Abstract

We live in a time of rising complexity both in the internal workings of our social, economic and political systems and in the outcomes that those systems produce. Increasing complexity has implications for social science: it hinders our ability to predict and explain and to prevent large deleterious events. To make headway on the problems that animate social and behavioral scientists: economic inequality, health disparities, achievement gaps, segregation, climate change, terrorism, and polarization among voters we must acknowledge their complexity through interdisciplinary teams. Harnessing complexity will require several changes: we must develop practical measures of social complexity that we can use to evaluate systems; we must learn how to identify combinations of interventions that improve systems; we must see variation and diversity as not just noise around the mean, but as sources of innovation and robustness; and finally, we must support methodologies like agent-based models that are better suited to capture complexity. These changes will improve our ability to predict outcomes, identity effective policy changes, design institutions, and, ultimately, to transform society.

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