Large language models can aggregate and reproduce vast objective knowledge reliably, yet they systematically lack the subjective intelligence that underwrites judgement, moral reasoning, and life‑shaping decisions. As a result, their fluency can mislead users into overestimating their ability to make normative or context‑sensitive calls.
— If accepted, this framing warns policymakers, educators, and platform designers to distinguish performance metrics from real‑world judgment and to avoid treating LLM outputs as substitutes for human discretion.
Adam Mastroianni
2026.03.31
100% relevant
The author’s coinage 'infinite midwit' and the Settlers of Catan trade analogy (infinite objective intelligence ≠ infinite subjective outcomes) in the article illustrate the gap between model competence and human judgment.
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