Testing a Process Model of Causal Reasoning With Inhibitory Causal Links

In this paper, we test people’s causal judgments when the graphs have inhibitory causal relations. We find evidence that a particularly important class of errors known as Markov violations extend to these settings. These Markov violations are important because they are incompatible with causal graphical models, a theoretical framework that is often used as a computational level account of causal cognition. In contrast, the systematic pattern of errors are in line with the predictions of a recently proposed rational process model that models people as reasoning about concrete cases (Davis & Rehder, 2020). These findings demonstrate that errors in causal reasoning extend across a range of settings, and do so in line with the predictions of a model that describes the process by which causal judgments are drawn.