The new study uses a Bayesian-style approach to show how people combine noisy or biased information with prior beliefs to form estimates. Treating inaccurate sources of information as part of the input—whether that inaccuracy comes from media, rumor, or personal bias—lets the model reproduce common misestimation patterns across many countries. Applied to large international surveys, the model finds that distortions play a smaller role than some earlier work implied, and that the same kinds of shared errors appear in very different cultural and political contexts.
This work matters for efforts to build fairer, more inclusive societies because it points to where corrective interventions might work. If uncertainty amplifies small inaccuracies into widely shared misperceptions, then improving how people encounter and process group information could reduce harm. The paper raises practical questions about communication, education, and policy that connect directly to how communities grow and include newcomers; the full article explores those implications in depth.
Abstract
Citizens in countries around the world dramatically overestimate the size of minority demographic groups and underestimate the size of majority groups. Media outlets and researchers have concluded that this pattern of errors is a result of characteristics of individual and societal distortions, such as the level of threat the group is imagined to pose and the amount of exposure someone has with the group. More recent work suggests that this error is a direct consequence of the psychological transformation of estimates under uncertainty. However, no work to date has provided an explanation for how distortion and uncertainty might jointly interact to produce people’s estimates. The goal of the current paper is to reconcile distortion and uncertainty-based accounts by providing a model that applies Bayesian inference to incorrect source information (presumed to result from external misinformation, or societal or individual distortions). We then apply that model to a broad set of international survey data and explore the cross-national structure of misestimation in expressed beliefs across a wide variety of topics. The results suggest that people are overall less and differently impacted by distortions than previous research has found, and that these distortions are often widely shared across quite distinct countries and groups.
