Can science predict the future?

DrThe world as a kind of clock mechanism, at its core is simple and predictable – that was a recent idea in the 18th century. In such a world, science has provided a method of being able to see the future on the basis of data and laws – in principle with the required accuracy, as long as the quality of the data is correct. Great thinkers were proponents of this idea, such as Isaac Newton for example or John Stuart Mill, and the idea of ​​a predictable world is undoubtedly a completely magical idea. However, today, some 300 years later, we know that this is a mistake. Because complex systems of the kind that unfortunately dominate the world operate completely differently.

Complex systems require unpleasant things like statistics, and tedious distinctions like those between correlation and causation. Infinite influences and factors interact in it. Some of them are sensitive to the smallest changes in parameters. All opaque cannot be properly reduced to manageable parts. The beautiful world of facts and certainty turns black and white into ugly gray tones of probability and error assessments.

When Model Predictions Fail

This is disappointing. The resulting frustration is still being felt today. One can recognize them, for example, in the accusation against the designers of epidemiology that their “model predictions” did not come true. Also in the demand to make the models “better”, to incorporate more parameters, more factors. This raises the hope that being able to accurately predict is something that can be achieved if you put in a little effort. One can leave statistics, the things that cannot be measured, behind and gain security – because who wants to make decisions based on unverified data?

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One might try to admit that studying complex systems can hardly produce more classic guarantees than a bankruptcy sale. One can refuse to write down scientific results until science clearly “shows” that anything is all right. A more productive position is to acknowledge that our modern understanding of our complex world is also changing the approach to scientific findings. This is where the often-invoked difference these days between scenarios and predictions comes into play.

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