Study: The Human Brain Is Biased Toward Inventing Structure When Learning Distributions
bravo_abad · x · 2026-08-10
Researcher Tianyuan Teng and coauthors demonstrate across eight behavioral experiments that when humans learn a probability distribution from limited data, they impose a preferred level of structural complexity on it.
Participants consistently invented multiple clusters when the true distribution was a single Gaussian, yet under-represented structure when it contained many clusters. The authors model this human learning bias as approximate Bayesian inference with a Distorted Economical Expansion (DEE) process, offering a computational perspective on cognitive biases.
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