Explanatory preferences for complexity matching.

Abstract

People are adept at generating and evaluating explanations for events around them. But what makes for a satisfying explanation? While some scholars argue that individuals find simple explanations to be more satisfying (Lombrozo, 2007), others argue that complex explanations are preferred (Zemla, et al. 2017). Uniting these perspectives, we posit that people believe a satisfying explanation should be as complex as the event being explained–what we term the complexity matching hypothesis. Thus, individuals will prefer simple explanations for simple events, and complex explanations for complex events. Four studies provide robust evidence for the complexity-matching hypothesis. In studies 1–3, participants read scenarios and then predicted the complexity of a satisfying explanation (Study 1), generated an explanation themselves (Study 2), and evaluated explanations (Study 3). Lastly, in Study 4, we explored a different manipulation of complexity to demonstrate robustness across paradigms. We end with a discussion of mechanisms that might underlie this preference-matching phenomenon.