Normality and actual causal strength.
Existing research suggests that people's judgments of actual causation can be influenced by the degree to which they regard certain events as normal. We develop an explanation for this phenomenon that draws on standard tools from the literature on graphical causal models and, in particular, on the idea of probabilistic sampling. Using these tools, we propose a new measure of actual causal strength. This measure accurately captures three effects of normality on causal judgment that have been observed in existing studies. More importantly, the measure predicts a new effect ("abnormal deflation"). Two studies show that people's judgments do, in fact, show this new effect. Taken together, the patterns of people's causal judgments thereby provide support for the proposed explanation.
Department of Philosophy and Symbolic Systems Program, Stanford University, United States. Electronic address: icard@stanford.edu.
Thomas F
TF
Icard
Department of Psychology, Harvard University, United States.
Jonathan F
JF
Kominsky
Program in Cognitive Science and Department of Philosophy, Yale University, United States.
Joshua
J
Knobe
D001499:Bayes Theorem; D006801:Humans; D007092:Imagination; D007600:Judgment; D008960:Models, Psychological
Actual causation; Bayes nets; Causal reasoning; Counterfactuals; Normality; Sampling