The Reverse Centaur’s Guide to Life After AI by Cory Doctorow review – the real price of artificial intelligence

Cory Doctorow’s new book argues the AI industry’s business model, not the technology itself, is designed to diminish workers and inflate a market bubble, according to a review in The Guardian [1]. The book, "The Reverse Centaur's Guide to Life After AI," uses the metaphor of a reverse centaur—a person whose freedom is constrained by a machine’s demands—to critique how AI is being deployed [1]. Doctorow contrasts this with a true centaur, where a human is assisted by a machine, such as a radiologist working with an AI to improve accuracy. The reverse centaur scenario, he argues, demotes humans to error-prone drones because it is cheaper for the hospital [1]. The core problem, Doctorow writes, is that the AI sector’s valuation is tied to the promise of replacing human labor. Morgan Stanley predicts AI will add almost a trillion dollars annually to the S&P 500, a figure derived largely from the salaries of workers it aims to displace [1]. OpenAI, which Doctorow dismisses as "a grossly overhyped and terrible firm," is currently valued at $852bn [1]. The organization, founded as a nonprofit in 2015, restructured in 2025 into a for-profit public benefit corporation partially controlled by its nonprofit arm, and conducted a $6.6 billion share sale that October [9]. Doctorow’s critique arrives amid broad public skepticism. A study found that 90% of people are less likely to use a product if it is advertised as AI-enabled, and 95% of generative AI pilot schemes are failing [1]. For Gen Z, AI has a favourability rating of minus 44, according to an NBC poll [1]. The industry’s response, Doctorow suggests, is to deliberately fuel outrage over AI-generated art as a form of hype, using public fear to convince investors of the technology’s disruptive power [1]. He targets the doctrine of "inevitabilism," the idea that workers have no choice but to accept the technology, a message former Google CEO Eric Schmidt delivered to booing students at a commencement address [1]. The financial stakes are systemic. Seven big tech companies now account for one-third of the US stock market’s value, meaning a burst bubble could trigger an economic shock comparable to 2008 or 2020 [1]. The research landscape reflects this concentration. A comparative analysis of AI companies found that Google, OpenAI, and Meta have been responsible for some of the largest training runs and a large fraction of algorithmic innovations underpinning large language models [6]. Google’s Gemini chatbot, launched in 2023, faced early criticism for historical inaccuracies in image generation, leading the company to suspend the feature [8]. Meanwhile, a 2025 analysis of major LLM providers’ terms of service identified "regulatory gray areas" that create uncertainty for legitimate research use, highlighting the complex rules governing the tools at the center of this economic transformation [2].