Department of Psychology, Syracuse University, 430 Huntington Hall, Syracuse, NY 13244, United States of America.
Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, 190 Thayer St., Providence, RI 02912, United States of America.
Cognition. 2023 Oct;239:105551. doi: 10.1016/j.cognition.2023.105551. Epub 2023 Jul 19.
Mechanisms play a central role in how we think about causality, yet not all causal explanations describe mechanisms. Across five experiments, we find that people evaluate explanations differently depending on whether or not they include mechanisms. Despite common wisdom suggesting that explanations ought to be simple in the sense of appealing to as few causes as necessary to explain an effect, the literature is divided over whether people adhere to this principle. Our findings suggest that the presence of causal mechanisms in an explanation is one factor that reduces adherence. While competing explanations are often judged based on their probability of being correct, mechanisms afford a different way of evaluating explanations: They describe the underlying nature of causal relations. Complex explanations (appealing to multiple causes) contain more causal relations and thus allow for more mechanistic information, providing a fuller account of the causal network and promoting a greater sense of understanding.
机制在我们思考因果关系时起着核心作用，但并非所有因果解释都描述了机制。在五项实验中，我们发现人们根据解释是否包含机制来对其进行不同的评估。尽管常识表明，解释应该尽可能简单，即只需要用到能够解释效应的最少原因，但文献对于人们是否遵守这一原则存在分歧。我们的研究结果表明，解释中存在因果机制是降低遵守程度的一个因素。虽然竞争解释通常基于其正确的可能性进行判断，但机制提供了一种不同的解释评估方式：它们描述了因果关系的本质。复杂的解释（涉及多个原因）包含更多的因果关系，因此可以提供更多的机制信息，更全面地描述因果网络，并增强理解感。
