Resilience in Complex Systems
Our everyday lives revolve around well-abstracted systems that have clear cause and effect mechanisms. I flip a switch, the light turns on; the specifics of the electricity grid are irrelevant. I keep money at the bank, the bank gives me interest. I pay for supplies at the store, now I can take them home.
But when it comes to changing systems, our everyday cause and effect intuition fails us. Increasing dollars spent per child at schools doesn’t seem to improve educational outcomes. (Where does the money go?). Countries that impose travel restrictions a few days before their neighbors have exponentially lower fatalities from COVID-19. Teams whose members gel well outperform teams with more accomplished individuals, but lower team cohesion.
This essay briefly explores these phenomena through the paradigm of systems thinking. Of particular interest are a class of systems called Complex Systems, which seem to evade reductionist, clean explanations. They’re complex, not because they’re complicated; it’s because even simple yet nonlinear interactions between their components give rise to rich behavior that cannot be understood in terms of any one individual factor (Meadows, 1982). Our goal here is to take a “whole systems” view of why many of these complex systems exhibit resilience to change, by examining their underlying dynamics; more specifically, their attractors.
We start by exploring attractors with the Lorenz system, then introduce causal loop diagrams as duals to differential equations, concluding with the impacts of attractors on climate change policies.
