Seeking confirmation is rational for deterministic hypotheses

Joseph L. Austerweil, Thomas L. Griffiths

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


The tendency to test outcomes that are predicted by our current theory (the confirmation bias) is one of the best-known biases of human decision making. We prove that the confirmation bias is an optimal strategy for testing hypotheses when those hypotheses are deterministic, each making a single prediction about the next event in a sequence. Our proof applies for two normative standards commonly used for evaluating hypothesis testing: maximizing expected information gain and maximizing the probability of falsifying the current hypothesis. This analysis rests on two assumptions: (a) that people predict the next event in a sequence in a way that is consistent with Bayesian inference; and (b) when testing hypotheses, people test the hypothesis to which they assign highest posterior probability. We present four behavioral experiments that support these assumptions, showing that a simple Bayesian model can capture people's predictions about numerical sequences (Experiments 1 and 2), and that we can alter the hypotheses that people choose to test by manipulating the prior probability of those hypotheses (Experiments 3 and 4).

Original languageEnglish (US)
Pages (from-to)499-526
Number of pages28
JournalCognitive science
Issue number3
StatePublished - Apr 2011
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence


  • Bayesian inference
  • Confirmation bias
  • Decision making
  • Determinism
  • Hypothesis testing
  • Rational analysis


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