Tell me something I don't know: How perceived knowledge influences the use of information during decision making

Samantha Kleinberg, Jessecae K. Marsh

Research output: Contribution to conferencePaperpeer-review

5 Scopus citations

Abstract

We are often confronted with new causal information about the world, such as what causes a disease. What we think we know may influence if and how we choose to use this new information. Yet as prior work has shown, we are not always successful at evaluating our own knowledge. We explored how helping people better understand what they know about a domain can influence their ability to use new causal information in a decision-making context. Participants self-assessed their knowledge (Experiment 1) or completed an objective assessment of their knowledge (Experiment 2) of diabetes, before making diabetes-related decisions, either with or without new causal information. Without a knowledge assessment, participants were less accurate with new causal information compared to without such information, replicating previous work. However, reassessing their knowledge increased participants' decision-making accuracy with causal information. We discuss why helping people realize the limits of their causal understanding may make them better supplement it with new information.

Original languageEnglish
Pages1849-1855
Number of pages7
StatePublished - 2020
Event42nd Annual Meeting of the Cognitive Science Society: Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020 - Virtual, Online
Duration: 29 Jul 20201 Aug 2020

Conference

Conference42nd Annual Meeting of the Cognitive Science Society: Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020
CityVirtual, Online
Period29/07/201/08/20

Keywords

  • causality
  • decision making
  • diabetes
  • illusion of explanatory depth

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