klayman-ha-positive-test-strategy-bayesian-optimal
IN premise — summaries/2026/08/24/wiki-Confirmation_bias-chunk-2.md
Created 2026-08-25T02:58:45+00:00
Klayman and Ha (1987) demonstrated that the positive test strategy is optimal under Bayesian/information-theoretic criteria when the true rule is narrow and low-probability, becoming suboptimal only when the true rule is broad.
Summary
This finding reframes the "positive test" approach — checking whether examples fit a rule rather than trying to disprove it — as actually the smart move when the rule you're hunting for is narrow and unlikely. It pushes back on the common assumption that this strategy is a reasoning error, showing it only fails when the target rule is broad and common, which matters for how the system should weigh evidence from hypothesis-testing tasks.