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Precautions can only be taken versus the expectable. If a (computer) model of a system allows no uncertainty, and therefore reduces the set of possible responses to just a few, then we have to be ready to pay the consequences. Complex system fail, according to Mayntz, due to “the close coupling of parts of the system and processes, and the interactiveness caused by the high degree of complexity, the unforeseen influence of separate processes upon each other.” The existence of uncertainty has two outcomes. First, it can lead to conditions that are indeed unexpected, and which can lead to failure. Secondly, it can lead to unexpected and unknown reserves of stability or resistance, inducing one to think that his design is indeed robust. Prediction, of both failure or success, as the engineering community sees it, is, in effect, possible only in a world of determinism. The presence of uncertainty breaks the established mental schemes and requires a totally new approach. We should first of all realize that understanding is far more important than prediction. We can’t just turn everything into a game of forecasting. Forecasting techniques in economics have reached impressive levels of complexity but they fail to explain what is going on. To obtain new knowledge we must study reality and not idealizations of reality. Inevitably, when we speak of knowledge, philosophy is involved. Determinism, by definition, suppresses novelty, and therefore inhibits new knowledge from being acquired. In effect, determinism leaves little room for philosophy. Computers constitute a powerful means of creating problems of philosophical nature, yet people seldom pay any attention to philosophy. The big problem with Western culture is that it favors certainty over knowledge. The so-called predictive (i.e. deterministic) models - the fetish of our times - are not capable of delivering new knowledge. All they can do is return what has been hard-wired into them. In simulation language this is called unwrapping. Most people are happy with this reassuring placebo-generating philosophy of life. However, since the Universe is overwhelmingly uncertain, deterministic models are, in most cases, simply wrong. Decision-making based on such models can, consequently, only add more entropy to our business environment and therefore, paradoxically, increase uncertainty. Using large parallel computers today, to run deterministic models, is like using the slide-rule, in the slide-rule days, to simply draw straight lines.
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