The Brookings Center on Social Dynamics and Policy applies complex systems science to the study of social dynamics and their implications for policy, mainly through the use of computational modeling and simulation. In a policy setting, complexity refers to situations in which responses to policy change may not be uniform or intuitive, due in part to feedback effects, time delays, interconnectedness, and non-linearity. In such situations, approaches from complex systems science can offer important advantages for the understanding of emergent social phenomena and the crafting of effective policy.
A central technique used at CSDP is agent-based computational modeling (ABM). This approach uses computerized artificial societies that are populated with entities called agents—simulated individuals, institutions, etc. Agents interact with each other and their environment according to specified decision rules. ABM models can be used study how key dynamics may be generated “from the bottom up” through the actions and interactions of individual agents, and how such dynamics may respond to policy changes. Data generated in ABM models can be directly compared to, and validated against, real-world data. This bottom-up approach often provides important insights into the causal mechanisms driving the outcomes of interest, and also provides a powerful and unique computational laboratory for policy experimentation. The computational environmental allows researchers to quickly and cost-effectively design and test a wide range of policy interventions while also considering heterogeneity across individuals and environments.
Application to policy research
To design effective policies in an increasingly complex, interdependent world, better understanding of causal mechanisms is needed. We must understand not just what factors play a role in a given phenomenon, but how and why these factors matter. Social dynamics are key drivers in the systems underlying many policy challenges—from the obesity epidemic to financial reform to ethnic conflict—and understanding such dynamics is the central focus of CSDP.