Cory Doctorow delivers a jarring corrective to the current AI panic: the technology isn't a world-ending horror, but a boring, expensive toy that we are collectively pretending is magic to justify a trillion-dollar bubble. By reframing the narrative from "existential risk" to "economic fraud," Doctorow exposes how the fear-mongering of tech executives is actually a sales tactic designed to secure funding for a product that is currently useless at scale.
The Sales Pitch of Doom
The core of Doctorow's argument is that the apocalyptic rhetoric surrounding artificial intelligence is not a warning, but a boast. He writes, "every public pronouncement about this terrible potential is also a public boast about its potential, period." This observation cuts through the noise of safety debates to reveal the underlying economic incentive: if the technology isn't potentially world-ending, it isn't worth the massive capital injection it is currently receiving. Doctorow argues that we are witnessing a "civilizational act of Magic Underpants Gnomery," where leaders bet the future on a tool that cannot yet do the open-ended research required to prove its own worth.
The author suggests that actual, existing AI is merely a "normal technology," comparable to a plug-in for a word processor that might help a skilled practitioner or might just waste time. Yet, the political and economic response is anything but normal. Doctorow points out that "normal technologies do not warrant the massive economic and political commitments that have been bestowed upon AI," citing the firing of civil servants and the construction of massive data centers that consume scarce water and energy. This framing is effective because it shifts the blame from the algorithm to the governance that allows such wasteful speculation to continue unchecked.
Critics might argue that dismissing AI as "normal" ignores the genuine, rapid acceleration of capabilities that could outpace human oversight. However, Doctorow anticipates this by noting that the current "destructive potential" is already being realized through the destruction of the productive economy and the environment, long before any hypothetical future singularity.
"The moment we stop believing in that potential is the moment that we stop supplying AI companies with bales of cash to shovel into their money-furnaces."
Criti-Hype and the Lich-King Narrative
Doctorow introduces a sharp critique of how the media and policymakers discuss AI safety, coining the term "criti-hype." He explains that this occurs when critics "tak[e] the sensational claims of boosters and entrepreneurs, flip[ping] them, and start talking about 'risks'." By repeating the lie that AI is a "rogue" force, the critics inadvertently validate the marketing of the very companies they seek to regulate. Doctorow insists, "The right way to criticize them is to point out that they're lying — not to repeat their lies as warnings."
This approach demands we stop treating tech CEOs as super-villains or "lich-kings." Doctorow describes Sam Altman not as a genius, but as a "con-man and a stock swindler" who benefits from being elevated to a status where he is "too big to jail." The argument here is that by mythologizing the evil of these figures, we grant them a durability they do not deserve. Instead, we should view AI as a "carny ride that triggers cardiac events in riders who never knew they had a problem," rather than a force that creates vulnerability out of thin air.
The author connects this to the broader concept of "enshittification," where platforms degrade to extract value, noting that the current AI boom is a "money-losingest" investment bubble that will eventually burst. He urges a shift from "AI safety" to accountability, asking why companies "suck so bad at building secure sandboxes" rather than marveling at the power of their hacking tools. This reframing strips the glamour from the industry, reducing it to a series of bad business decisions and regulatory failures.
"Treating AI as unexceptional is the best way to halt the destructive march of AI companies and their impact on jobs, the climate and the economy."
From Inevitability to Agency
The piece concludes by rejecting the fatalism of "vulgar Thatcherism," which claims there is no alternative to the current trajectory of technology. Doctorow champions a "heroic Gibsonism," invoking William Gibson's idea that "the street finds its own use for things." This perspective empowers users and regulators to seize control of the technology, using it for good while banning or blocking the harmful applications. He asserts that AI is not a "cursed artifact" stained with "communicable sin," but simply "computers" that can be repurposed once the bubble bursts.
This is a crucial pivot for busy readers who feel paralyzed by the scale of the problem. Doctorow argues that the world will be better off when these companies go bankrupt and their servers are sold off, provided we stop treating the technology as magical. By normalizing AI, we remove the shield of inevitability that protects the industry from scrutiny. The argument holds that we must stop asking if AI will destroy the world and start asking why we are allowing a "slop-filled" economy to consume our resources.
"The world will be better off when the AI companies are bankrupt and their servers are sold off at ten cents on the dollar — but using those servers to run open models in modest, careful ways won't infect you with their wickedness."
Bottom Line
Doctorow's most compelling contribution is the exposure of "criti-hype" as a mechanism that fuels the very bubble critics claim to fear; by treating AI as a normal, flawed tool rather than a magical entity, we strip the industry of its ability to demand unlimited capital. The argument's greatest vulnerability lies in its optimism about the "street" seizing control, potentially underestimating the entrenched power of the data centers and the legal frameworks already being built to protect them. Readers should watch for whether policymakers can shift from debating "safety" to enforcing the hard economic realities of a failing investment model.