Subjective Causality

• URL: http://arxiv.org/abs/2401.10937v1
• Date: Wed, 17 Jan 2024 11:36:38 GMT
• Title: Subjective Causality
• Authors: Joseph Y. Halpern, Evan Piermont
• Abstract summary: We represent causality using causal models (also called structural equations models) We show that it is possible to understand and identify a decision maker's subjective causal judgements by observing her preferences over interventions.
• Score: 14.440599230549443
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: We show that it is possible to understand and identify a decision maker's subjective causal judgements by observing her preferences over interventions. Following Pearl [2000], we represent causality using causal models (also called structural equations models), where the world is described by a collection of variables, related by equations. We show that if a preference relation over interventions satisfies certain axioms (related to standard axioms regarding counterfactuals), then we can define (i) a causal model, (ii) a probability capturing the decision-maker's uncertainty regarding the external factors in the world and (iii) a utility on outcomes such that each intervention is associated with an expected utility and such that intervention $A$ is preferred to $B$ iff the expected utility of $A$ is greater than that of $B$. In addition, we characterize when the causal model is unique. Thus, our results allow a modeler to test the hypothesis that a decision maker's preferences are consistent with some causal model and to identify causal judgements from observed behavior.

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