Scientific and religious explanations often coexist in the sense that they are both endorsed by the same individuals, and they are sometimes conjoined such that a single explanation draws upon both scientific and religious components. In this chapter we consider the psychology of such explanations, drawing upon recent research in cognitive and social psychology. We argue that scientific and religious explanations often serve different psychological functions, with scientific explanations seen as better serving epistemic functions (such as supporting accurate models of the world), and religious explanations seen as better serving non-epistemic functions (such as offering emotional comfort or supporting moral behavior). This functional differentiation points to a potential benefit of conjunctive explanations: by fulfilling multiple psychological functions, they will sometimes satisfy a broader range of explanatory goals. Generalizing from the case of science and religion, we suggest that conjunctive explanations may be especially appealing when a given explanatory framework faces tradeoffs between different explanatory goals (such as generality versus precision), resulting in an advantage to explanations that draw upon multiple explanatory frameworks instantiating different tradeoffs.
People often face the challenge of evaluating competing explanations. One approach is to assess the explanations’ relative probabilities – e.g., applying Bayesian inference to compute their posterior probabilities. Another approach is to consider an explanation’s qualities or ‘virtues’, such as its relative simplicity (i.e., the number of unexplained causes it invokes). The current work investigates how these two approaches are related. Study 1 found that simplicity is used to infer the inputs to Bayesian inference (explanations’ priors and likelihoods). Studies 1 and 2 found that simplicity is also used as a direct cue to the outputs of Bayesian inference (the posterior probability of an explanation), such that simplicity affects estimates of posterior probability even after controlling for elicited (Study 1) or provided (Study 2) priors and likelihoods, with simplicity having a larger effect in Study 1, where posteriors are more uncertain and difficult to compute. Comparing Studies 1 and 2 also suggested that simplicity plays additional roles unrelated to approximating probabilities, as reflected in simplicity’s effect on how ‘satisfying’ (vs. probable) an explanation is, which remained largely unaffected by the difficulty of computing posteriors. Together, these results suggest that the virtue of simplicity is used in multiple ways to approximate probabilities (i.e., serving as a cue to priors, likelihoods, and posteriors) when these probabilities are otherwise uncertain or difficult to compute, but that the influence of simplicity also goes beyond these roles.
Identifying abstract relations is essential for commonsense reasoning. Research suggests that even young children can infer relations such as “same” and “different,” but often fail to apply these concepts. Might the process of explaining facilitate the recognition and application of relational concepts? Based on prior work suggesting that explanation can be a powerful tool to promote abstract reasoning, we predicted that children would be more likely to discover and use an abstract relational rule when they were prompted to explain observations instantiating that rule, compared to when they received demonstration alone. Five- and 6-year-olds were given a modified Relational Match to Sample (RMTS) task, with repeated demonstrations of relational (same) matches by an adult. Half of the children were prompted to explain these matches; the other half reported the match they observed. Children who were prompted to explain showed immediate, stable success, while those only asked to report the outcome of the pedagogical demonstration did not. Findings provide evidence that explanation facilitates early abstraction over and above demonstration alone.