Abstract

Much of cognition allows us to make sense of things by explaining observable evidence in terms of unobservable explanations, such as category memberships and hidden causes. Yet we must often make such explanatory inferences with incomplete evidence, where we are ignorant about some relevant facts or diagnostic features. In seven experiments, we studied how people make explanatory inferences under these uncertain conditions, testing the possibility that people attempt to infer the presence or absence of diagnostic evidence on the basis of other cues such as evidence base rates (even when these cues are normatively irrelevant) and then proceed to make explanatory inferences on the basis of the inferred evidence. Participants followed this strategy in both diagnostic causal reasoning (Experiments 1–4, 7) and in categorization (Experiments 5–6), leading to illusory inferences. Two processing predictions of this account were also confirmed, concerning participants’ evidence-seeking behavior (Experiment 4) and their beliefs about the likely presence or absence of the evidence (Experiment 5). These findings reveal deep commonalities between superficially distinct forms of diagnostic reasoning—causal reasoning and classification—and point toward common inferential machinery across explanatory tasks.

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