(click to copy)


Implicit racial biases are lower in more populous more diverse and less segregated US cities

Implicit biases – differential attitudes towards members of distinct groups – are pervasive in human societies and create inequities across many aspects of life.

Recent research has revealed that implicit biases are generally driven by social contexts, but not whether they are systematically influenced by the ways that humans self-organize in cities.

We leverage complex system modeling in the framework of urban scaling theory to predict differences in these biases between cities. Our model links spatial scales from city-wide infrastructure to individual psychology to predict that cities that are more populous, more diverse, and less segregated are less biased.

We find empirical support for these predictions in U.S. cities with Implicit Association Test data spanning a decade from 2.7 million individuals and U.S. Census demographic data. Additionally, we find that changes in cities’ social environments precede changes in implicit biases at short time-scales, but this relationship is bi-directional at longer time-scales.

We conclude that the social organization of cities may influence the strength of these biases.

A.J. Stier, S. Sajjadi, F. Karimi, L.M.A. Bettencourt, M.G. Berman, Implicit racial biases are lower in more populous more diverse and less segregated US cities, Nature Communications 15 (2024) 961.

Sina Sajjadi, PhD Candidate at the Complexity Science Hub © Verena Ahne

Sina Sajjadi

Fariba Karimi, Faculty Member at the Complexity Science Hub © Matthias Raddant

Fariba Karimi

Luis Bettencourt

0 Pages 0 Press 0 News 0 Events 0 Projects 0 Publications 0 Person 0 Visualisation 0 Art


CSH Newsletter

Choose your preference
Data Protection*