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Confirmation bias emerges from an approximation to Bayesian reasoning.

Charlie Pilgrim1, Adam Sanborn2, Eugene Malthouse2

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Summary
This summary is machine-generated.

Confirmation bias, the tendency to favor existing beliefs, arises naturally from boundedly rational belief updating. Our BIASR model explains how cognitive shortcuts lead to various confirmation biases.

Keywords:
BayesianBounded rationalityCognitive modelConfirmation biasInformation processingSource reliability

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Area of Science:

  • Cognitive Science
  • Psychology
  • Decision Making

Background:

  • Confirmation bias is the tendency to search for and interpret information in a way that confirms pre-existing beliefs.
  • Understanding the cognitive mechanisms behind confirmation bias is crucial for explaining human judgment and decision-making.

Purpose of the Study:

  • To present a computational model, BIASR (Bayesian updating with an Independence Approximation and Source Reliability), that explains the emergence of confirmation bias.
  • To demonstrate how boundedly rational belief updating can naturally lead to various forms of confirmation bias.

Main Methods:

  • Developed the BIASR model, a Bayesian network where an individual's beliefs about a hypothesis and source reliability are updated simultaneously.
  • Incorporated an independence approximation to overcome memory limitations associated with fully rational Bayesian updating.

Main Results:

  • The BIASR model successfully generates multiple forms of confirmation bias, including biased evaluation, assimilation, attitude polarization, belief perseverance, and source selection bias.
  • The model illustrates that assuming independence between beliefs is a cognitive strategy that leads to these biases.

Conclusions:

  • Confirmation bias is a natural outcome of cognitive processes that simplify complex belief updating under memory constraints.
  • The BIASR model provides a parsimonious explanation for a wide range of observed confirmation biases in human cognition.