to try to get me to comment on the future of AI.

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That's a thing I strenuously resisted doing, because I wasted two years of my life explaining patiently and repeatedly why I thought crypto was stupid, and getting relentless bollocked by cryptocurrency cultists who at first insisted that I just didn't understand crypto. And then, when I made it clear that I *did* understand crypto, insisted that I must be a paid shill

This is literally what happens when you argue with Scientologists, and life is Just. Too. Short.

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So I didn't want to get lured into another one of those quagmires, because on the one hand, I just don't think AI is that important of a technology, and on the other hand, I have very nuanced and complicated views about what's wrong, and not wrong, about AI, and it takes a long time to explain that stuff.

But people wouldn't stop asking, so I did what I always do. I wrote a book.

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Over the summer I wrote a book about what I think about AI, which is really about what I think about AI criticism, and more specifically, how to be a good AI critic. By which I mean: "How to be a critic whose criticism inflicts maximum damage on the parts of AI that are doing the most harm." I titled the book *The Reverse Centaur's Guide to Life After AI*, and Farrar, Straus and Giroux will publish it in June, 2026.

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But you don't have to wait until then because I am going to break down the entire book's thesis for you tonight, over the next 40 minutes. I am going to talk *fast*.

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Start with what a reverse centaur is. In automation theory, a "centaur" is a person who is assisted by a machine. You're a human head being carried around on a tireless robot body. Driving a car makes you a centaur, and so does using autocomplete.

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And obviously, a *reverse* centaur is machine head on a human body, a person who is serving as a squishy meat appendage for an uncaring machine.

Like an Amazon delivery driver, who sits in a cabin surrounded by AI cameras, that monitor the driver's eyes and take points off if the driver looks in a proscribed direction, and monitors the driver's mouth because singing isn't allowed on the job, and rats the driver out to the boss if they don't make quota.

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The driver is in that van because the van can't drive itself and can't get a parcel from the curb to your porch. The driver is a peripheral for a van, and the van drives the driver, at superhuman speed, demanding superhuman endurance. But the driver is human, so the van doesn't just use the driver. The van uses the driver *up*.

Obviously, it's nice to be a centaur, and it's horrible to be a reverse centaur.

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There are lots of AI tools that are potentially very centaur-like, but my thesis is that these tools are created and funded for the express purpose of creating reverse-centaurs, which is something none of us want to be.

But like I said, the job of an sf writer is to do more than think about what the gadget does, and drill down on who the gadget does it *for* and who the gadget does it *to*. Tech bosses want us to believe that there is only one way a technology can be used.

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Zuckerberg wants you to think that it's technologically impossible to have a conversation with a friend without him listening in. Cook wants you to think that it's technologically impossible for you to have a reliable computing experience unless he gets a veto over which software you install and without him taking 30 cents out of every dollar you spend. Pichai wants you think that it's impossible for you to find a webpage unless he gets to spy on you from asshole to appetite

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This is all a kind of vulgar Thatcherism. Margaret Thatcher's mantra was "There is no alternative." She repeated this so often they called her "TINA" Thatcher: There. Is. No. Alternative. TINA.

"There is no alternative" is a cheap rhetorical slight. It's a demand dressed up as an observation. "There is no alternative" means "STOP TRYING TO THINK OF AN ALTERNATIVE." Which, you know, *fuck that*.

I'm an sf writer, my job is to think of a dozen alternatives before breakfast.

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So let me explain what I think is going on here with this AI bubble, and sort out the bullshit from the material reality, and explain how I think we could and should all be better AI critics.

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Start with monopolies: tech companies are gigantic and they don't compete, they just take over whole sectors, either on their own on in cartels.

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Google and Meta control the ad market. Google and Apple control the mobile market, and Google pays Apple more than $20 billion/year not to make a competing search engine, and of course, Google has a 90% Search market-share.

Now, you'd think that this was good news for the tech companies, owning their whole sector.

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But it's actually a crisis. You see, when a company is growing, it is a "growth stock," and investors really like growth stocks. When you buy a share in a growth stock, you're making a bet that it will continue to grow. So growth stocks trade at a huge multiple of their earnings. This is called the "price to earnings ratio" or "P/E ratio."

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But once a company stops growing, it is a "mature" stock, and it trades at a much *lower* P/E ratio. So for ever dollar that Target - a mature company - brings in, it is worth ten dollars. It has a PE ratio of 10, while Amazon has a PE ratio of 36, which means that for ever dollar Amazon brings in, the market values it at $36.

It's wonderful to run a company that's got a growth stock. Your shares are as good as money.

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If you want to buy another company, or hire a key worker, you can offer stock instead of cash. And stock is very easy for companies to get, because shares are manufactured right there on the premises, all you have to do is type some zeroes into a spreadsheet, while *dollars* are much harder to come by. A company can only get dollars from customers or creditors.

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So when Amazon bids against Target for a key acquisition, or a key hire, Amazon can bid with shares they make by typing zeroes into a spreadsheet, and Target can only bid with dollars they get from selling stuff to us, or taking out loans. which is why Amazon generally wins those bidding wars.

That's the *upside* of having a growth stock. But here's the downside: eventually a company has to stop growing.

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Like, say you get a 90% market share in your sector, how are you gonna grow?

Once the market decides that you aren't a growth stock, once you become mature, your stocks are revalued, to a P/E ratio befitting a mature stock.

If you are an exec at a dominant company with a growth stock, you have to live in constant fear that the market will decide that you're not likely to grow any further. Think of what happened to Facebook in the first quarter of 2022.

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They told investors that they experienced slightly slower growth in the USA than they had anticipated, and investors *panicked*. They staged a one-day, $240B sell off. A quarter-trillion dollars in 24 hours! At the time, the largest, most precipitous drop in corporate valuation in human history.

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That's a monopolist's worst nightmare, because once you're presiding over a "mature" firm, the key employees you've been compensating with stock, experience a precipitous pay-drop and bolt for the exits, so you lose the people who might help you grow again, and you can only hire their replacements with dollars. With dollars, not shares.

And the same goes for acquiring companies that might help you grow, because they, too, are going to expect money, not stock.

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This is the paradox of the growth stock. While you are growing to domination, the market loves you, but once you *achieve* dominance, the market lops 75% or more off your value in a single stroke if they don't trust your pricing power.

Which is why growth stock companies are always desperately pumping up one bubble or another, spending billions to hype the pivot to video, or cryptocurrency, or NFTs, or Metaverse, or AI.

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I'm not saying that tech bosses are making bets they don't plan on winning. But I am saying that winning the bet - creating a viable metaverse - is the secondary goal. The primary goal is to keep the market convinced that your company will continue to grow, and to remain convinced until the next bubble comes along.

So this is *why* they're hyping AI: the material basis for the hundreds of billions in AI investment.

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Now I want to talk about *how* they're selling AI. The growth narrative of AI is that AI will disrupt labor markets. I use "disrupt" here in its most disreputable, tech bro sense

The promise of AI - the promise AI companies make to investors - is that there will be AIs that can do your job, and when your boss fires you and replaces you with AI, he will keep half of your salary for himself, and give the other half to the AI company.

That's it.

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That's the $13T growth story that MorganStanley is telling. It's why big investors and institutionals are giving AI companies hundreds of billions of dollars. And because *they* are piling in, normies are also getting sucked in, risking their retirement savings and their family's financial security.

Now, if AI could do your job, this would *still* be a problem. We'd have to figure out what to do with all these technologically unemployed people.

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But AI can't do your job. It can *help* you do your job, but that doesn't mean it's going to save anyone money. Take radiology: there's some evidence that AIs can sometimes identify solid-mass tumors that some radiologists miss, and look, I've got cancer. Thankfully, it's very treatable, but I've got an interest in radiology being as reliable and accurate as possible

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