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Human information demand is driven by how we perceive probabilities of gains and losses, not just linear motives. This finding impacts understanding decision-making under risk and uncertainty.

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Area of Science:

  • Cognitive science
  • Decision science
  • Neuroeconomics

Background:

  • Effective decision-making relies on strategic information sampling.
  • Cognitive mechanisms underlying information demand remain incompletely understood.

Purpose of the Study:

  • To investigate the role of subjective probability perception in information demand.
  • To compare non-linear and linear models of information seeking behavior.

Main Methods:

  • Behavioral testing across three independent participant samples (N=50, 50, 150).
  • Quantitative model comparisons to evaluate predictive accuracy.
  • Correlational analyses with personality traits and risk preferences.

Main Results:

  • A model incorporating non-linear probability and value perception significantly outperformed a linear model.
  • Individual non-linearities in information demand correlated with personality and risk-seeking/aversion.
  • Subjective perception of probabilistic outcomes is key to information demand.

Conclusions:

  • A computational framework based on subjective probability perception enhances understanding of information demand.
  • This framework links information seeking to decision-making under risk and uncertainty.
  • Non-linear perception of probability is a crucial factor in information-seeking behavior.