A Counterfactual Model of Causal Judgments in Double Prevention
Kevin O'Neill, Duke University, United States; Tadeg Quillien, University of Edinburgh, United Kingdom; Paul Henne, Lake Forest College, United States
Posters 1 Poster
Pacific Ballroom H-O
Thu, 25 Aug, 19:30 - 21:30 Pacific Time (UTC -8)
In cases of double prevention--when one event prevents another from preventing an outcome initiated by a productive factor--people tend to judge the productive factor as causal but the double preventer as non-causal. Recent work demonstrated that this tendency can be explained by appealing to people's agreement with and tendency to consider counterfactuals: asking people to imagine the absence of the double preventer decreased their tendency to view the productive factor as more causal than the double-preventer. These effects were well-explained by the Necessity-Sufficiency (NS) model, which instantiates a particular counterfactual account. Here we asked whether another model, the Counterfactual Effect Size (CES) model, could predict the same effects. We found that the CES model indeed predicted these effects, suggesting that the ability of counterfactual theories to predict causal judgments in cases of double prevention is not unique to the NS model.