Paul Cilliers Webcast : Read the Summary

Knowing Complex Systems. The limits of understanding

Due to their non-linear nature, complex systems are incompressible. They are also open systems and cannot be understood without also understanding their environments and their history. To fully know something complex will therefore involve incorporating all the complexity of the system and its environment. This not humanly possible, perhaps not even possible in principle. Thus, our models of complex systems always have to reduce the complexity. Since what is left out also has non-linear effects, we cannot predict the error made in the reduction. The modelling and understanding of complex system thus always involve an element of choice which cannot be justified by pure calculation. There is always a normative element involved.

This is not an argument against calculation, but a justification for why formal models will always have to be supplemented by narratives which make the limits of the model explicit. At the same time, the narrative models are also limited to a certain perspective. It can thus be argued that there is an irreducible ethical component to our understanding of complexity. We have to accept the responsibility for our models although we know they are flawed. When dealing with complexity there are simultaneous roles for the natural and the human sciences, for both mathematics and imagination.

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Cilliers, P. (2001). "Boundaries, hierarchies and networks in complex systems." International Journal of Innovation Management, 5 (2): pp. 135–147.

Khalil, E.L. and Boulding, K.E. (eds.) (1996). Evolution, Order and Complexity. London: Routledge.

Rosen, R. (1996). "On the limitations of scientific knowledge." In, J.L. Casti and A. Karlqvist (Eds.), Boundaries and Barriers. On the Limitations of Scientific Knowledge. Reading, Massachusetts: Addison Wesley: pp. 199–214.