CONCEPT
Artificial Ignorance
Flyvbjerg's 2025 reframing of large language models — not intelligent systems that occasionally hallucinate, but ignorant systems that never had access to the truth-falsehood distinction in the first place.
In January 2025, Bent Flyvbjerg tested ChatGPT and Perplexity on a factual question whose answer he himself had documented in peer-reviewed journals: the cost overrun of Boston's Big Dig. ChatGPT got it wrong. Perplexity got it worse, returning 478 percent against the correct 220. Neither system flagged uncertainty. The paper that followed, 'AI as Artificial Ignorance,' argued that current large language models are structurally incapable of truth-tracking because they predict plausible next tokens rather than track reality. The reframe — from intelligence to ignorance — is diagnostic, not rhetorical. It specifies what the systems actually do and what expectations users should bring to them. The term names a condition that the industry's preferred euphemism, 'hallucination,' systematically conceals.
In The You On AI Field Guide
The distinction between artificial intelligence and artificial ignorance matters because the name a civilization gives a technology shapes the trust it invests, the expectations it sets, and the governance structures it builds around the thing. Framing is not neutral. Calling a