Uncertainty and Quality in Sciences for Policy
Course Leader: Roger Strand
In their seminal book Uncertainty and Quality in Science for Policy (Kluwer, 1990), Silvio Funtowicz and Jerome Ravetz analysed the strengths, limitations and problems of applying quantitative information in public decision-making, in particular in decisions on environmental and technological risk. By this effort they paved the way for what later has been known as the field of post-normal science. This is more than a philosophical theory on the relationship between science and public decision-making. It is also a field that has produced a number of concepts, methods and approaches to the characterisation and management of uncertainty and quality in evidence.
This course will provide a theoretical and practical introduction to a selection of these theoretical and methodological developments.
Funtowicz and Ravetz distinguished between technical, methodological and epistemic uncertainty. While the discipline of statistics provides concepts and methods for assessing and quantifying uncertainty at the technical level, other approaches are useful when dealing with methodological and epistemic uncertainty; the latter also known as ignorance.
This course will introduce various typologies for uncertainty, the so-called NUSAP approach and similar methods for the characterisation of uncertainty, the concept of sensitivity analysis and recent discussions on “extended peer review” and participatory approaches to knowledge production. In order to be able to apply such methods wisely, however, profound understanding of the philosophical and historical foundations of concepts of knowledge, evidence, probability, risk and uncertainty is needed. The course literature as well as some of the classes will accordingly go in depth on such theoretical issues.
Full course description (pdf)