Projects per year
Abstract / Description of output
Everything that happens has a multitude of causes, but people make causal judgments effortlessly. How do people select one particular cause (e.g., the lightning bolt that set the forest ablaze) out of the set of factors that contributed to the event (the oxygen in the air, the dry weather …)? Cognitive scientists have suggested that people make causal judgments about an event by simulating alternative ways things could have happened. We argue that this counterfactual theory explains many features of human causal intuitions, given two simple assumptions. First, people tend to imagine counterfactual possibilities that are both a priori likely and similar to what actually happened. Second, people judge that a factor C caused effect E if C and E are highly correlated across these counterfactual possibilities. In a reanalysis of existing empirical data, and a set of new experiments, we find that this theory uniquely accounts for people’s causal intuitions.
Original language | English |
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Pages (from-to) | 1-27 |
Number of pages | 27 |
Journal | Psychological Review |
DOIs | |
Publication status | Published - 8 Jun 2023 |
Keywords / Materials (for Non-textual outputs)
- causal selection
- causation
- computational modeling
- counterfactuals
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Dive into the research topics of 'Counterfactuals and the Logic of Causal Selection'. Together they form a unique fingerprint.Projects
- 1 Finished
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Computational constructivism: Exploring the algorithmic basis of discovery
1/04/21 → 31/03/24
Project: Research