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Modeling information demand in the framework of probabilistic reasoning
Matthew W Jiwa1,2, Jacqueline Gottlieb3,4,5
1Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA. matt.jiwa@unimelb.edu.au.
Communications Psychology
|January 17, 2026
Summary
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.
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.
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