Models and simulations have long been an indispensable instrument in science and policy. Without models we would be unable to imagine the impact of climate change, understand our financial systems, or design new physical infrastructures, to name some obvious examples. Today, experiments are often carried out in silico, and in many scientific disciplines muddy boots are being replaced by computational models. As models become a dominant form of knowledge, they shape policy-making across a multitude of domains: evidence-based decision-making increasingly means model-based decision-making.
This reliance on models and simulation brings forth new powers of anticipation, but also new vulnerabilities. What impact is the rise of modelling having on the very nature of research questions and projects being pursued in the sciences? How is simulation changing the nature of scientific evidence and claims to truth, and what does this mean for quality control and public policy? This seminar series will explore the role of modelling in contemporary science and policy, looking across domains and offering a comparative perspective on the power and limitations of modelling truths.
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