Paper short abstract:

Responsible quantification should communicate uncertainty, instead of uncertain results. Three scientific approaches are presented that use numbers as heuristic tools that allow for a participatory assessment of uncertainty, rather than as information.

Paper long abstract:

A lot of effort is invested in producing quantitative information for policy and a lot of criticism is directed towards the use of numbers in policy. One of the cornerstones of modern science is its reliance on the scientific method: the application of the same approach to all types of problems is supposed to ensure objectivity and reproducibility, to produce "matters of fact" (Shapin and Schaffer 1985). However, solving differential equations for calculating the risk of an earthquake may lead to mathematically sound results, but may be irrelevant in advising policy. If the goal is to advice policy makers about real world situations, how helpful is it to provide lab-created evidence? Providing real world evidence entails dealing with uncertainty, embracing complexity, and possibly producing non-conclusive results - but more relevant advice.

In this paper three approaches are analysed, which have emerged from these criticisms and propose responsible uses of quantitative information: (i) quantification of uncertainty through the NUSAP system of Post-Normal Science, (ii) the heuristic use of numbers through Quantitative Story-Telling and (iii) the heuristic use of statistics through Applied Statistics. The concept of responsible quantification emerges from these practices, favouring a heuristic use of numbers that can acknowledge uncertainty and complexity.

Shapin S & Schaffer S (1985) Leviathan and the air pump: Hobbes, Boyle and the experimental life. Princeton: Princeton University Press.