In case you haven't noticed, complexity and chaos science has been movin' and shakin' the natural-scientific world for several decades, leading to fabulous advances in everything from climate science to the human genome project to molecular physics. It's been breaking down disciplinary boundaries and leading to some life-affirming images that grip the popular imagination, from the notion of the earth being one system (Lovelock's beloved 'Gaia theory') to the notion that the flapping of a butterfly's wings can shape a tornado - even the smallest action, in the right circumstances, can make a profound difference. It's a science where the phrase 'we don't know' is common normal - a far cry from much of the rest of the world. But what does it mean for social sciences - and particularly, for practical action and sustainable development?
There's a dangerous breed of managerial consultant-type complexity-specialists (something of an oxymoron if you ask me) who take the language and then insert the latest management flashy answer underneath it. I'm not sure how much these guys really understand complexity and how much of it is window dressing. And there are those who doubt that the natural sciences can really help us understand the complexity of the social world. Oh, wait - that's the whole point. The social world - especially sustainable development - is super-complex. In fact, the problems that most of international sustainable development tries to deal with - poverty, disasters, conflict, international relationships, governance, empowerment, environmental-human systems - those are some of the most complex challenges we've got. So - yes, complexity has a lot to offer sustainable development. I'm not going to get into all of it here - though there's been some fascinating work done on it - but there's a few interesting illustrations I recently learned about that might help open the possibilities.
In many ways, complexity takes ideas that I, at least, thought were 'duh' and grounds them in the 'reality' of complexity science and mathematics. It's not just my common sense talking- the world really does respond better to some ways of thinking than to other ways. Let's take the problem of cause-effect (linear) kinds of thinking. Old pattern, based on Newton and the Cartesian world view: (A) leads to (B). Input leads to Output. Great for machines and much of the industrial revolution. And clocks. And all sorts of things - in a closed-system. Not so great when you start adding things like disgruntled workers into factories who want things like ownership. Or, in the case of sustainable development, when you think that natural disasters are unrelated to society - the notion that we can segregate the 'natural' from the 'social'. But if you take three factors (initial conditions, in complexity terminology) - say, a garbage dump, a poor slum city in south east asia on the edge of the ocean (near the new industrial harbour) and the regular tsunamis (or monsoon rains) that got a little bit worse from climate change, and you put them all together in such a way that the storm hits the garbage dump and the poor people who make their living picking through it, spreads it all over the places, kills people in the process and leads to weeks and months of disease and un-healthy conditions in an already impoverished context, and you've got a serious disaster. It's not just the disaster - its the way it interacts with the initial conditions and the social system. Trying to address just one of those issues isn't going to do much. You have to look at the system, and you have to reconise that those interactions are complex. Patterns can be distinguished, but not necessarily predicted. Which means you need to get out of the input-output mentality - or at least, recognise that while (A) might be necessary to create (B), in a complex situation, it is not enough. Sending aid is not enough. It has to be coupled with the reality on the ground; local ownership of the follow up projects, etc.
Sustainable Development is complex. It is well worth looking at how we can best use complexity theory to work in the field better - without pretending we know more than we do (which in my case, isn't much!)