The Reverse Centaur's Guide to Life After AI

by Cory Doctorow

Whether you want to criticize, kill, or use AI, you have to get through the hype and uncover the real story. Start with labor: in automation theory, a centaur is a person who chooses to use technology to help them do the things that matter to them. A reverse centaur is a person who has been conscripted to serve as a helper for a machine, at an inhuman, machine pace: a driver made to deliver all day long, nonstop; a warehouse worker made to work without food or bathroom breaks; a programmer made to crank out impossible amounts of code. As Doctorow says: it's not enough to ask what the technology does - we have to understand who it's doing it for and who it's doing it to.

The intended audience for AI hype isn't the people who are forced to use AI. The AI show is a performance staged for bosses and investors. . Investment bankers claim AI will to be worth more than $16 trillion: a number that only makes sense if AI replaces vast swathes of the wage-earning human workforce. To justify that level of "value," every story about AI must be presented as inevitable, world-changing disruption. Even the tales of the robot apocalypse are a calculated attempt to bolster the fearsome power of AI.

Anything that can't go on forever eventually stops. When the AI bubble bursts, what will we salvage? Is there something in the wreckage that everyday people will find useful? In The Reverse Centaur's Guide to Life After AI - as he so successfully did in Enshittification - Doctorow recounts both how we found ourselves in this dire situation and how we can get through it, to a life "after" AI in which the tools work for us, not the other way around.

Genres: Nonfiction, Technology, Science, Audiobook, Politics, Artificial Intelligence, Business

240 pages, Paperback

First published June 23, 2026

About the author

Cory Doctorow is a science fiction author, activist, journalist and blogger — the co-editor of Boing Boing and the author of the YA graphic novel In Real Life, the nonfiction business book Information Doesn’t Want To Be Free, and young adult novels like Homeland, Pirate Cinema, and Little Brother and novels for adults like Rapture Of The Nerds and Makers. He is a Fellow for the Electronic Frontier Foundation and co-founded the UK Open Rights Group. Born in Toronto, Canada, he now lives in Los Angeles.

Reviews

[emily · Rating 5 out of 5]

‘A reverse centaur is a human who is conscripted into acting as an assistant to a machine.’

‘This centaur/reverse centaur distinction is the heart of the paradox at the heart of the debate about the usefulness of AI tools. When you find yourself surrounded by people swearing that a given tool is worse than useless and others swearing that it has madeo their lives easier and better, you can bet that the former group is made up of reverse centaurs who’ve had AI imposed upon them, the latter group is all centaurs who’ve gotten to make up their own minds about where, when, and how to use AI tools. The solution to the paradox is to stop thinking about what the gadget does, and pay attention to who the gadget does it to and who the gadget does it for. The important part isn’t the technical characteristics of the device, it’s the power relationships of the people who use the device.’

‘The social arrangements of technology are a choice, not an inevitability.’

‘Successor technologies to the cash register—like mobile phone attachments that let people process credit card transactions—allow creative workers to sell directly to passersby at art fairs, comic-cons, and flea markets. They enhance the welfare and improve the material circumstances of workers. The most important thing about the gadget isn’t what it does, it’s who it does it for and who it does it to.’

‘Inevitabilists will tell you a version of this story whose moral is, See, you take the good with the bad. They’re wrong. You don’t have to take the good with the bad. You can get the good without the bad. The difference isn’t to be found in what a technology does; it’s in what your boss uses the technology to inflict upon you. If you want to get the good without the bad, you need to switch from fighting technologies to fighting bosses.’

‘The IG app, for example, tracks everything from how quickly you scroll, what’s on the screen when you stop scrolling (or just slow down), even readings from your phone’s accelerometer—how you’re holding and moving your phone while you interact with their app. All this can be correlated with your location, the specifications of your device, and your other activities—the places you’ve visited recently, the places you subsequently visit, the things you buy, and the people you converse with.’

‘The fact that your technology tools spy on you means that the tech workers who make those tools can be rewarded or punished based on your usage.’

‘The current AI bubble is being driven by large tech firms’ need to tell a growth story to investors, which means that this AI has to be deployed in a way that reduces wages, because that’s the only thing that customers will pay enough for to make all those investors’ money back and more besides. What’s more, the mere existence of a widely accepted AI story can help suppress the wages of workers, even before AI is deployed. Workers who anticipate their imminent replacement by AI can be bullied into accepting worse conditions, dropping unionization demands, and taking other measures that shift the distribution of a firm’s profits from investors to workers.’

‘Never forget that you aren’t the target for AI hype—investors are. To the extent that anyone thinks of you when designing the publicity and marketing campaigns for AI, they are merely hoping that you will be visibly and loudly impressed.’

‘And—sometimes the most efficient way to convince your real target to take action is to act on someone else, someone with little power or agency.’

‘Remember, you aren’t the audience for AI companies’ hype. The real audience is the finance sector. To the extent that you are targeted by AI messaging, it’s in hopes of getting you to evince some kind of behavior that makes investors think there’s something to this AI business.’

‘Tech workers, especially those early workers, were often people whose lives had been transformed for the better by their experiences with networked computers, and many wanted to bring those benefits to the whole world’

‘Does AI really make coders more efficient? That certainly doesn’t seem to be the case for junior coders, whose “vibe coding” efforts might produce quick-and-dirty tools for one-off usage—for example, a script to reformat a single text file, once—but who lack the depth of experience to vet AI-produced production code for subtle errors that accumulate as “technical debt” in the enterprise systems they work on. Worse: without the hard-won experience of creatively solving a succession of programming challenges, these junior coders may never develop the requisite depth of expertise needed to do a thorough review of AI-generated code.’

‘In a world of giant media cartels, giving creative workers new copyrights to bargain with is like giving your bullied schoolkid extra lunch money. It does not matter how much lunch money you give Junior, the bullies are just gonna take that, too. Give your kid enough lunch money and the bullies will amass a fortune large enough to bribe the principal to look the other way. Keep giving that kid more lunch money and the bullies will be able to afford a global advertising campaign demanding more lunch money for all those hungry kids.’

‘Here’s a rule of thumb for tech policy prescriptions. Anytime you find yourself, as a worker, rooting for the same policy as your boss, you should check and make sure you’re on the right side of history.’

‘At a moment when AI algorithms are dictating who gets hired, who gets a loan, and who goes to jail (as well as who gets bombed), Hinton dismisses all of these concerns as not “existentially serious,” and tells us that we need to put all our focus on the coming day when one of these prize AI mares gives birth to a locomotive.’

‘AI is a bubble, but not all bubbles are created equal. Start here, though: every bubble is bad. The foundation of a bubble isn’t just “irrational exuberance” in which retail investors—you and me—unwisely gamble our life savings and lose everything. Bubbles all have winners, and these winners don’t come out on top by accident. Before a stock swindler inflates a bubble, they first acquire a lot of whatever the bubble is for, so they can sell it to us, and make out like a literal and figurative bandit.’

‘Every bubble is a transfer of wealth from savers to crooks. Every bubble is bad. We shouldn’t have bubbles. The pump-and-dumpers who inflate these bubbles should face criminal sanctions. Regulators should intervene to prevent bubble formation in the first place. That said: not all bubbles are created equal. Some bubbles pop and leave nothing behind. These are the pure fraud bubbles.’

‘Defenders of AI will often cite other technologies that were costly at the outset, like the web itself, as evidence that AI will soon solve all its energy and scale problems. But the web revolution was a decade of unbroken drops in the cost of servicing each new web user. In economics terms, the web had great “unit economics”—the cost of each web session fell and fell, even as the cost of getting on the web (from hardware to software to connectivity) was also falling.’

‘Not so with AI. Each generation of AI foundation models has been vastly more expensive to train and operate than the previous generation. Not only that, but many refinements in AI that are meant to improve accuracy and reduce “hallucinations” involve breaking a prompt down into multiple pieces and prompting an AI to respond to each prompt, turning that response into a new prompt, over and over again, to produce “chains of thought.” These are, to quote Ed Zitron, “dogshit unit economics.” AI gets more expensive every time it adds a user. It gets more expensive every time it adds a feature. It gets more expensive every time it improves. This is the opposite of the conditions under which the web attained liftoff.’

‘Companies are not training new foundation models because the old ones are so profitable that their owners have gobs of cash left over to make even better ones. Every AI company is losing money, and the bigger the AI company is, the more money it’s losing. The biggest AI companies are losing billions per quarter.’

‘The financing for new models is coming from investors, and those investors are making a bet that the AI they’re funding will be so good that employers can fire half their workers and replace them with AI, with the proceeds split between AI companies’ customers, and the AI companies themselves. Failing that, they’re making a bet that AI companies’ sales staff can convince employers to fire half their employees and replace them with AI that can’t do their jobs, and that no one will figure this out until after the AI companies’ investors have cashed out.’

‘This may seem like a paltry and trivial outcome from hundreds of billions of dollars and gigatons of planet-killing carbon, because it is. The serious environmental costs of AI will be borne by everyone on the planet, and all the animals and plants we share it with, for hundreds of years to come. Much of that harm is already locked in, and all we can do now is think about how we will mitigate it—how we’ll treat the zoonotic plagues, where we’ll house the climate refugees, how we’ll evacuate our low-lying cities, and how we’ll douse the wildfires.’

‘The economic costs of the AI crash will also be felt around the world, for a generation or more. Those harms are also locked in. You can’t give a third of the S&P 500’s value over to seven money-losing AI companies that energetically pass the same $100 billion IOU around and around without creating the conditions for a prolonged, brutal, global crash.’

‘Remember: all bubbles are terrible, but some bubbles are productive. The stuff that’s left behind when the bubble pops is salvage. Just because we deplore the waste that went into its production, that doesn’t mean we have to contribute to that waste by discarding this perfectly good remnant. There are plenty of uses for chatbots, too. Many, many people report that “conversing” with a chatbot is therapeutic. That’s easy to believe—A chatbot “therapist” is more like an interactive journal, one that feeds you back bland—but increasingly personalised—responses as you spill your guts to it.’

‘To put this in the context of AI art: AI art is uncanny because it has the seeming of intent without an intender, and it grows more meaningful the more a human infuses it with communicative intent. An AI therapist is a chatbot that you iteratively prompt and re-prompt, and the sentences in its replies to you are a higher- and higher-fidelity expression of the communicative intent you infuse into the sentences you feed it. An AI therapy session is a creative work of literature in which you are the principal author and the chatbot is a coauthor that makes successively refined guesses about what you want to hear based on your responses to its responses (to your responses to its responses).’

‘Some people have experienced “AI psychosis” in which they have led their chatbots into extremely destructive conversations wherein the chatbot fed and amplified dangerous delusions. At least one person killed themselves after such an experience.’

‘It’s because this all arrived as part of an investment bubble that was inflated by attacking workers of all kinds, and that stands to destroy the planet and the economy, that we are forced to take sides as either “anti-AI” or “pro-AI.” It’s fine to be “anti–AI bubble,” but it’s pretty silly to be “anti–statistical analysis” and “anti–machine learning” and “anti–automated inference.” Long after the bubble is gone, many of these tools will recede to the status of boring utilities, nurtured by open-source weirdos and a few ambitious startups. That’s not the problem. The problem is that all of today’s nonsense applications of AI will do lasting damage, separate from these perfectly useful utilities.’

‘There’s the obvious, world-threatening harm done by the gigatons of CO2 emitted by AI data centers to perform the redundant and wasteful training processes and to serve queries. Then there’s the world of labour. We’ll see lots of people fired—not because an AI can do their job, but because an AI salesman can convince their credulous bosses to fire them and replace them with an AI that can’t do their job.’

‘That’ll be bad enough. Not only will good people lose their jobs, but the rest of us will lose the value those people produced when they did their jobs. We’ll get bad chatbot advice, bad chatbot diagnoses, bad chatbot recommendations. And then, when the bubble pops, we won’t even have that. Companies will go bust. The data centers where these giant money- and power-sucking foundation models are housed will go dark. This will be even worse than having shitty AI doing important work badly—it will be a time in which that important work won’t be done at all.’

‘The job of a good AI critic is to help pop the bubble as quickly as possible, before the walls of all our institutions are filled with this digital asbestos that we’ll be digging out for generations. To be a good AI critic is to understand the material origins of the bubble, and to strike at the material factors that keep it inflated.’

‘I do a lot of things, but above all, I’m a science fiction writer. I’ve been selling SF stories since I was a teenager. It’s really fun to think about AI, to carry on outlandish thought experiments that challenge us to examine what we think of as intelligence, as agency, as morality. Imaginative exercises, whether undertaken as fiction or as computer code, open your mind to strange possibilities and exciting ideas.’

‘But thought experiments aren’t plans. They’re not predictions. The fact that you’ve seen movies and read books with superintelligent AI in them doesn’t mean that AI is real. It doesn’t mean that it’s likely. It doesn’t even mean that it’s possible.’

‘Many technologists have been inspired by science fiction to create interesting and useful things. The AI scientists who dreamed of better interfaces and came up with the techniques underpinning image generators and large language models did something incredible—But they haven’t invented an intelligent being. They haven’t set in motion the tools to conjure up a new god or demon. They haven’t even invented a tool that can do your job for you.’

‘But there is one thing that—AI bosses who are gunning for generational, dynastic wealth by transforming us all into AI-lashed reverse centaurs—don’t want you to know. That thing is this: the future is up for grabs. It is not inevitable. AI isn’t a genie that can’t be put back into a bottle. How we use AI is up to us. Whether we use AI is up to us. The future can be ours, if we never stop remembering that the most important fact about a technology isn’t what it does, it’s who it does it for, and who it does it to.’

[W.D. Clarke · Rating 4 out of 5]

Very good as far as it goes, especially on the economics and legal aspects of the ‘AI’ bubble + as it affects workers.

Also: the author writes with the kind of approachable clarity that makes this the ideal gift for your parents, your young adult children, any ‘civilian’ who wants to learn and think about ‘AI’ —and begin to talk back...

You will not have a good time with this if you think LLMs are anything other than fancy statistical prediction engines, that ‘Generative’ AI generates anything, really (vs. shuffles the deck chairs that others—human others—have made), and that ‘Agentic’ AI ‘agents’ possess, well, agency—or that there is no bubble, or that if there even is a bubble, there is real ‘value add’ to it (such as the miles and miles of fibre-in-the-ground-to-be-found in the wake of the WorldCom/dot-com debacle), which shall emerge when the bubble’s shake-out is complete.

I won't rehash the author’s bubble analysis here, but will simply recapitulate some of the interesting premises and concepts he employs to buttress that, viz.

— ‘the most important aspect of a new technology isn’t what the machine does, it’s who it does it for and who it does it to’.

— ‘Never forget that you aren’t the target for AI hype (investors are)’

— ‘the Byzantine premium’: ‘the extra value that investors place on an asset that they don’t understand’

— ‘day-old donuts’: AI tools we civilians can use are a money-losing sideshow to AI investors and pitch-men alike, function only to hype a social consensus that the ‘I’ in AI is a real thing, that ‘there’s a “there” there’

— ‘Centaur’ = human workers empowered to use technologies at their own discretion, to make their work (and work lives) better

— ‘Reverse Centaur’ = human workers serve needs of automated machines, reduced to ‘human in the loop’ status’

— ‘innovation’ is usually just ‘disruption’ (sold to companies as ways to reduce human labour costs)

— ‘automation blindness’: human workers subjected to automated processes eventually lose the cognitive skills needed to assess their outputs (to be that human-in-the-loop)

— ‘accountability sink’: when reverse centaurs/humans-in-the-loop are blamed for AI failures, rather than the AI or executives who purchased/implemented AI solutions

— ‘vocational awe’: ‘the process by which employers exploit their workers’ sense of duty to the people they serve to get them to accept brutal working conditions’.

— ‘GIGO’ (‘Garbage In, Garbage Out’): Errors in computer output remoreselessly rise with errors of inputs (‘ the coprophagic AI problem: when you feed a bot on botshit, you get something AI researchers call “model collapse,” a dramatic reduction in the quality of the guesses the bot makes’)

— ‘personalized pricing’: ‘Weaponized spying’ (‘when it’s done to fix the price of goods, it’s called “surveillance pricing.” When it’s done to fix the price of wages, it’s called “algorithmic wage discrimination”.’)

I am sure I missed a few! Oh, and:

— ‘normal technology’: ‘A thing that creative people and others use, sometimes, when it makes sense, with mixed results, but sometimes good ones.’ (What AI could one day be if burst the economic bubble/drop the terminology hype)

Art: ‘what happens when an artist has a big, numinous, irreducibly complex feeling in their mind, which they infuse into some artistic medium—a book, a song, a dance, a painting, a photograph, and such—in the hopes of making a facsimile of that big, numinous, irreducibly complex feeling materialize in the minds of people who experience their art’.

I could quibble with that definition, but agree with its sentiment: statistical word-prediction engines do not have thoughts, feelings, or the capacity to make art

[Booksblabbering || Cait❣️ · Rating 4 out of 5]

Cory is always able to take daunting topics that impact every facet of all lives into something accessible with an underlying humour to balance out the doom.

This short yet packed non-fiction explains how technology is treating human workers. He argues that instead of AI serving as a helpful tool, many companies use AI to force humans to work at impossible, machine-like speeds.

A Centaur is a human who uses technology to boost their own skills.
A Reverse Centaur is a human being treated like an assistant to a dominant machine.

One example that stood out to me: programmers are known for using AI to generate code. However, if they are forced to spend their entire day fixing, checking, and reviewing endless lines of bad AI-generated code, they become reverse centaurs. The machine causes more work than it saves.

Importantly, it is always the WORKER’S fault for any mistake the AI makes that they don’t pick up. Why are we pinning responsibility on the person when it’s the machine failing?

I appreciated that this doesn’t outright villainise all aspects of AI, but warns of the preconceptions - good and bad. As well as the reliance; the impact on capitalism, productivity, and workers; and the impact on the arts.

I wish we got more about the impact of AI on the environment, as well as how to push back against what is becoming normalised. Especially as Cory acknowledges the certain failure and generational financial loss, and the devastating consequences on climate change.

Overall, a digestible guide to how mega companies use AI to shorthand their employees and disregard the future effects.

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[Edie · Rating 5 out of 5]

I have been telling everyone all about my plans for a solarpunk summer. (In case you haven't heard yet, get ready for Solarpunk Summer '26! Now that you know, you will start to see it everywhere.) Cory Doctorow's latest is exactly the book to kick it off. The Reverse Centaur's Guide to Life After AI explains the AI bubble, coming collapse, what we can do about it, and what we should use from it. Solarpunk is about using technology in sustainable ways for collective flourishing. Doctorow's description of how to use AI appropriately explains the concept in detail with concrete examples. This book explores the financial, social, and ethical quandaries we find ourselves collectively wading through as we navigate the AI minefield and gives suggestions for paths forward. I truly appreciate the author's approach - AI is not the problem, the way we choose to use it and leverage it is. The financial house of cards will collapse and when it does, there are bits and bobs to save. This is the book I will be thrusting into people's hands when I talk about the stock market and alternative investments. (Which I do much too often because as much as I promise myself I will stop giving unsolicited advice, I can't seem to help it.) This isn't a doom & gloom book. It is a book about what to do while and after things go boom. Thank you to Cory Doctorow, Macmillan Audio, and NetGalley for the audioARC.

[David Dayen · Rating 5 out of 5]

Fantastic. They won't let me rate it because it's not out yet. Buy this, it's the most succinct expression of what AI portends and how it should be thought about.

[Mizuki Giffin]

This was phenomenal. It took complicated economic, technological, philosophical, and labour dimensions of AI and presented it in a way that was easy to understand, boiled down to the thesis that AI isn't made for us as users, but to investors for capital. I listened to the audiobook and the passion in Cory Doctorow's voice is infectious. While this is an infuriating topic, I also found myself laughing out loud as Doctorow highlights the absurdity of the AI hype we're living through. I couldn't recommend this more. 

[Cam Waller · Rating 5 out of 5]

shook

[Cathy · Rating 5 out of 5]

This was really excellent. A comprehensive, well-supported response to the claim that “AI is here no matter what so we either fall in line or get left behind.” This narrative of inevitability, the warning of a world in which AI replaces all workers, is intentionally amplified in order to lure investors to continue feeding into a bubble that is destined to burst. Doctorow breaks down the hustle, the dubious ways these companies will count a user’s forced scrolling past an AI summary as “engagement,” creating inflated numbers that they can then pitch to investors, even if it’s all BS. It doesn’t matter that all these sites are now unusable, because the target of every pitch is the investor, not the user experience.

Doctorow is not anti AI, but anti the unregulated capitalism that enables unmitigated growth at any cost. He argues that once the bubble bursts, we will be able to determine how AI can actually be useful (an example he provides is of refugees being able to communicate more effectively with people in new countries thanks to improved translation services). But until that happens, it’s so much harder to focus on potential positives because we are all drowning in endless slop.

Anyway, thank you to my friend Jane for the rec and thank you to Libro.fm’s Librarian ARC program for the early copy.

[Masha Kazankova · Rating 5 out of 5]

AI is not inevitable, and as with application of any technology, it’s important to understand who it does things to and who it does things for. Another example of great tech criticism that is quite accessible and focused on the wellbeing of the many, rather than the sickeningly high capital gains of the few.

[Matt Vaughan · Rating 3 out of 5]

I’m an AI skeptic, but I’m also a mature thinking person, so I don’t need a book on the topic to align perfectly with my point of view. That said, there is a lot in this book that I do agree with, and some interesting ideas that came from it, like automation blindness, and good results from LLMs being similar in likelihood to slot machine payouts.

The areas where I found the book less than convincing do stand out, though:

- There’s a section explaining how restricting LLMs from training on scraped copyrighted data wouldn’t help anyone and would only make it harder to have search engines, but I found it unconvincing. If I write a book and software comes along and swallows it up to make use of it for its own purposes, that feels outside of the agreed-upon understand of books. Just like I don’t want to read something written by a non-human, I don’t want a non-human ingesting my work. I want to connect with actual living people!
- One of the main arguments in favour of some LLM usage in the future is the improvement of transcription technology. But we’ve had transcription software for ages, and it has improved over time, so what makes this AI and not software? This is one of the sticky points with vaguely describing a whole assortment of technology as ‘artificial intelligence’, as anyone who has spent time around computers in their lives have already used versions of this sort of thing.
- The author says that chatbots acting as therapists are good and helpful, and I could not disagree more. Chatbots rely on tricking people into thinking there’s an intelligent being on the other side, but it’s actually just a prediction algorithm pumping out what they think should come next. It can be a neat trick, but it’s also misrepresenting the technology in a way that is misleading to people, and it’s one of the ways I’d like to see AI brought to heel. Do not pretend to be a being when you’re code.
- The other uses cited for using AI now are silly. One example is an AI summarizing DND campaigns and generating images of what happened, but the errors it creates are mentioned as a fun aside and not a fundamental flaw. Accepting hallucinations is so strange, why would we use a calculator if it was known to sometimes give wrong answers?
- The other example was a human rights organization using AI to arrange data. Okay, but didn’t you just say that hallucinations are real and unavoidable? Why would a group with a role that significant in protecting vulnerable people use a technology with such potential for failure?

This is a 3.5/5 for me.

[Nathania Calae · Rating 4 out of 5]

I think many of us are quite concerned with the future of AI. Questions like: now what; how do we go from here; who does this affect? Etc etc!

Look no further because this book has eased my anxieties whilst reminding me how dystopian our REALITY is lol. To preface: I recommend reading this author's 2025 release mainly because it works perfectly in tandem with this one. Thankfully, I listened to a podcast all about it, so I already had a basis for his ideas. I will say that this book isn't saying the most revolutionary things HOWEVER I do think that it is incredibly important, relevant, and most of all human. That's literally all anyone can ask for right now. I appreciated it, especially in audiobook form because of the authors vocal mannerisms (if that makes sense). This book makes sure to keep the readers engaged through its examples, definitions, and examinations which lends the book to be quite ‘bingeable’ and enjoyable, especially since it's such a short novel.

I really recommend this and I honestly might go back to read his last release!

Thank you to NetGalley and the publishers for giving me an arc copy to review!!!

[Christina · Rating 5 out of 5]

Last year, I read Adam Becker’s More Everything Forever: AI Overlords, Space Empires, and Silicon Valley's Crusade to Control the Fate of Humanity, which looked into some of the bizarre beliefs and philosophies that come from Silicon Valley. After reading Cory Doctorow’s The Reverse Centaur’s Guide to Life After AI, it all makes a lot more sense. I thought, after reading Becker’s book, that these fringe ideologies were essentially cultish; the rich tech bros pushing them had enough money to start personal think tanks filled with yes men, and were micro dosing far too many recreational drugs. (And that’s probably still part of it.) But Doctorow’s reason makes much more sense, so it’s the most probable: huge amounts of money.

It all comes down to convincing investors than these seven large tech firms are not yet mature firms (which they really are), but still dynamic, growing firms, like they used to be. Investors are willing to pay more for stock in growing firms, and they’re really willing to pay a lot for firms that are growing in what would seem leaps and bounds with a big payoff at the end. This allows these companies to spend beyond their actual profits. Since some of them are not making much profit, or are otherwise loosing money, this only adds to the drive to promote the story of never ending growth. Hence, the never ending, constantly changing, AI hype. Hence the wild stories about AI taking over the world, and the constant fear-mongering.

Doctorow isn’t anti-AI. He uses it himself, and sees plenty of areas where it could be helpful. He is especially bullish on the small AI programs, the ones that don’t come with a surveillance corporation attached to them that sucks up users’ data, is working hard to eat up resources, is producing outrageous amounts of pollution, and is trying to destroy as many jobs as possible. Those companies are driving an AI bubble, which Doctorow is very much against.

Reading this book made me think of a scene from the film The Big Short. Mark Baum, played by Steve Carell, has traveled to Florida to check out the mortgage boom for his investment firm. After taking to an erotic dancer who has several mortgages as speculative investments and has used her mortgages as collateral to buy more mortgages, he calls his firm. “Yep! It’s a bubble!”

AI may end up as world-changing as electricity or the steam engine, but it’s looking more likely it will be a lot less revolutionary than that. Most companies who have fired vital personal in the hopes of replacing them with AI have had to rehire. Self-driving cars are still not here. Doctorow relates the infamous story of one that killed a person, which led to the revelation that 1.5 engineers had to operate it remotely for it to be ‘self-driving.’ Same for those stores Amazon claimed wouldn’t need cashiers or self-checkouts; AI was supposed to instantly know what you took home and charge your account automatically. Again, it was people, this time in India, using lots of CCTV cameras, because AI couldn’t do that. The stores eventually closed, but the hype bought more investment. It seemed like a business failure on the surface, but there was a method to the madness, and it worked.

Doctorow explains all this in a straightforward manner that’s easy to understand. He cuts through the hype, the BS, and the gaslighting with simple, clear logic in an accessible style. (I read this entire book in two days.) Unlike some other books that are AI skeptical, he closes with how it could be better, and how we all need to stop believing both the hype and doom. (It’s a false dichotomy; they both inflate the bubble.) The future is not inevitable. Anybody who tries to convince you otherwise stands to profit in some way from the status quo.

[Dan Trefethen · Rating 5 out of 5]

I love reading Cory Doctorow. I hate reading Cory Doctorow.

I love reading his work because he is so well informed and clear-eyed about the effects of technology on human society, and what those in charge of technologies are trying to accomplish.

I hate reading his work because he pulls back the curtain on how exploitative, grubby and money-hungry a lot of the technology world is. In the old maxim, it's "follow the money" if you want to know why things are happening the way they are. He told us about the inevitable degradation of services in his book "Enshittification", and in this one he shows how much the AI bubble is a hype intended to keep investors investing huge sums in enterprises that cannot all be sustainable.

Cory loves LLM-based AI when used by humans to support human endeavors (humans as centaurs, using machines to enhance our capabilities) and hates using LLM-based AI to slave humans to support machines (as in large warehouse distribution centers), when we become 'reverse-centaurs'.

He's not anti-AI, he's anti-AI bubble, where the AI companies are making outlandish promises to reverse-centaur humans (or remove them altogether) to justify the huge growth prospects they need to keep investors investing. You don't need the AIs to be better at a job than a human - you just need to convince the boss that the AI can do it. So far, there's little to no evidence that this works, not with the AI we've got today - companies get egg on their face and have to hire back employees. (Today's news had a story about Ford Motor Company hiring back 350 'graybeard' engineers to train young engineers and the AI systems they were using that were screwing up.) Meanwhile, thousands of jobs get trashed and lives thrown into disruption.

Cory is afraid that by the time the bubble bursts (and with 35% of the US stock market held by seven companies involved in AI, it's bound to happen), so much of the damage will be irreversible.

That's why I hate reading Cory Doctorow. I hate to think that he's right. But I can't really refute his conclusions, not in a substantially meaningful way.

He concludes the book thusly:

"AI isn't a genie that can't be put back in the bottle. How we use AI is up to us. Whether we use AI is up to us. The future can be ours, if we never stop remembering that the most important fact about a technology isn't what it does, it's who it does it for, and who it does it to."

[GONZA · Rating 2 out of 5]

As much as I'd like to blindly believe what Doctorow says—especially regarding concerns about artificial intelligence—I got the impression that someone had kidnapped him and forced him to write this complacent book under torture. But I'm surely wrong, and everything will turn out just fine.

Per quanto mi piacerebbe credere ciecamente a quanto dice Doctorow soprattutto nei riguardi delle preoccupazioni sull'intelligenza artificiale, ho avuto l'impressione che qualcuno lo avesse rapito e lo avesse obbligato a scrivere questo libro compiacente sotto tortura. Ma sicuramente mi sbaglio e andrá tutto benissimo.

[Mason Raymundo · Rating 5 out of 5]

Made me audibly laugh more than once. Totally diffused some existential fears I had about big tech and AI. Book sort of makes them out to be charlatans which I enjoyed. If I had to complain I’d say the book goes on a pretty big tangent about AI art and how it affects creators which I just don’t care as much about.

But I really like this authors style and I’m definitely gonna read enshittification next

[Bryan · Rating 4 out of 5]

This is a very good perspective on the current AI bubble. In past bubbles there have been things that are useful after the bubble bursts. We should think about how the smaller language models maybe used after the hype. Or will building increasingly expensive models be the way of things moving forward? It seems like that will have to stop at some point.

[Dávid L · Rating 4 out of 5]

Sok benne az igazság, de én ilyen szöveget nem adnék ki a kezemből. Értem, hogy ez nem a Fordulat folyóiratban jelent meg, de azért lehetett volna egy kicsit árnyaltabb. Sokszor kijön, hogy balos gondolatok ellenére kulturálisan elég konzervatív a szerző, valahogy úgy mint a Magyarországon egyre felkapottabb Novara media.

[Lucas Martin · Rating 5 out of 5]

Easy read with great information about what's wrong with AI, how to be an effective critic, and what to expect when the AI bubble bursts

[Avery · Rating 3 out of 5]

Disclaimer- most of this book makes the assumption that (super)human-level artificial intelligence is not possible within the near future. In this framing, most conversation about it doing so exists to serve solely to further the interests of those invested in the AI bubble. I don’t know that this assumption is as obvious to me as it is to Doctorow, and if you strongly disagree with it, then there’s probably not much in this book for you.

I don’t think I’d have enough patience to work at the EFF, and I’m grateful that there are people like Doctorow who can push on these issues. The legal distinctions made in the book frequently felt inconsistent to me, but I think it’s possible that this is more of a me problem than the book being inaccurate. I just can’t get over “code is speech” being a better reason than “secure crypto is secure” for the government to allow the use of cryptography.

There's a bit that I might need to reread that explains how, while the training inputs may have been stolen, and that theft is bad, the results derived from the theft are fine. This is sort of weird to me. I guess code/creative works are protected, but not “objective facts”, where all of those terms are super vague. I feel like it would follow that if I could get my hands on the model weights (complex but objective statistical facts about the inputs) for Mythos/Opus/etc then I should be able to legally publish them in the public domain? An avenue left unexplored by this book.

One of the book’s ideas for a path through the AI morass is that copyright only applies to works of *human* creativity, and so the result of a prompt should automatically be in the public domain.

This is pretty compelling for stopping the reverse-centaurization of the workforce, but some of the analogies given didn’t resonate with me. Some amateur human taking literally whatever photograph automatically gets copyright for it, but someone who decides to train a monkey to take a selfie doesn’t? The monkey selfie is clearly still an intentional piece of art made by the human who decided to get it to press the button. It's literally a creative human work.

It seems like it’s hard enough to draw a line here that it would be relatively unlikely, without an enormous effort, to draw the line that the prompted input isn’t enough to qualify the result as art. After all, the photographer didn’t place all the pixels, they just pointed their lens at something and pressed “submit” on the camera. Barring that, we might still end up with reverse-centaur employees tasked with tweaking just enough pictures on the outputs to qualify it as human.

Still, I think it’s a valuable endeavor to attempt to develop the conversation here past “pro” or “anti” AI into something a little more nuanced. We can admit that the recent AI developments can be useful for some things some times without saying that all of the ways they can be used would be good for humans. We can think about how to think about their usage such that they don’t destroy society. It’s hard to maintain enough hope that any of this will be possible, given the incredible resources on the side of the tech companies and investors here, but thank you to Doctorow for tirelessly pushing.

[Jesper · Rating 4 out of 5]

I always enjoy listening to Cory Doctorow rant about technology and society and all the problems with them, and this book about the current AI bubble was no exception. The fact that most of the content wasn't really new information to me or that some of the arguments rely more on anecdotes and colorful analogies than detailed data does not really detract from that enjoyment, but it does make me a bit wary to not take some of the conclusions too seriously. Don't misunderstand me: I absolutely agree with the many harms caused by AI that this book talks about, but I'm not as eager as Doctorow to dismiss some of the claims about the capabilities of AI models (and the subsequent dangers of those) yet.

One thing that listening to this book did make me change my mind on is on the AI copyright question. Doctorow makes a pretty convincing argument that the way AI models are built does not meaningfully rely on copyright violations, and that making copyright law stricter to prevent training AI models would cause much more harm than good. There are more than enough other reasons to oppose continued AI rollouts that have more solid backing than copyright.

Now, let's see how much longer we can keep inflating this balloon before it pops.

[Melanie Duitsman · Rating 3 out of 5]

3.25⭐ for me.

I listened to the audiobook version of this book.

This was my first Cory Doctorow book. I read/listen to pretty much anything. I do have to admit the work of art on the cover was intriguing to me. It was definitely something that caught my attention.

The subject matter was interesting to me as well. The way the information was presented though was very scattered in my opinion. It was like the mind of what I imagine someone with untreated ADHD to be like. I am not a certified physician or qualified in any capacity to make that call. I have even wondered if I have ADHD at various moments in my life but I digress. I wonder if I would have had a better experience had I read the e-book instead of listened to the audiobook.

There were parts that I liked though. The author seemed to be well researched on the subject matter. There were some moments that made me actually laugh out loud. For the subject matter it was the perfect length, 4 hours. Thank you NetGalley & the publisher for the ALC in exchange for my honest review. Would I recommend it? I already have. Would I read or listen to another Cory Doctorow book? Maybe. Enshittification sounds interesting. Tata for now!💖

[Steadycamscott · Rating 4 out of 5]

I ripped through Cory’s other book Enshittification so when I discovered he wrote about the Ai boom, it became my most anticipated book of the year. (Pun intended).

Like his previous book he articulates so well why this craze is happening. This extends to what LLMs can do, what it cannot and who’s profiting on the wild claims. Labor plays a big factor in the book unsurprising. Plus the book is funny as well as interesting. I chuckled a bit at the analogies of chatbots being slot machines.

It definitely feels like an extension to his previous book, but the last two chapters really focuses on the tools local models can provide once the dust settles and the stockholders move on. It’s both fair as it is critical to the tech conglomerates that cultivated this technology.

[Rose · Rating 4 out of 5]

This was informative about the problems with AI (and some circumstances where it can be useful). I think the most important takeaway is this: who is AI doing things for and who is AI doing things too? Doctorow posits these as being the keys to using AI responsibly, and I think that makes a lot of sense.

I received a free ALC for library employees from Libro.fm.

[Theo Moore]

If u can find me a tech writer who is as funny, compelling and readable as Cory Doctorow I’ll eat my hat

[Ikra Anwar · Rating 5 out of 5]

Love this guy. I think maybe he underestimates how good and useful AI can be but his constant focus on individual humans and how things affect workers makes this a fantastic read.

[Kerri D · Rating 4 out of 5]

I learned a lot about why and how AI in ways I didn’t think about. Not sure I like it tho. 3.5

[Dan P · Rating 5 out of 5]

This is the perspective we're all missing on the AI bubble. Cannot recommend this enough! Compelling, realistic, and yet still somewhat optimistic, like the best of Cory's work.

[Kate Smith · Rating 4 out of 5]

4.5 stars
Doctrow was able to express and demonstrate the issues I’ve been having with how AI is being implemented extremely well.

[Lance Eaton · Rating 4 out of 5]

I supported Doctorow’s Kickstarter for the audiobook, The Reverse Centaur’s Guide to Life After AI , because I believe deeply in Doctorow’s work and ethic around publishing but also I regularly his work because feels like an inoculation against the tech bro BS that surrounds so many conversations about technology. The book continues his work and connects directly to Enshittification: Why Everything Suddenly Got Worse and What to Do About It, Chokepoint Capitalism: How Big Tech and Big Content Captured Creative Labor Markets and How We'll Win Them Back, The Internet Con: How to Seize the Means of Computation, and How to Destroy Surveillance Capitalism. In many ways, it feels like the AI-specific version of the same larger project: look past the gadget, look past the hype, and look at the larger techno-social capitalist system that decides who benefits and who gets used up.

That is Doctorow at his best. He does not treat AI as magic, or as an inevitable apocalypse, or as a neutral tool that just happens to exist outside power. He keeps asking the better question: who does this technology do things for, and who does it do things to? That centaur/reverse centaur distinction is the book’s frame. There is a real difference between a person choosing a tool that helps them do their work and a person being forced to become the human assistant to a machine that is ultimately being used to de-skill, discipline, or replace them.

That nuance is appreciated given that the AI discourse feels stuck between two unhelpful poles: AI is the future and we should all worship it, or any use of AI is automatically horrible, limiting, and meaningless. To my delight and appreciation, Doctorow is much more interesting than that. He is deeply skeptical of the AI bubble, of the promises by tech bro trillionaires, of the sales pitch that AI will become the next employer revolution. And he leaves space for smaller, useful tools: voice-to-text, transcription, image manipulation, local models, things that are as he tells us boring in the best way. I was using voice-to-text to gather my own thoughts for this review, so that point felt especially relevant. There is something here. It just is not necessarily the thing being sold to us.

In this book, he does go into copyright, which some of you may know, I have lots of thoughts about given my professional background. Given how much of my own work has been in and around copyright, knowledge production, and AI, I found Doctorow’s argument both clarifying and affirming. He reinforces what I have thought for a while: AI itself does not challenge copyright in the way many people want it to. If we think it does, we may be misunderstanding copyright and misunderstanding who copyright usually serves. It generally does not serve creative artists. It often serves corporations.

Doctorow’s takedown of “copyright will save us from AI” is one of the strongest parts of the book because it moves the conversation away from a tempting yet inadequate answer and toward labor, bargaining power, ownership, and control. That is a harder conversation, and it is also the more honest one. A new copyright framework around AI training sounds appealing until you remember who usually owns, controls, and exploits copyright. If the solution is one more right that creators can be forced to sign away, then it may not be a solution at all. Ultimately, there’s not a clear pathway that will actually be successful to trying to end or dismiss AI on copyright claims. In many ways, that makes sense. It is not copying and as soon as you get into the claim that works “inspired’ by copyrighted artists, you largely collapse a whole bunch of possibilities about how we as humans learn (hint: we copy a lot until we can build from our insights).

Doctorow’s chapter on AI’s role in art does not just throw all of AI away. He is skeptical, rightly, of someone entering a prompt, accepting whatever the machine gives them, and putting it into the world without much thought or meaning-making. But he also recognizes that art has always been entangled with technology. To say this new technology can have no role in art feels too heavy-handed and historically shortsighted. We have had versions of this conversation before, and we are usually wrong when we insist that a new technology cannot possibly matter to art.

An interesting idea can be found and named in Doctorow’s work. The more we get sucked into the fetishizing, demonizing, or aggrandizing the narrative (even in from a critical lens), the more power we actually give over to it. It’s like it’s Pennywise, feeding and growing bigger on our fears. Every time we get sucked into that coversation, we’re feeding the beast. It’s not explicit but does emanate from the text.

Where the book gets harder for me is the “guide” part. Doctorow diagnoses the problem really well, yet he doesn’t really guide us through it beyond “thinking”. He points toward unions, worker control, co-ops, better social arrangements, and creative workers resisting becoming reverse centaurs. It does signal possibilities. He discusses the Writers Guild successful rejection of AI, but they are a class of workers with unusual leverage compared to the vast majority of people being pushed into reverse-centaur conditions. A lot of people do not have the agency, solidarity, money, time, or infrastructure to resist.

And even beyond the workplace, a lot of consumers will choose what is cheaper or faster because the system is designed that way. We see it in self-checkout. We see it in online ordering and delivery. We see it in the way convenience gets framed as individual choice. He doesn’t go so far to label those seeking convenience as villains, rather explains as how they may be creating pathways that lead to their own exploitation.

Knowing that these issues permeate AI as many of our other digital systems does not quite empower us.

I felt something similar with his discussion of agentic AI. Doctorow is right that agentic AI, especially as a commerce fantasy, is probably a dead end. The idea that we will all have bots comparison-shopping, negotiating, and improving outcomes for us runs straight into the reality that companies will use their own systems to counter ours, block transparency, and prevent real enrichment. In a country with no meaningful federal data protection laws around consumer data, that seems incredibly likely.

Still, I am not entirely convinced that means agentic AI has no value. When I use these tools, I am often approaching them less through the lens of capital and commerce and more through tinkering, exploring, and trying to do things I could not easily do before. That may not be the domain of this book, and maybe it is not Doctorow’s purpose here, but it just feels like a limitation. The critique of the investment pitch is strong while the sense of what individuals might do with these tools outside that pitch feels thinner. Of course, that does make sense of the book and its focus; it’s just his handling of agentic AI doesn’t have the same nuance that generative AI does (which makes me wonder if he has actually played with it).

Doctorow makes a persuasive case that the AI bubble is built on several houses of cards: financially, technically, and rhetorically. He is also right to push back against the glamorous superintelligence conversation when the real harms are predictive policing, wage theft, surveillance pricing, deepfakes, misinformation, and the redistribution of money and power upward. The obsession with whether AI is sentient or whether it will overpower us is such a distraction. The small, nimble, insidious uses are the ones most likely to creep in while everyone is looking elsewhere.

I finished the book asking, okay, what am I to do with this? If I am in a workplace where AI is being forced down my throat and I do not have meaningful ways to resist, what are my realistic options? How do we address these systems in ways that are thoughtful and not exhausting? Doctorow warns about the damage that could happen before the bubble bursts, and about the economic disaster that may follow, but the book does not really guide us through that. It gives me a better map of the trap without a better toolkit for living inside it.

That is not entirely fair to put on this book, and I know it is not fully Doctorow’s project. I deeply appreciate his analysis, his open access commitments, his Creative Commons practice, and the consistency of his work. I keep listening to his books and funding his audiobook Kickstarters because his voice is invaluable. After Enshittification, The Internet Con, and now this, there is also a slightly repetitive quality. Repetitive, informative that is not always breaking new ground. Some examples and arguments recur because they are central to his framework, but in this book, that repetition sometimes makes the limits of the “how” more visible.

Regardless, The Reverse Centaur’s Guide to Life After AI is valuable. For Doctorow fans, it is another strong dose of clarity. For people who have not thought much about AI, it may be genuinely useful. And for people who are hypercritical of AI, it gives permission to have a more nuanced view: reject the bubble, reject the exploitation, reject the bosses trying to turn workers into reverse centaurs, but do not pretend every tool is meaningless just because the industry around it is rotten.

Doctorow is at his best when he is slicing through the capitalist approach to technology while still recognizing the individual or collective value (but not “Value”) of these tools. That is the strength of this book, even when it falls short as a guide. It helps clarify what AI is, what it is not, what is being sold to us, and who is likely to pay the cost. I just wish it left me with a clearer sense of what comes next.

[danah · Rating 5 out of 5]

Cory does an excellent job unpacking why you can both like AI and hate the political-economic project of AI. When AI haves you superpowers, you get to be a centaur. But when you are forced to bow down and be exploited by those who deploy AI to minimize your value, you are a reverse centaur. This is a super accessible and snarky book.