The Politics of Modelling

Nassim Nicholas Taleb, Distinguished Professor of Risk Engineering, NYU Tandon School of Engineering. Author of the five-volume Incerto series (The Black Swan) 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.

Orrin H. Pilkey, Professor, Duke University's Nicholas School of the Environment, Co-author, with Linda Pilkey-Jarvis, of Useless Arithmetic: Why Environmental Scientists Can't Predict the Future, Columbia University Press, Washington, DC, 2009 The Politics of Modelling: Numbers between Science and Policy is a breath of fresh air and a much-needed cautionary view of the ever-increasing dependence on mathematical modelling in ever-widening directions. The five aspects of modelling that should be 'minded' are a sensitive summary of factors that should be considered when evaluating any mathematical model.

Wendy N. Espeland, Professor of Sociology, Northwestern University. The methods by which power insinuates itself into models, and facilitates their portability and amendments, are diverse and sometimes insidious. And that's one reason why the range of cases explored in The Politics of Modelling are so illuminating and why we need to pay attention to its authors. [...] Good scholarly books usually do one of two things. They dig into the details of something so that we understand it better, see it in a new light. We often call this depth. Or they bring things together in some creative amalgamation that allows us to make new comparisons, to see patterns we hadn't before seen. This we call breadth. It is rare when a book does both things well. This one does.

Theodore M. Porter, Department of History, UCLA, author of Trust in Numbers, Princeton University Press, Princeton, NJ, 1995 A modern Rip Van Winkle, awaking from a century of scientific slumbers, would be dismayed to find so much emphasis on models and so little talk of scientific laws and facts. Although Rip's dyspeptic view of models now seems misguided, a call for caution is very much in order. Modelling tools have consequences both for science and for a larger public, taking in historical, sociological, and moral perspectives as well as technical, scientific ones.

Anthony J. Sadar, Washington Times My decades of modeling operation and interpretation of results have been greatly expanded by the terrific perspective proffered in The Politics of Modelling.

Sondoss Elsawah, Environmental Modelling & Software, ScienceDirect If the road to change starts with recognition and self-awareness, then the book has done a significant service to the modelling community by naming the biases and calling out some of the dilemmas and risks deeply rooted in the modelling institution.

Sondoss Elsawah, ELSEVIER I strongly rec...

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