Uncertainty and quality should be integrated into the quantitative sciences of complex systems; this talk offers some practical techniques that illustrate how this could be accomplished.
The faith that truth lies in numbers goes back to the Pythagorean attempt to unify both practical and theoretical sciences. Its current manifestation is the idolisation of pre-Einsteinian physics in the quantification of social, economic, and behavioural sciences. The talk will explain how this "crisp number" mode of thinking has promoted the use of over-simplistic models and masking of uncertainties that can in turn lead to incomplete understanding of problems and bad decisions. The quality of a model in terms of its fitness for purpose can be ignored when convenience, especially computerised convenience, offers more easily calculated crisp numbers. Yet these inadequacies matter when computerised models generate pseudo-realities of their own through structures such as financial derivatives and processes such as algorithmic trading. Like Frankenstein's monster, we have already seen financial market pseudo-reality take on an uncontrolled, unstable and dangerous life of its own, all the more beguiling when it generated income for all parties in the merry-go-round. Despite its manifest failings, it is still going on.