Adapting to Uncertainty: Complexity Science and COVID-19
JUNE 10, 2020
What are complex systems, why are they so hard to predict, and what can complexity science tell us about how we can respond to the novel coronavirus and ultimately defeat it?
- Both human society and the COVID-19 pandemic are complex adaptive systems. That is, they are dynamic networks of independent and interconnected agents that adapt to their environments.
- Complex systems exhibit emergent behavior — the whole is more than the sum of its parts — which makes them hard to study, predict, or control with conventional analytical tools.
- Complexity science offers clues for how society can fight this virus while minimizing the risk of cascading failures. In periods of high uncertainty, we need to prioritize adaptability over efficiency, distributed processing over hierarchical processing, evolution over design, and experimentation over mandates.
- During this adaptive period, central governments should focus on facilitating innovation and the free flow of information and resources across society.
- Complexity science also offer lessons for solving other stubborn problems that have long plagued society.