Human and LLM everyday reasoning are both pattern matching, not world models.

Studdiford and Lupyan tested human participants and 25 LLMs on common-sense causal reasoning and found shared, predictable error patterns triggered by irrelevant prompt details (arXiv). They localized the attention heads driving it. The uncomfortable implication: the gap between human and machine everyday reasoning may be narrower than we assume, because both inherit the same brittleness. If you've watched an agent get derailed by an irrelevant detail in a ticket, this is the mechanism. We do it too.