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Why We Need a Bullshit Detector for AI

Generative artificial intelligence can produce linguistically clear, structured, and persuasive answers whose claims are nevertheless false, incomplete, unsupported, or unsuitable for the relevant context. The central problem is not merely the well-known possibility of so-called hallucinations. It lies in the growing gap between linguistic plausibility and epistemic reliability. The article uses the pointed term bullshit detector neither as a psychological diagnosis of the machine nor as a supposedly reliable human alarm mechanism. What is meant is a personal, embodied, risk-based review process that examines statements, presentation, use, and institutional responsibility separately. The aim is neither blanket distrust nor blind acceptance but calibrated trust. One could also say: use common sense. At the same time, the article shows why individual critical faculties are not enough. The less users are able to conduct expert scrutiny and the greater the potential harm, the less the safety of an AI system may depend on their personal judgment. Providers, organizations, and public institutions bear an upstream responsibility. The bullshit detector is therefore not merely an individual skill. It is a social and institutional infrastructure for dealing with artificial intelligence. But of course, it is also no excuse not to continue developing one’s own sixth sense.