Course: ‘Sensitivity analysis, sensitivity auditing and beyond’
Advanced course directed towards PhD-candidates and postdoctoral fellows in quantitative sciences and in particular fields of research that produce evidence for public policy and decision making. Students from both the natural sciences, social sciences and health sciences are welcome.
The course moves from hard - mathematical modelling, number crunching and the benefits of sensitivity analysis, to soft - issues in the use of numbers in policy, passing by sensitivity auditing, an approach to the appraisal of model – generated evidence in adversarial settings. The course is useful for all students who either do or plan to do some modelling and to use model generated inference to tackle practical issues linked to social or environmental problems. The course stresses the non-neutrality of any technique, and the links between quantification and policy.
Date: February 6- 8, 2017
Trainers: Andrea Saltelli
Duration of lessons: 4h (3+1) 10.00-13.00 + 15.00-16.00 practicum
Deadline for applications: January 30th 2017
The course is free but places are limited.
- Monday 06.02.17
Lesson 1: Sensitivity analysis
Why most published sensitivity analysis are wrong; Good practices; A bit of calculus; Why sensitivity analysis helps to anticipate criticism; The case of the Stern Review; The secrets of sensitivity analysis;
Practicum on some elementary computation of sensitivity measures
- Tuesday 07.02.17
Lesson 2: Sensitivity auditing
The seven rules with illustrations; NUSAP; Quantitative story telling against hypocognition & Socially constructed ignorance; Decalogue of the diligent quantifier;
Practicum with example of frames
- Wednesday 08.02.17
Lesson 3: Ethics of quantification
Absurdities from the world of numbers; Science: is there a crisis? Causes and remedies; Why Quantify? Quantification and trust; Evidence based policy and its opposite; Evidence and power; Evidence as the currency of the lobbies; Plain cases of corruption; Evidence and the end of facts; Ancien regimes; The origins of the Cartesian dream; Climate blues and climate wars;
Practicum with group discussions.
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D. Saisana, M., Tarantola, S., 2008, Global Sensitivity Analysis. The Primer, John Wiley & Sons publishers.
Saltelli, A., D’Hombres, B., Sensitivity analysis didn't help. A practitioner's critique of the Stern review, 2010, Global Environmental Change, 20, 298-302.
Saltelli, A., Annoni, P., 2010, How to avoid a perfunctory sensitivity analysis, Environmental Modeling and Software, 25, 1508-1517.
Saltelli, A., Funtowicz, S., 2014, When all models are wrong: More stringent quality criteria are needed for models used at the science-policy interface, Issues in Science and Technology, Winter 2014, 79-85.
Chapter 2 in: Benessia, A., Funtowicz, S., Giampietro, M., Guimarães Pereira, A., Ravetz, J., Saltelli, A., Strand, R., van der Sluijs, J., 2015, The Rightful Place of Science: Science on the verge, Published by The Consortium for Science, Policy and Outcomes at Arizona State University.
Chapter 1 in: Benessia, A., Funtowicz, S., Giampietro, M., Guimarães Pereira, A., Ravetz, J., Saltelli, A., Strand, R., van der Sluijs, J., 2015, The Rightful Place of Science: Science on the verge, Published by The Consortium for Science, Policy and Outcomes at Arizona State University.
Audio-visual material: Workshop on responsible quantification, with videos.