When we try to manage systems of systems with both “hard” engineered aspects and “soft” living components we often have problems in achieving desired outcomes, in obtaining evidence of system change and in getting our act together in the first place – just think of the ongoing debates about climate change! After at least two decades we are still arguing about the predictions of global warming, what the goal might be and the best way to go about emissions control. In such debates science, politics, values and beliefs are completely intertwined.
Nevertheless we live in an age when scientific or “evidence based” management is all the rage. Government bureaucrats lie awake at night dreaming of effective and efficient evidence based policies. We are all in the thrall of computer modeling, big data, evidence, prediction and quantitative risk assessments – all the scientific machinery of the modern age. But this machinery has led us astray.
It is well worth going back and re-watching the series of films produced in 2011 by Adam Curtis for BBC2. In his film series “All watched over by machines of loving grace” Curtis produced a critique of the idea of the computer as a model of the world around us. The idea of the world as a computable machine was flawed but this realist, rationalist and materialistic approach to life has seriously infected all our intellectual and practical endeavors for centuries. Utopian dreams have always foundered in the end on human nature. Life is different.
We have uncritically transposed tools and techniques from the “hard” sciences to the “soft” and thereby created problems. Nonetheless, physics envy is alive and well in the land. In the Great Financial Crash it was partly physics envy that was our undoing. The modelers and the financial quants forgot about human behavior! There is a paper in the ArXiv entitled “Warning: physics envy may be hazardous to your wealth”. It was. More of the same will not do.
For about 300 years we have worked with a set of interlinked assumptions about the way the world is, best exemplified by Newton’s great achievements in physico-mathematics. No question, in the correct context this works brilliantly; and we have used the approach to build the modern world. We have built this world of ours by fixing all the simple problems – by assuming that the world could be modeled, and simulated, as a huge clockwork machine.
In this series of blogs I am going to break with convention and argue that if we are to make progress with 21st century systemic problems both the science and the social science – the knowledge and the practice – must be rethought. What was appropriate for the 17th and 18th centuries – when the world seemed limitless and new continents were being discovered and explored – is now longer appropriate for this modern, crowded planet. In effect I am going to try to rethink chunks of the entire Enlightenment project. A modest goal indeed!
Now, with over 7 billion of us inhabiting a system of systems largely of our own making we are experiencing – and trying to manage – a set of complex problems arising from the reflexive interconnections within and between living and inanimate systems. Complexity does not lend itself to a machine analogy. Complexity is, by definition, not simulable. So throwing ever more computer power at the problem has not worked, and will not work. There is no largest model – a model of everything – that will tell us what to do and guarantee results. Complex worlds are fundamentally uncertain and unpredictable.
Unfortunately the “world as machine” analogy is so deeply entrenched after 300 years that many (most) reject any such breach in the wall of scientific methodologies. At a Catchment Change Network meeting in UK in 2011 I heard consultants continue to call for scientists to produce a huge “model of everything” that would merely tell them what to do and where to restore river water quality and, furthermore, guarantee results!
It is time to reverse the Enlightenment project of subsuming all the “softer” sciences into the “exact” camp. Indeed, because we now face a large number of complex problems, the situation needs to be reversed: the “exact” sciences should be seen merely as a useful, but restricted, subset of a much larger set of ways of knowing. It is time to broaden our epistemology and to find new ways to rethink systems of systems and their management.
In a paper in Bioscience in 2006, Kevin Rogers and colleagues in South Africa wrote that is was time to develop a “fundamentally new course” for tackling these kinds of complex systems management problems. They likened the usual scientific approach to a horse race in which most of the horses were shot at the starting gate before the race got underway. Instead they advocated a more pluralistic approach in which “all horses (even those which appear lame at the first appearance) are nurtured and coaxed to their full capacity.” I am going to attempt to do a bit of coaxing.
So we have to live with complexity and irreducible uncertainty, and to tackle complex problems requires a fundamental change in the methodologies of systems science and in the dominant economic, and socio-political approaches. Since the Enlightenment we have followed an intellectual and ethical path in which the knowledge problem and the collective action problem have become one.
The idea of a clockwork universe coupled with the predominance of (Newtonian) reason and the privileging of the individual over the system has led us to where we are today. So to rethink the Enlightenment requires us to rethink everything from science to ethics, from economics to politics. A modest goal indeed! But, just maybe, if we can make some progress, some of the most intractable problems of the age might yet yield.