Department of Psychology, University of Göttingen.
Top Cogn Sci. 2018 Jan;10(1):242-257. doi: 10.1111/tops.12309. Epub 2017 Nov 19.
Causal queries about singular cases are ubiquitous, yet the question of how we assess whether a particular outcome was actually caused by a specific potential cause turns out to be difficult to answer. Relying on the causal power framework (Cheng, ), Cheng and Novick () proposed a model of causal attribution intended to help answer this question. We challenge this model, both conceptually and empirically. We argue that the central problem of this model is that it treats causal powers that are probabilistically sufficient to generate the effect on a particular occasion as actual causes of the effect, and thus neglects that sufficient causal powers can be preempted in their efficacy. Also, the model does not take into account that reasoners incorporate uncertainty about the underlying general causal structure and strength of causes when making causal inferences. We propose a new measure of causal attribution and embed it into the structure induction model of singular causation (SISC; Stephan & Waldmann, ). Two experiments support the model.
关于单一案例的因果查询无处不在，但实际上，我们如何评估一个特定结果是否确实是由特定潜在原因引起的，这个问题很难回答。程和平和诺维克（）基于因果力框架（Cheng, ），提出了一种因果归因模型，旨在帮助回答这个问题。我们从概念和实证两个方面对该模型提出了挑战。我们认为，该模型的核心问题在于，它将在特定情况下足以产生效应的因果力视为效应的实际原因，从而忽略了充分的因果力可能会被预先阻止其效力。此外，该模型没有考虑到推理者在进行因果推理时会结合对潜在一般因果结构和原因强度的不确定性。我们提出了一种新的因果归因度量，并将其嵌入到单一因果结构推断模型（SISC；Stephan & Waldmann, ）中。两个实验支持了该模型。
