Ways of thinking

But, how to think about such a complex world?

One approach is to break the complex world into smaller, more manageable pieces.

The argument goes that if we can understand the separate pieces, then we can put our separate understandings together to understand the whole.

This is reductionist, or Cartesian (after René DesCartes) Thinking.
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It works for simple things.
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Cartesian thinking fails to address complex problems because, in the process of breaking up the overall concern into parts, the connections and interactions between those parts get lost.
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Consider a comparison:-
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If you break a dry-stone wall apart, you end up with a pile of stones, with which you can rebuild the dry-stone wall - nothing lost, and perhaps even something gained in an improved wall
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Take a human-being apart, perhaps as a surgeon, and you end up with a pile of organs, bones, muscles, sinews...but you can never reconstitute the human being
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The difference?
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The whole human depends on the continued interaction between all the parts - in fact, the parts are all mutually dependent.
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So it turns out to be with complex systems - they are made up from many interacting, mutually dependent parts.
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Because of this it is often impractical to conduct experiments on them.
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Just imagine the social scientist, at the height of the prison riot, saying: "Stop just a tick guys, I want you all to tell me what your feelings are at this moment."
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Systems Thinking
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So, what is systems thinking?
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Fundamentally, of course, it is thinking about some world, or universe of discourse, in terms of open, interacting systems.
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Which can seem like nailing jelly to a wall in complex situations.
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So, the practice is growing and spreading of simulating systems behavior, using simple dynamic, non-linear simulations.
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Hence:
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Systems thinking seeks enlightenment through the creation and exploitation of open, interacting, nonlinear dynamic systems models of problems, situations and phenomena.
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Put into simpler terms, a problem, situation or phenomenon is first modeled as interacting systems, such that the model exhibits behaviors that replicate those of the problem, situation or phenomenon.
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The model is then used as a "learning laboratory," so that various aspects may be changed, augmented, rearranged, etc., to understand and to change behavior.
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Finally, it may be possible to propose and test some beneficial changes in the model, with reasonable expectations that corresponding changes in the real world would afford similar benefits.
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Systems thinking, then, is a way of understanding the complex real world we see about us, of managing its complexity, and of conceiving and testing ways of changing behavior "in vitro," with a view to implementing similar changes in vivo.
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System thinking is systems-scientific, and the models that it engenders are systems theoretic behavior models.
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They are, in general, nonlinear because the world they represent is nonlinear.
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They are also holistic, i.e., the models are of whole systems, without external, unqualified sources and sinks.
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And they are synthesized without reduction.
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In systems models, the interactions are as important as the systems
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The third archetype views the world as made up of feedback loops, such that cause and effect chains loop back upon themselves.
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This is the view held by cyberneticists and by advocates of non-linear dynamics and chaos.
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This viewpoint proposes that the world is largely chaotic and that you can no more predict the future from the past than you can predict next month's weather from last month's.
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System thinkers in this domain use Causal Loop Models (CLMs) and non-linear difference equation models.
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Often their models behave counter-intuitively, suggesting that the phenomenon they are thinking about may hold some surprises.
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Prof D. K. Hitchins