Abstract

Singular causation queries (e.g., “Did Mary's taking contraceptives cause her thrombosis?”) are ubiquitous in everyday life and crucial in many professional disciplines, such as medicine or law. Knowledge about general causal regularities is necessary but not sufficient for establishing a singular causation relation because it is possible that co-occurrences consistent with known regularities are in an individual case still just coincidental. Thus, further cues are helpful to establish a singular causation relation. In the present research we focus on information about mechanisms as a potent cue. While previous studies have shown that reasoners consider mechanism information as important when it comes to answering singular causation queries, no formal model has been proposed that explains why this is case. We here present a computational model that explains how causal mechanism information affects singular causation judgments. We also use the model to identify conditions that restrict the utility of mechanism information. We report three experiments testing the implications of our formal analysis. In Experiment 1 we found that reasoners systematically use mechanism information, largely in accordance with our formal model, although we also discovered that some people seem to rely on simpler, computationally less demanding reasoning strategies. The results of Experiments 2 and 3 demonstrate that reasoners have a tentative understanding of the conditions that restrict the utility of causal mechanism information.

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