What Happens When People Don't Understand How AI Works [View all]

Despite what tech CEOs might say, large language models are not smart in any recognizably human sense of the word.

https://www.theatlantic.com/culture/archive/2025/06/artificial-intelligence-illiteracy/683021/

https://archive.ph/401p7



On June 13, 1863, a curious letter to the editor appeared in The Press, a then-fledgling New Zealand newspaper. Signed “Cellarius,” it warned of an encroaching “mechanical kingdom” that would soon bring humanity to its yoke. “The machines are gaining ground upon us,” the author ranted, distressed by the breakneck pace of industrialization and technological development. “Day by day we are becoming more subservient to them; more men are daily bound down as slaves to tend them, more men are daily devoting the energies of their whole lives to the development of mechanical life.” We now know that this jeremiad was the work of a young Samuel Butler, the British writer who would go on to publish Erewhon, a novel that features one of the first known discussions of artificial intelligence in the English language.

Today, Butler’s “mechanical kingdom” is no longer hypothetical, at least according to the tech journalist Karen Hao, who prefers the word empire. Her new book, Empire of AI: Dreams and Nightmares in Sam Altman’s OpenAI, is part Silicon Valley exposé, part globe-trotting investigative journalism about the labor that goes into building and training large language models such as ChatGPT. It joins another recently released book—The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want, by the linguist Emily M. Bender and the sociologist Alex Hanna—in revealing the puffery that fuels much of the artificial-intelligence business. Both works, the former implicitly and the latter explicitly, suggest that the foundation of the AI industry is a scam.

To call AI a con isn’t to say that the technology is not remarkable, that it has no use, or that it will not transform the world (perhaps for the better) in the right hands. It is to say that AI is not what its developers are selling it as: a new class of thinking—and, soon, feeling—machines. Altman brags about ChatGPT-4.5’s improved “emotional intelligence,” which he says makes users feel like they’re “talking to a thoughtful person.” Dario Amodei, the CEO of the AI company Anthropic, argued last year that the next generation of artificial intelligence will be “smarter than a Nobel Prize winner.” Demis Hassabis, the CEO of Google’s DeepMind, said the goal is to create “models that are able to understand the world around us.”

Read: What ‘Silicon Valley’ knew about tech-bro paternalism

These statements betray a conceptual error: Large language models do not, cannot, and will not “understand” anything at all. They are not emotionally intelligent or smart in any meaningful or recognizably human sense of the word. LLMs are impressive probability gadgets that have been fed nearly the entire internet, and produce writing not by thinking but by making statistically informed guesses about which lexical item is likely to follow another. Many people, however, fail to grasp how large language models work, what their limits are, and, crucially, that LLMs do not think and feel but instead mimic and mirror. They are AI illiterate—understandably, because of the misleading ways its loudest champions describe the technology, and troublingly, because that illiteracy makes them vulnerable to one of the most concerning near-term AI threats: the possibility that they will enter into corrosive relationships (intellectual, spiritual, romantic) with machines that only seem like they have ideas or emotions.

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