摘要：SummaryDecision makers in contexts as diverse as medical, judicial, and political decision making are known to differ substantially in response bias and accuracy, and these differences are a major factor undermining the reliability and fairness of the respective decision systems. Using theoretical modeling and empirical testing across five domains, we show that collective systems based on pooling decisions robustly overcome this important but as of now unresolved problem of experts' heterogeneity. In breast and skin cancer diagnostics and fingerprint analysis, we find that pooling the decisions of five experts reduces the variation in sensitivity among decision makers by 52%, 54%, and 41%, respectively. Similar reductions are achieved for specificity and response bias, and in other domains. Thus, although outcomes in individual decision systems are highly variable and at the mercy of individual decision makers, collective systems based on pooling decrease this variation, thereby promoting reliability, fairness, and possibly even trust.Graphical abstractDisplay OmittedHighlights•Professional decision makers typically differ in their response bias and accuracy•Such differences undermine the reliability and fairness of decision systems•Pooling decisions reduces such variation in response bias and accuracy•This occurred in cancer diagnostics, fingerprint analysis, and forecastingdecision science; psychology
