Failures of explaining away and screening off in described versus experienced causal learning scenarios

Bob Rehder, Michael R. Waldmann

Research output: Contribution to journalArticle

Abstract

Causal Bayes nets capture many aspects of causal thinking that set them apart from purely associative reasoning. However, some central properties of this normative theory routinely violated. In tasks requiring an understanding of explaining away and screening off, subjects often deviate from these principles and manifest the operation of an associative bias that we refer to as the rich-get-richer principle. This research focuses on these two failures comparing tasks in which causal scenarios are merely described (via verbal statements of the causal relations) versus experienced (via samples of data that manifest the intervariable correlations implied by the causal relations). Our key finding is that we obtained stronger deviations from normative predictions in the described conditions that highlight the instructed causal model compared to those that presented data. This counterintuitive finding indicate that a theory of causal reasoning and learning needs to integrate normative principles with biases people hold about causal relations.

Original languageEnglish (US)
Pages (from-to)245-260
Number of pages16
JournalMemory and Cognition
Volume45
Issue number2
DOIs
StatePublished - Feb 1 2017

Keywords

  • Causal learning
  • Causal reasoning
  • Explaining away
  • Markov violations
  • Reasoning errors

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)

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