Functional Rule Inference from Causal Selection Explanations

Nicolas Navarre (1) , Can Konuk (2) , Neil R. Bramley (1) , Salvador Mascarenhas (2)

1 School of Informatics [Edimbourg]
2 IJN - Institut Jean-Nicod

Building on counterfactual theories of causal-selection, according to which humans intuitively evaluate the causal responsibility of events, we developed an experimental paradigm to examine the effect of causal-selection explanations on abductive causal inference. In our experiment, participants attempted to infer the rule responsible for winning outcomes of random draws from urns with varying sampling probabilities. Participants who were provided with causal-selection judgments as explanations for the outcomes made significantly closer inferences to the rule than those relying on observations alone, or on other explanations of causal relevance. We mirror these empirical results with a computational model of inference from explanation leveraging the theories of causal selection.

Mots clés: causal inference; causal selection; counterfactual theories of causation

Domaines: Sciences cognitives

Nicolas Navarre, Can Konuk, Neil R. Bramley, Salvador Mascarenhas. Functional Rule Inference from Causal Selection Explanations. 46th Annual Cognitive Science Society Meeting, Jul 2024, Rotterdam (NL), Netherlands. ⟨hal-04572408⟩