EXYSTENCE NoE
Seminar on 12 Nov 2004, Helsinki

Dr. Auli Keskinen, University of Tampere, Finland Futures Research Centre


The Relationship between Complexity Research and Futures Studies

Dr. Auli Keskinen:

I think that we could call complexity research and futures studies, sister sciences. They integrate conventional research areas, are multi-disciplinary and study phenomena of organisations which are multi-dimensional and multi-phased and so on. In order to create insight into what goes on we share sciences or sub-sciences which often complement each other though they may have their own approaches and methodologies.
Some of the issues are common. If we very briefly consider what the epistemology of futures studies is about there are actually two ways of approaching the acquisition of knowledge: it is the acquisition or creation of new knowledge and reprocessing existing knowledge. Quite different methodologies are needed in each case and we have to recognise that there are many different types of knowledge such as explicit and tacit knowledge and so on. Similar methods are used in the study of subsystems and heterarchic processes. There is often no hierarchy in the conventional sense in many of the common organisations that are changing today.
Another point we might consider here is how futures research is approaching a joint interest area and this is typical of multistakeholder studies. Different stakeholders can have a common or joint interest area and in approaching it you have to create a common language and understanding of what that is. What then happens in practice is that you go back and forth in a feedback process and there is a kind of hyper-cycle created in understanding and interaction processes. We are in a socially strong transition period and that's why we need new models all the time. If we ask what the slogans or buzz words are, then such terms as 'holism', 'heterarchy', 'hyper cycle' and 'humanism' are much used. What we are now facing with the ubiquitous change around the world is that we have a lot of pieces of information, like a mosaic and perhaps that is a good metaphor for the network of knowledge because when and if we can put these little pieces of knowledge together in an insightful way then we get a picture.
One of the important points about this metaphor is the scaling. If you go very close to the picture, so close that you put your nose on it, you only see one little piece and because of the 'noise' if you try to judge the whole picture you will go astray. But if you get further away you start to understand what kind of image is going to emerge; you create insight. Networks create a much more distorted picture than a mosaic and there are usually nodes which have very many connections and some that have very few connections. What can be studied with this kind of network is how robust it is; how well it can adapt if you destroy the connections in different places. This is important for information networks and social networks. If you destroy a well connected node the effect is very great, if you destroy one with few connections maybe nothing much happens. This is an important consideration in building networks. A random distribution of connections would be easier but social networks, for example, are never random. There are well connected people and people who are not. Where there are many well connected nodes the system is not easy to destroy.
We can see many examples of networks in our communications and there are some very simple rules determining the connectedness for any kind of network and of course the links themselves can be very different. One of the interesting studies of human network is the spread of contagious diseases. But the contagion need not be a disease, it might be an idea or it might be worry or fear. This is important for the people who need to control the spread.
The other thing I want to say something about the distribution of events which occur in networks. There is the famous example of the sand pile for which Per Bak pioneered the research some 15 or 20 years ago. Sand falls through a funnel grain by grain onto a sand pile and the size of avalanche created is noted. What was found out was that there are critical thresholds at which the pile collapses as different sized avalanches. This is an indication of how the energy dissipation in the system works. The natural world is actually full of this kind of self organised criticality. Perhaps you are all familiar with the Mandelbrot pattern which is possibly one of the most beautiful images that computers have created. Models which create these kinds of images can be made to simulate phenomena in nature and all kinds of other complex systems.
What we are facing today are a lot of new sciences that are not the conventional ones of the past but are integrative between the traditional paradigms. We can draw a new world map which shows how these have affected sciences such as geology, biology, energy science and information science thus filling gaps in the whole. Today there is a lot of emphasis on new technologies which are leading to new scientific paradigms. We live in a very confusing world and to bring out new insights is a very challenging job.