Stina Kjellgren / Universität Stuttgart
In recent years, advances in computer technology have enabled a new type of predictive science, in which sophisticated numerical models and data from past observations are used to foretell the behaviour of complex systems, such as the climate or extreme weather events. These predictions are very different from the ones used in traditional science with the aim of testing the explanatory power of scientific understanding. Whereas science has sometimes been seen as representing 'truth' and certain knowledge, this picture is difficult to apply to simulations, considering the epistemological uncertainty of models. The question is whether practitioners understand this, and what might happen if they don't?
Much hope is placed in predictions to guide policy making and reduce risk, but their effect is likely to depend on how they are understood and made use of. This lecture will touch upon insights from empirical studies on the translation of modelling results into practice, as well as theory on science-policy interaction, with the aim of providing a basic understanding of the factors likely to affect the societal contribution of predictive science.