The Politics of Modelling

Andrea Saltelli is based at Pompeu Fabra University in Barcelona. His most recent papers have tackled sensitivity analysis and auditing, the ecological footprint, the future of statistics, the rationale of evidence-based policy, the crisis of science and the post-truth discussion. Andrea gives courses in sensitivity analysis, sensitivity auditing, science integrity, and the ethics of quantification. He has recently published on the role of science in processes of regulatory capture.Monica Di Fiore is a researcher at the Institute for Cognitive Sciences and Technologies of the Italian National Research Council (CNR) of Rome. She has dealt with innovation and social acceptance of technologies.Her most recent work focuses on open science and responsible research and innovation, the reproducibility crisis, science-based normative capture, and the sociology and ethics of quantification. She recently contributed to a manifesto published by Nature on the quality of mathematical models.

• Foreword: Mathematically modelling as a critical cultural enterprise Wendy Espeland Preface: The sciences of modelling through Dan Sarewitz Part I - Meeting models 1: Introduction Monica Di Fiore and Andrea Saltelli 2: Pay no attention to the model behind the curtain Philip Stark Part II - The rules 3: Mind the framing: Match purpose and context Monica Di Fiore, Marta Kuc-Czarnecka, Samuele Lo Piano, Arnald Puy, and Andrea Saltelli 4: Mind the hubris: Complexity can misfire Arnald Puy and Andrea Saltelli 5: Mind the assumptions: Quantify uncertainty and assess sensitivity Emanuele Borgonovo 6: Mind the consequences: Quantification in economic and public policy Wolfgang Drechsler and Lukas Fuchs 7: Mind the unknowns: Exploring the politics of ignorance in mathematical models Andy Stirling Part III - The rules in practice 8: Sensitivity auditing: A practical checklist for auditing decision-relevant models Samuele Lo Piano, Razi Sheikholeslami, Arnald Puy, and Andrea Saltelli 9: Mathematical modelling: Lessons from composite indicators Marta Kuc-Czarnecka and Andrea Saltelli 10: Mathematical modelling, rulemaking, and the COVID-19 pandemic Ting Xu 11: In the twilight of probability: COVID-19 and the dilemma of the decision-maker Paolo Vineis and Luca Savarino 12: Models as metaphors Jerome R. Ravetz Epilogue: Those special models: A political economy of mathematical modelling Andrea Saltelli and Monica Di Fiore

The strong principle for the real world is: never use a model if you don't know its limitations and side effects. In fact, you must know what it can't do for you better than what it can do. I am glad this project is taking place: a long-awaited examination of the role-and obligation-of modeling.