Kling starts by referring to a recent article by Jordan Greenhall for the proposition that:
With complex problems, we need to lower our expectations about our ability to arrive at fully satisfactory solutions.
Greenhall offers this illustration: the behavior of a simple bumblebee is complex, because it has response mechanisms that we do not fully understand; but a Boeing 747 is merely complicated, because its behavioral range is limited by a design and structure that we understand and can model.He then goes on to talk about economics and the (misnamed) "social sciences".
And perhaps, by understanding those differences, it will induce some humility in those who think they can solve any problem.When I was a graduate student in economics in the late 1970s, we were trained as if the economy is complicated, but not complex. We were told that if we learned enough mathematics and statistics and applied these tools, then eventually we could predict and control economic outcomes.In fact, economic behavior is complex. There are too many causal factors, feedback loops, non-linear effects, and unprecedented phenomena involved to enable economists to control the economy precisely and reliably. Often, the best mathematical models are not even useful, as was dramatically shown a decade ago by the failure to anticipate the financial crisis and its aftermath.In fact, complexity is a challenge in all of what we unfortunately call “the social sciences.” The very term social science gives the impression that human behavior is merely complicated, so that social outcomes can be predicted and managed by experts.
Many complicated problems have been solved by human beings and by our powerful computing tools. But I think this creates the expectation that we can solve complex problems as well. By understanding the difference between complication and complexity, we can take a more realistic view.