It’s Complicated: Improving Decisions on Causally Complex Topics

Samantha Kleinberg, Jessecae K. Marsh

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

We make frequent decisions about how to manage our health, yet do so with information that is highly complex or received piecemeal. Causal models can provide guidance about how components of a complex system interact, yet models that provide a complete causal story may be more complex than people can reason about. Prior work has provided mixed insights into our ability to make decisions with causal models, showing that people can use them in novel domains but that they may impede decisions in familiar ones. We examine how tailoring causal information to the question at hand may aid decision making, using simple diagrams with only the relevant causal paths (Experiment 1) or those paths highlighted within a complex causal model (Experiment 2). We find that diagrams tailored to a choice improve decision accuracy over complex diagrams or prior knowledge, providing new evidence for how causal models can aid decisions.

Original languageEnglish
Pages2437-2443
Number of pages7
StatePublished - 2021
Event43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021 - Virtual, Online, Austria
Duration: 26 Jul 202129 Jul 2021

Conference

Conference43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021
Country/TerritoryAustria
CityVirtual, Online
Period26/07/2129/07/21

Keywords

  • causal reasoning
  • complexity
  • decision making

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