Uncertainty quantification plays a central role, particularly in the areas of artificial intelligence, big data and smart data as well as Industry and Factory 4.0. The aim here is to systematically recognise, measure and take into account uncertainties in data, models or forecasts.
Imagine a company uses artificial intelligence to predict the demand for products. Although the software works with a lot of data, there are always fluctuations, for example due to sudden changes in the weather or new trends. Uncertainty quantification helps to visualise these imponderables. Instead of just giving a fixed value, such as "1000 units will be sold next month", the model also shows how certain this prediction is - for example: "With 80% probability, we will sell between 900 and 1100 units."
Uncertainty quantification therefore ensures greater transparency and a better basis for decision-making. Companies can better assess risks, develop robust plans and react more flexibly. Uncertainty quantification is thus becoming an important tool for managers and decision-makers in the digital world.
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