CONCEPT
Pseudo-Expertise
The AI-era counterfeit: confident familiarity with a domain's vocabulary and standard arguments, not grounded in the direct experience of having wrestled with the domain's actual problems.
Pseudo-expertise is the characteristic failure mode of AI-mediated learning: a confident familiarity with a domain's concepts, vocabulary, and standard arguments that has not been earned through the sustained, friction-rich encounter with the domain's actual problems. The pseudo-expert can discuss the field fluently. She can produce competent output at high speed. What she cannot do is recognize when the standard approach fails, when familiar concepts do not apply, when the situation requires the kind of perception developed only through the slow process of genuine attention. Pseudo-expertise is invisible from the outside — its outputs resemble those of genuine expertise — and often invisible to the practitioner herself, because AI's plausible scaffolding feels like understanding even when it is not.
In The You On AI Field Guide
The distinction between expertise and pseudo-expertise tracks Murdoch's broader distinction between attending to the subject and attending to the output. Genuine expertise is built through attending to the subject — through the years of wrestling with problems that resist the practitioner's initial framing