The two words the AI industry hates more than anything

Blood in the Machine

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The two words the AI industry hates more than anything

I talk with computational linguist Emily M. Bender, co-author of the influential 2021 “stochastic parrots” paper, about why AI industry leaders can’t stop seething over the term.

Brian Merchant

Oct 02, 2026

“Stochastic parrots,” a term coined by four leading AI researchers in a paper in 2021, essentially holds that large language models are not “intelligent” but are rather systems that output material based on what’s in their training data. Now, while LLMs and technologies described as AI today have become more sophisticated and complex over the last 5 years, the term remains a fundamentally accurate way of describing what LLMs do.

Yet the industry hates it like the plague. AI industry folks absolutely lose their minds over the term, and often bring it up, unprompted, just to try to debunk it again and again.

Why does this particular term have a unique capacity to enrage AI industry folks? I had a theory that, even more so than other critiques about shaky financing or dubious functionality, stochastic parrots undercuts the very foundation that the AI boom is built on: That tech companies are building a machine god of infinite power and potential. These firms have relied on narrative to build up and to sell to the world a very expensive, resource-consumptive technology. If it turns out it’s an unthinking system that’s often fallible in predictable ways, well, that might not be worth quite as many trillions of dollars.

To discuss this theory in greater depth, I thought I’d go right to the source—to one of the paper’s co-authors, professor Emily M. Bender, of the University of Washington.

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