Economics, complexity and futures studies
Underlying current dominant economic theory there is a built-in assumption of equilibrium. According to W Brian Arthur this emanate from the 1870:s when mathematics became the dominant language in the field. The transformation of economy to a mathematical field meant that required generalizations and abstractions, the core strength of mathemathics, was hiding the real world dynamics and implicitly shaped new assumptions of the world it tried to model.
This caused economics to become much better at predicting things. The problem was that it just predicted what would happen in a world where equilibrium was the default condition.
What happened on a deeper level was the field of economy unknowingly had removed the concept of time from the world they were studying.
Economic philosopers like e g Joan Robinson have observed this problem without having any impact on the field in general.
”Once we admit that economy exists in time, that history goes one way, from the irrevocable past into the unknown future, the conception of equilibrium [...] becomes untenable. The whole of traditional economics needs to be thought out afresh.”
I think this blindness to the aspects of time in the fields of economics is a key to understanding the difficult relations between entrepreneurs, strategists and even futurists on one hand and economists on the other. And maybe even the miscommunication between economists and politicians...?
One field that resisted being completely transformed by mathematics was biology. Because of that the language of biology is so compelling as metaphors for explaining the changes in our society.
From my point of view it is no coincidence that it was biology, information theory and the young field of computer science that became the fertile ground for developing the new understanding around ecology, systems, complexity et al. It was fields where the complex interaction of individual actors was impossible to ignore and change were the only constant.
Today we are gradually coming to understand that mathemathical abstractions must be accompanied by algorithms in order to be relevant in the real world which is complex and in constant change.
This is why we now see the birth of new areas of economics like e g Complexity Economics which is heavily based on algorithms and simulations in order to build a better theory of economics based on that non-equilibrium is the natural state rather than an exception.
As bystanders we will most likely continue to use the metaphors of algorithms, evolution and ecology, rather than the old mechanical metaphors to explain the world around us. On the surface we just don't think the mechanical metaphors are relevant any more. On a deeper level I think many of us already have changed our fundamental metaphore framing how we perceive the world we live in.
We are not seeing ourselves parts of a mechanical clockwork anymore. We are now increasingly seeing ourselves as interrelated actors in a dynamic and ever changing ecosystem.
Our institutions and bodies of skills, knowledge and theories are still carrying a heavy load of mechanistic bagage from the period before the enlightenment.
