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Bayesian principles in cognition are compatible with wishful thinking. Opposing goals lead to goal-consistent conclusions from the same evidence via Bayesian calculations, driven by affective prediction errors.

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Area of Science:

  • Cognitive Science
  • Psychology
  • Decision Making

Background:

  • Bayesian principles are widely applied to human cognition.
  • Wishful thinking, where beliefs align with desires, appears to contradict Bayesian universality.
  • This study investigates the compatibility of Bayesian optimality and wishful thinking.

Purpose of the Study:

  • To demonstrate that Bayesian optimality and wishful thinking are compatible.
  • To explain how opposing goals can lead to divergent conclusions from identical evidence using Bayesian reasoning.
  • To introduce a formal Bayesian model of wishful thinking driven by affective prediction errors.

Main Methods:

  • Development of a formal Bayesian model.
  • Empirical testing across five studies.
  • Analysis of how affective experiences inform goal-consistent conclusions.

Main Results:

  • Identical prior beliefs and evidence can yield opposite conclusions under opposing goals through Bayesian calculations.
  • Affective experiences provide privileged, goal-consistent information.
  • Affective prediction errors were shown to drive wishful thinking.

Conclusions:

  • Bayesian principles and wishful thinking are reconcilable within a formal Bayesian framework.
  • Goal-directed cognition, mediated by affect, can explain apparent deviations from Bayesian rationality.
  • The findings support a model where emotions influence belief updating in a goal-congruent manner.