Simplicity is Used to Promote Accuracy (vs. Efficiency) in Explanation Evaluations

People often prefer simpler explanations over more complex ones, but the function of this preference remains unclear. Does simplicity serve to increase the accuracy of explanation evaluations, improve efficiency, or both? The current research investigates this question in the context of evaluating which of two competing explanations is more likely—one simple (involving a single cause) and one complex (involving two causes)—when base rate probabilities are either provided or inferred from background knowledge. Across two studies (N = 766), participants were asked to evaluate explanations under different goal conditions (accuracy vs. efficiency) and report the information they relied on. Results showed that simplicity was used more under accuracy goals than efficiency goals, was generally combined with probability information rather than used as an alternative to it, and was associated with more accurate—but slower—judgments. These findings suggest that simplicity is primarily used to promote accuracy, not efficiency, in explanation evaluation. This work provides one of the first direct empirical tests of the goals underlying simplicity preferences. It challenges the idea that simplicity primarily functions as a cognitive shortcut to increase efficiency, and instead supports the view that simplicity helps people better approximate probabilistic reasoning. These findings offer new insights into the cognitive role of simplicity and the strategies people use to evaluate competing explanations.