Tech journalist and science fiction author Cory Doctorow is back with a provocative new book, The Reverse Centaur's Guide to Life After AI, which serves as a follow-up to his earlier work on enshittification. In a recent interview, Doctorow did not mince words about the artificial intelligence industry, calling it "the money-losingest thing our species has ever done." He argues that the AI bubble is fundamentally different from previous tech bubbles and will leave a mixed legacy.

The Material Reality of AI

Doctorow defines a "centaur" as a human augmented by technology—like a radiologist using AI to spot tumors. A "reverse centaur" is the opposite: a person reduced to a mere appendage of a machine, such as an Amazon delivery driver monitored by AI cameras. The AI industry, he says, is intent on creating more reverse centaurs, not empowering workers. This distinction is key to understanding why some workers embrace AI while others resent it.

He points out that the capital expenditure on AI globally has reached $1.4 trillion, yet the sector only generates about $50 billion in annual revenue. “Every AI customer loses money for the company, every use of AI by that customer loses money for the company, and every generation of AI loses more money than the last one,” Doctorow notes. This is in stark contrast to the dot-com bubble, which left behind useful infrastructure and a generation of skilled programmers.

The Fantasy of a World Without People

Doctorow argues that AI's appeal to business and political leaders lies in a deep-seated fantasy: a world without people. “Hell really is other people,” he says, explaining that powerful people find it galling that workers can't be replaced by compliant machines. This fantasy drives mass layoffs and the deployment of AI in government and corporate settings, even when the technology is not up to the task. He cites the example of Amazon's "Just Walk Out" stores, which were initially powered not by AI but by human workers in India watching camera feeds.

The author is not anti-AI per se; he uses local models for transcription and proofreading and praises tools like Whisper and Copilot when used appropriately. However, he warns that the current hype is unsustainable. “The bubble doesn’t want cheap useful things. It wants expensive ‘disruptive’ things: big foundational models that lose billions every year.”

Historical Bubbles and Their Residues

Drawing parallels to the dot-com crash, Doctorow suggests that the AI bubble will leave behind productive residue: cheap GPUs, open-source models, and a pool of skilled applied statisticians. He notes that DeepSeek, a Chinese spin-out, created a powerful model with just $6 million, causing a massive market sell-off. “If you’ve got cheap hardware and you’ve got applied statisticians, you’ve got these open source models and you’ve got a technology that fundamentally is interesting and has done useful things—that’s a better setup than one in which we’re all running around arguing about whether the word-guessing program is going to wake up, become God, and turn us into paperclips.”

But he warns that the social reception of AI is historically anomalous. In the past, workers smuggled the web into workplaces; now, bosses force workers to use AI against their will. “That’s the difference between the words on the Greek temple, ‘Know thyself,’ and your boss shining 16 cameras in your face and going, ‘I know you better than you do. And by the way, I think you could work an extra hour a day without breaking a sweat.’”

Striking at the Roots

Doctorow's solution is not new copyright laws—which he argues would only benefit big media companies—but labor law reform. He points to Hollywood screenwriters and actors who beat AI by sectoral bargaining, and suggests extending that right to all workers. “The only people who’ve ever beaten AI are the Hollywood screenwriters and actors. And the reason they were able to beat them is because uniquely, among workers in America, they are exempt from the Taft-Hartley Act‘s prohibition on what’s called sectoral bargaining.”

He also criticizes the narrative that AI will destroy all jobs. “I think we have to distinguish between the AI doing your job and the AI being incapable of doing your job, but your boss is such a sucker that he fires you and replaces you with the AI anyway. There’s infinite evidence for the second one.” He challenges AI executives to declare whether they would personally trust an AI-driven nursing home in their old age.

Useful Applications Amid the Hype

Despite his criticism, Doctorow sees genuine potential in AI for specific tasks. He uses a local model to catch typos in his blog posts, and his friend Patrick Ball of the Human Rights Data Analysis Group employs AI to prioritize cases for the Innocence Project. “It’s not like they’re asking the chatbot to write a brief for them, but this is a hugely important function, and it is getting innocent people out of prison,” Doctorow says.

The author concludes that the AI bubble will burst, but not before causing significant economic damage. He advises readers to go "long on laser tag arenas"—a joke about repurposing data centers—and to prepare for a future where the technology's useful components become cheap and accessible. The key is to ensure that the power dynamics shift away from monopolies and toward workers and users.

Source: Ars Technica News