The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want, by Emily M. Bender and Alex Hanna, has a straightforward thesis: the technology that goes by the name “AI”—a “marketing term,” according to the authors—is a con, “a bill of goods you are being sold to line someone’s pockets.” It’s a form of hype that uses tropes from science fiction to make the technology, and its creators, “appear powerful—if not godlike—in their technical creation.” It’s a technology that doesn’t deliver on promises of its wealthy proponents. Instead, those “well-placed players are poised to accumulate significant wealth from other people’s creative work, personal data, or labor, and replacing quality services with artificial facsimiles.” The infrastructure on which it operates is made from rare-earth minerals and is manufactured with toxic chemicals, used outrageous amounts of water for cooling, and is likely to make decarbonizing our economy impossible. It’s a massive surveillance machine. It encourages managers to fire actual human employees because they figure that AI slop can do the same work more cheaply. (The fact that it can’t doesn’t matter, apparently.) It perpetuates the racism and sexism that’s in its training data. It’s inherently unreliable, generating wrong answers to questions and making the work of research—figuring out which sources are credible and which aren’t—impossible. The investment bubble it’s creating (bigger now than when the book was written) could cause an economic collapse when it pops. And, they argue, it needs to be resisted.

Bender, a computational linguist, and Hanna, the director of research at the Distributed AI Research Institute, describe generative AI—platforms like ChatGPT and Claude, which run on large language models—“synthetic text extruding machines” which mimic speech but have no intelligence and are incapable of forming a communicative intention. Like ELIZA, the chatbot developed by Joseph Weizenbaum in the late 1960s, these platforms fool us into thinking that they’re intelligent, mostly because we’re prone to attributing intelligence to things that seem to have language, the way we see faces in clouds (a phenomenon called pareidolia). Predicting which word follows in a series without knowing what any of the words actually mean isn’t a sign that the machines are thinking or conscious. Besides, we don’t really know what consciousness or intelligence actually are. We don’t have clear definitions of either term that would help us measure the claims of many AI proponents. We’re falling for an illusion, Bender and Hanna argue, and the hype surrounding AI is driven more by FOMO than anything rational.

The AI Con covers a lot of ground. It’s well-researched but approachable, its prose almost breezy. I’m not a fan of generative AI, so I’m prone to agree with its arguments, so in my case, Bender and Hanna are preaching to the choir. Still, they unpack the actual harms this technology is causing while seeing through the hype about its potential risks and putative benefits. Because the technology is developing so rapidly, it’s already a little out of date, even though it was just published last year; the economic and ecological damage AI is causing seems to be worse than the book suggests, and the resistance to generative AI and the data centres on which it runs has exploded in the past six months. Still, Bender and Hanna seem to know what they’re talking about, and The AI Con is a useful corrective against the technological triumphalism and the rhetoric of inevitability that surrounds AI. We see both in our federal government’s AI strategy—and just about everywhere else. I’m glad I read it. The next AI book I’ll tackle will be Karen Hao’s Empire of AI: Dreams and Nightmares in Sam Altman’s OpenAI. But that won’t happen right away, mostly because I didn’t bring it with me on this trip. Oh, and also because life’s too short to spend all my energy thinking about AI.