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In a novel ‘identify the Expert’ task, participants receive suggested
answers by two advisors. They know one is high-accuracy and
recommends answers reflecting the academic consensus (‘Expert’).
The other is low-accuracy and recommends the modal answer from
a sample of laypeople (‘Populist’). Participants are incentivized
to identify the Expert. Yet, they overwhelmingly choose the Populist,
even when they could always identify the Expert without using
Bayesian reasoning. Overconfidence hampers decision making, but
does not fully account for the low success rate. Bayesian models
fail to explain these choices. These results are relevant for a wide
range of expert selection problems.
