ABSTRACT
The previous chapter provided a detailed discussion of the basic principles of chaos theory and complexity. Attention was drawn to some of the essential features of chaos, particularly those relating to bifurcations (or period doubling), self-similarity, strange attractors and sensitivity to initial conditions. From this, it was established that dynamic systems which display sensitive dependence on initial conditions have a time evolution which is unpredictable. The state of a system at time + 1 cannot be known unless all the conditions at time = 0 can be specified. Clearly, in practice, this is an impossible task because, as discussed by Hobbs (1991), over time even differences at the quantum level will eventually be expressed at the macro level. It would not be surprising, then, if the reader concluded that chaos theory takes empirical research beyond the bounds of scientific certainty into the realms of the unknown and unknowable. However, this need not necessarily be the case. Of course the implications of chaos theory suggest that we will be bound by limitations in our endeavours to explain the social world and individual action, but this does not mean that nothing useful can be discerned. There may be limitations, but, as with weather forecasts which do in part predict the future, the application of chaos theory to the social sciences may also lead to new forms of understanding. At the very least we will know why we can predict so little.
