Beyond Markov: Accounting for Independence Violations in Causal Reasoning

Although many theories of causal cognition are based on causal graphical models, a key property of such models-the independence relations stipulated by the Markov condition-is routinely violated by human reasoners. Two accounts of why people violate independence are formalized and subjected to experimental test. Subjects' inferences were more consistent with a dual prototype model in which people favor network states in which variables are all present or all absent than a leaky gate model in which information is transmitted through network nodes when it should normatively be blocked. The article concludes with a call for theories of causal cognition that rest on foundations that are faithful to the kinds of causal inferences people actually draw.