Mathematical models are used to inform decisions across many sectors including climate change, finance, and epidemics. But as Erica Thompson explains in this Oxford Mathematics Public Lecture, models are not perfect representations of the real world – they are partial, uncertain and often biased.  What, then, does responsible modelling look like?  And how can we apply this ethical framework to new AI modelling methods?

Oxford Mathematician Mike Giles is a computational mathematician who has worked at the interface with both engineering and computer science. His early research was on computational fluid dynamics, developing algorithms and software which is today used by Rolls-Royce in the design of its aircraft engines. More recently, he moved into computational finance and more generally the area of Uncertainty Quantification, developing advanced Monte Carlo simulation methods