Simple --> Complex

The reductionist spirit of the first Enlightenment yielded a passion for classification—of species, of races, of types of all kinds of things—and this had the virtue of clarifying and simplifying what had once seemed fuzzy. But Enlightenment mathematics was limited in its ability to depict complicated systems like ecosystems and economies. The second Enlightenment is giving us the tools to understand complexity, as Scott Page and John Miller explain in Complex Adaptive Systems. Such systems—whether they are stock markets or immune systems, biospheres or political movements—are made of interacting agents, operating interdependently and unpredictably, learning from experience at individual and collective levels. The patterns we see are not mere aggregations of isolated acts but are the dynamic, emergent properties of all these interactions. The way these patterns behave may not be predictable, but they can be understood. We understand now how whirlpools arise from turbulence, or how bubbles emerge from economic activity.

Liu, Eric; Hanauer, Nick (2011-12-06). The Gardens of Democracy: A New American Story of Citizenship, the Economy, and the Role of Government (Kindle Locations 307-314). Perseus Books Group. Kindle Edition. 
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Simple --> Complex
Atomistic --> Networked
Competition --> Cooperation
Efficient --> Effective
Equilibrium --> Disequilibrium
Independent --> Interdependent
Linear --> Non-linear
Mechanistic --> Behavioral
Predictive --> Adaptive
Rational calculator --> Irrational approximator
Selfish --> Strongly reciprocal
Win-lose --> Win-win or lose-lose
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