Author: Esko Kilpi
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Posted: April 10, 2012 736 views

One of the basic ideas of modern science is that the laws of the material universe can only be meaningfully understood by expressing quantified measurements. Numerical terms are needed, not just words and stories. Instead of ordinary sentences we must use mathematical equations, was the belief.

The values of the measurements at a given starting time are called initial conditions for that system. The Newtonian, deterministic claim is that for any given system, the same initial conditions will always produce identically the same outcome. Life is like a movie that can be run forwards or backwards in time.

One thing we have learned is that no real measurement is infinitely precise. All measurements necessarily include a degree of uncertainty. The uncertainty that is always present arises from the fact that all measuring devices can record measurements only with finite precision. To be able to reach infinite precision, the instrument we use should be able to display the outputs with infinite number of digits.

By using very accurate devices, uncertainty can often be made acceptable for the particular purpose, but it can never be eliminated completely. It is important to note that the uncertainty in the outcome does not arise from randomness in the equations, but from the lack of infinite accuracy in the initial conditions.

It used to be assumed that it was theoretically possible to obtain nearly perfect predictions by getting more precise information. Better instruments would shrink the uncertainty in the initial conditions, leading to shrinking imprecision in predictions. The lack of infinite precision was anyway thought to be a minor problem. Well, our belief systems are still mostly based on the idea that very small uncertainties don’t matter.

Possibly the first clear explanation of a very different kind of understanding was given in the late nineteenth century by the French mathematician Henri Poincaré. He was the founder of the modern dynamical systems theory. His claim was that there were systems that followed different laws: the tiniest imprecision in the initial conditions could grow in time. Two nearly indistinguishable sets of different initial conditions for the same system would then result in two developments that differed massively form one another. This is the reason why seemingly random behavior can emerge from deterministic systems with no external source of randomness.

Poincaré was way ahead of his time. His early thoughts gained evidence in 1963, when Edward Lorenz found, by accident, that even simple computer models of weather were subject to very sensitive dependence on initial conditions.

Numbers fool us and quantifies measurements are very rarely the whole picture. And we can’t go back in time – and stories matter more than we think.

Suggested reading:

The End of Certainty: Time, Chaos, and the New Laws of Nature by Iliya Prigogine. 1998. Chaos: Making a New Science by James Gleick. 1987

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About the author >

Esko Kilpi

Esko Kilpi is founder and principal in Esko Kilpi Oy, a leading research and consultancy firm working with the challenges of knowledge work and digital work environments. The organization is based in Helsinki, Finland. In addition to his work as an executive adviser Kilpi takes part in academic research and lectures on the topics of organizational learning, knowledge based view of the firm and interaction technologies as key enablers for knowledge based value creation in Nordic countries, Europe, Middle-East, Far-East and USA. He has published various articles on these subjects and is the co-author of a book on teams and process management (1996) and books on management challenges of the information age (2001, 2006). His teaching and research interests are about organizational contexts, where creative learning takes place and organizational dynamics for emergence of coherence and novelty. A large part of his work has concentrated on principles of organizational viability based on what can be learned from complexity sciences and theories of complex adaptive systems. At the moment Kilpi's work has focused on open source principles and social software implementations in organizational contexts. Kilpi has been a member of the advisory board of the World Bank on Knowledge Management. He has also been a member of the expert think tank on Knowledge Management for the European Union.

more information Weblog: http://eskokilpi.blogging.fi/

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