Andrea Saltelli

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Andrea Saltelli
Photo of Andrea Saltelli.jpg
Born (1953-08-26) August 26, 1953 (age 70)
Rome, Italy
NationalityItalian
Alma mater Sapienza University of Rome
Organization(s) Pompeu Fabra University-Barcelona School of Management, University of Bergen (Norway) and National Research Council (Italy)

Andrea Saltelli (born August 26, 1953, in Rome, Italy) is an Italian scholar specializing in quantification using statistical and sociological tools. He has extended the theory of sensitivity analysis to sensitivity auditing, focusing on physical chemistry, environmental statistics, impact assessment and science for policy. He is currently Counsellor at the UPF Barcelona School of Management.

Contents

Biography

Saltelli earned his degrees in inorganic chemistry from Sapienza University of Rome in the summer of 1976. He then worked at the Italian Nuclear Authority ENEA and, for one year, at the Argonne National Laboratory in the United States. From 2005 to 2015, he worked at the Joint Research Centre of the European Commission, leading a team dedicated to econometrics and applied statistics. Between 2016 and 2020, he held the position of associate professor at the Centre for the Study of the Sciences and the Humanities (Senter for vitenskapsteori) at the University of Bergen. [1] [2]

Works

Andrea Saltelli has significantly contributed to the field of uncertainty and sensitivity analysis, [3] [4] [5] founding the SAMO (Sensitivity Analysis of Model Output) international conference series in 1995. [6] Saltelli has authored two handbooks on global sensitivity analysis, [7] [8] the most recent of which has been translated into Chinese. [9] His works introduced the concepts of global sensitivity analysis [10] and total sensitivity indices, [11] helping to popularize [12] the variance-based sensitivity analysis work of the Russian mathematician Ilya M. Sobol. [13] His formulae for efficiently computing variance-based sensitivity indices [10] have been widely adopted by practitioners. [14] [15] Saltelli has applied his expertise to diverse fields, including climate change, [16] ranking of higher education, [17] ecological footprint, [18] and composite indicators. [19] [20] His recent research focuses on the reproducibility of scientific results, [21] [22] principles for mathematical modelling [23] [24] and the ethics of quantification. [25] [26]

Andrea Saltelli has collaborated with Silvio Funtowicz, Jerome R. Ravetz and Jeroen van der Sluijs on the theories and applications of post-normal science. [27] He has also worked with the Belgian sociologist Paul-Marie Boulanger on the application of Niklas Luhmann's theories to the reproducibility crisis in scientific research [28] and to the COVID-19 pandemic. [29] Furthermore, Saltelli has collaborated with the Norwegian economist Erik Reinert on themes related to quantification in economics, [30] [31] and with Daniel Sarewitz on the post-truth debate. [32]

Sensitivity auditing

In an interview for 'The Corbet Report', [33] Saltelli shared his early fascination with generating quantified evidence through statistical or mathematical modelling, highlighting his concern over how easy it is to produce poor-quality evidence, if not to manipulate data or deceive with numbers. This concern drove his engagement with issues in the fields of epistemology, philosophy of science, and science for policy [33] surrounding the responsible production of data.

This same concern led him to extend the theory of sensitivity analysis to sensitivity auditing, which aims to assess the entire process of knowledge and model generation, including explicit or implicit assumptions, interests, stakes and motivations on part of the developers. [34] According to existing guidelines [35] including those from the European Commission, [36] sensitivity auditing becomes particularly relevant when modelling results influence political decision-making processes.

Books

Related Research Articles

The ecological footprint measures human demand on natural capital, i.e. the quantity of nature it takes to support people and their economies. It tracks human demand on nature through an ecological accounting system. The accounts contrast the biologically productive area people use to satisfy their consumption to the biologically productive area available within a region, nation, or the world (biocapacity). Biocapacity is the productive area that can regenerate what people demand from nature. Therefore, the metric is a measure of human impact on the environment. As Ecological Footprint accounts measure to what extent human activities operate within the means of our planet, they are a central metric for sustainability.

Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system can be divided and allocated to different sources of uncertainty in its inputs. A related practice is uncertainty analysis, which has a greater focus on uncertainty quantification and propagation of uncertainty; ideally, uncertainty and sensitivity analysis should be run in tandem.

<span class="mw-page-title-main">Post-normal science</span> Approach to the use of science on urgent issues involving uncertainty in facts and moral values

Post-normal science (PNS) was developed in the 1990s by Silvio Funtowicz and Jerome R. Ravetz. It is a problem-solving strategy appropriate when "facts [are] uncertain, values in dispute, stakes high and decisions urgent", conditions often present in policy-relevant research. In those situations, PNS recommends suspending temporarily the traditional scientific ideal of truth, concentrating on quality as assessed by internal and extended peer communities.

<span class="mw-page-title-main">Jerome Ravetz</span> American philosopher

Jerome (Jerry) Ravetz is a philosopher of science. He is best known for his books analysing scientific knowledge from a social and ethical perspective, focussing on issues of quality. He is the co-author of the NUSAP notational system and of Post-normal science. He is currently an Associate Fellow at the Institute for Science, Innovation and Society, University of Oxford.

Published in 1991 by Max Morris the elementary effects (EE) method is one of the most used screening methods in sensitivity analysis.

In applied statistics, the Morris method for global sensitivity analysis is a so-called one-step-at-a-time method, meaning that in each run only one input parameter is given a new value. It facilitates a global sensitivity analysis by making a number r of local changes at different points x(1 → r) of the possible range of input values.

Variance-based sensitivity analysis is a form of global sensitivity analysis. Working within a probabilistic framework, it decomposes the variance of the output of the model or system into fractions which can be attributed to inputs or sets of inputs. For example, given a model with two inputs and one output, one might find that 70% of the output variance is caused by the variance in the first input, 20% by the variance in the second, and 10% due to interactions between the two. These percentages are directly interpreted as measures of sensitivity. Variance-based measures of sensitivity are attractive because they measure sensitivity across the whole input space, they can deal with nonlinear responses, and they can measure the effect of interactions in non-additive systems.

<span class="mw-page-title-main">Index (statistics)</span> Statistical term, a compound measure in statistics

In statistics and research design, an index is a composite statistic – a measure of changes in a representative group of individual data points, or in other words, a compound measure that aggregates multiple indicators. Indexes – also known as composite indicators – summarize and rank specific observations.

Sensitivity auditing is an extension of sensitivity analysis for use in policy-relevant modelling studies. Its use is recommended - i.a. in the European Commission Impact assessment guidelines and by the European Science Academies- when a sensitivity analysis (SA) of a model-based study is meant to demonstrate the robustness of the evidence provided by the model in the context whereby the inference feeds into a policy or decision-making process.

NUSAP is a notational system for the management and communication of uncertainty in science for policy, based on five categories for characterizing any quantitative statement: Numeral, Unit, Spread, Assessment and Pedigree. NUSAP was introduced by Silvio Funtowicz and Jerome Ravetz in the 1990 book Uncertainty and Quality in Science for Policy. See also van der Sluijs et al. 2005.

<span class="mw-page-title-main">Ilya M. Sobol'</span> Russian mathematician (born 1926)

Ilya Meyerovich Sobol’ is a Russian mathematician, known for his work on Monte Carlo methods. His research spans several applications, from nuclear studies to astrophysics, and has contributed significantly to the field of sensitivity analysis.

<i>Uncertainty and Quality in Science for Policy</i>

Uncertainty and Quality in Science for Policy is a 1990 book by Silvio Funtowicz and Jerome Ravetz, in which the authors explain the notational system NUSAP and applies it to several examples from the environmental sciences. The work is considered foundational to the development of post-normal science.

<span class="mw-page-title-main">Silvio Funtowicz</span> Philosopher of science

Silvio O. Funtowicz is a philosopher of science active in the field of science and technology studies. He created the NUSAP, a notational system for characterising uncertainty and quality in quantitative expressions, and together with Jerome R. Ravetz he introduced the concept of post-normal science. He is currently a guest researcher at the Centre for the Study of the Sciences and the Humanities (SVT), University of Bergen (Norway).

<i>Science on the Verge</i>

Science on the verge is a book written in 2016 by group of eight scholars working in the tradition of Post-normal science. The book analyzes the main features and possible causes of the present science's crisis.

<i>The No Nonsense Guide To Science</i> 2006 non-fiction book by Jerome Ravetz

The No Nonsense Guide to Science is a 2006 book on Post-normal science (PNS). It was written by American born British historian and philosopher of science Jerome Ravetz.

The sociologyof quantification is the investigation of quantification as a sociological phenomenon in its own right.

Sensitivity analysis studies the relation between the uncertainty in a model-based the inference and the uncertainties in the model assumptions. Sensitivity analysis can play an important role in epidemiology, for example in assessing the influence of the unmeasured confounding on the causal conclusions of a study. It is also important in all mathematical modelling studies of epidemics.

Sensitivity analysis studies the relationship between the output of a model and its input variables or assumptions. Historically, the need for a role of sensitivity analysis in modelling, and many applications of sensitivity analysis have originated from environmental science and ecology.

<span class="mw-page-title-main">Paul-Marie Boulanger</span> Belgian sociologist

Paul-Marie Boulanger is a Belgian sociologist active in the study of sustainable development and consumption.

The Politics of Modelling, Numbers Between Science and Policy is a multi-authors book edited by Andrea Saltelli and Monica Di Fiore and published in August 2023 by Oxford University Press.

References

  1. ↑ ORCID, andrea saltelli (0000-0003-4222-6975) , retrieved 15 March 2024
  2. ↑ UIB-SVT, Andrea Saltelli at UIB , retrieved 15 March 2024
  3. ↑ Norton, J., 2015. An introduction to sensitivity assessment of simulation models. Environmental Modelling & Software 69, 166–174.
  4. ↑ Borgonovo, E., Plischke, E., 2016. Sensitivity analysis: A review of recent advances. European Journal of Operational Research 248, 869–887.
  5. ↑ Da Veiga, Sébastien, Fabrice Gamboa, Bertrand Iooss, and Clémentine Prieur. 2021. Basics and Trends in Sensitivity Analysis. SIAM.
  6. ↑ [Groupement de Recherche MASCOT-NUM], "SAMO Meetings," 2019. [Online]. Available: https://www.gdr-mascotnum.fr/samo.html. [Accessed: 22-Nov-2020].
  7. ↑ Saltelli A., Tarantola S., Campolongo F. and Ratto M. (2004) Sensitivity Analysis in practice. A guide to assessing scientific models, New York: John Wiley & Sons.
  8. ↑ 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.
  9. ↑ "Private Domain". cfe.m.jd.com. Retrieved 2024-03-10.
  10. 1 2 Saltelli A., 2002, Making best use of model evaluations to compute sensitivity indices, Computer Physics Communications, 145, 280-297.
  11. ↑ Homma T., and Saltelli A., 1996, Importance measures in global sensitivity analysis of model output, 1996, Reliability Engineering and System Safety, Vol. 52 No. 1 1-17.
  12. ↑ Toshimitsu HOMMA and Andrea SALTELLI, 2005, Use of Sobol's Quasirandom Sequence Generator for Integration of Modified Uncertainty Importance Measure, Journal of Nuclear Science and Technology, 32:11, 1164-1173.
  13. ↑ A. Saltelli, I.M. Sobol', About the use of rank transformation in sensitivity analysis of model output, Reliability Engineering and System Safety 50 (1995) 225–239.
  14. ↑ Owen, Art B. 2013. "Variance Components and Generalized Sobol' Indices." SIAM/ASA Journal on Uncertainty Quantification 1 (1): 19–41.
  15. ↑ Owen, Art B., Josef Dick, and Su Chen. 2014. "Higher Order Sobol' Indices." Information and Inference: A Journal of the IMA 3 (1): 59–81.
  16. ↑ 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.
  17. ↑ Paruolo, P., Saisana, A., Saltelli, A., 2013, Ratings and rankings: Voodoo or Science? Journal Royal Statistical Society A, 176 (3), 609–634.
  18. ↑ Giampietro, M., and Saltelli, A., 2014, Footprints to nowhere, Ecological Indicators, 46, 610–621.
  19. ↑ OECD-JRC Handbook On Constructing Composite Indicators: Methodology And User Guide, OECD Statistics Working Paper JT00188147, STD/DOC(2005)3.
  20. ↑ Kuc-Czarnecka, M., Lo Piano, S. and Saltelli, A. (2020) 'Quantitative storytelling in the making of a composite indicator', Social Indicators Research, 149(3), 775-802, 2020.
  21. ↑ Philip B. Stark and Andrea Saltelli, Cargo-cult statistics and scientific crisis, SIGNIFICANCE, 05 July 2018.
  22. ↑ Andrea, Saltelli (2018-12-01). "Why science's crisis should not become a political battling ground". Futures. 104: 85–90. doi:10.1016/j.futures.2018.07.006. hdl: 10609/93175 . ISSN   0016-3287.
  23. ↑ Saltelli, Andrea (2019-08-27). "A short comment on statistical versus mathematical modelling". Nature Communications. 10 (1): 3870. Bibcode:2019NatCo..10.3870S. doi:10.1038/s41467-019-11865-8. ISSN   2041-1723. PMC   6712000 . PMID   31455789.
  24. ↑ A. Saltelli, G. Bammer, I. Bruno, E. Charters, M. Di Fiore, E. Didier, W. Nelson Espeland, J. Kay, S. Lo Piano, D. Mayo, R.J. Pielke, T. Portaluri, T.M. Porter, A. Puy, I. Rafols, J.R. Ravetz, E. Reinert, D. Sarewitz, P.B. Stark, A. Stirling, P. van der Sluijs, Jeroen P. Vineis, Five ways to ensure that models serve society: a manifesto, Nature 582 (2020) 482–484.
  25. ↑ Saltelli, Andrea; Di Fiore, Monica (2020-08-19). "From sociology of quantification to ethics of quantification". Humanities and Social Sciences Communications. 7 (1): 1–8. doi:10.1057/s41599-020-00557-0. ISSN   2662-9992.
  26. ↑ UCL (2021-01-21). "Why ethics of quantification is needed now". UCL Institute for Innovation and Public Purpose. Retrieved 2024-03-10.
  27. ↑ Andrea Saltelli, Lorenzo Benini, Silvio Funtowicz, Mario Giampietro, Matthias Kaiser, Erik Reinert, Jeroen P. van der Sluijs, 2020, The technique is never neutral. How methodological choices condition the generation of narratives for sustainability, Environmental Science and Policy, Volume 106, Pages 87-98.
  28. ↑ A. Saltelli and P.-M. Boulanger, "Technoscience, policy and the new media. Nexus or vortex?," Futures, vol. 115, p. 102491, Nov. 2019.
  29. ↑ P.-M. Boulanger and A. Saltelli, "Pandemic Luhmann," SSRN Electron. J., May 2020.
  30. ↑ Erik Reinert, Sylvi Endresen, Ioan Ianos, and Andrea Saltelli, 2016, "Epilogue: The Future of Economic Development between Utopias and Dystopias", in Handbook of alternative theories of economic development, Edited by Erik S. Reinert, Jayati Ghosh, and Rainer Kattel, Elgar Publishing, see here for the working paper version.
  31. ↑ UCL (2021-03-16). "Altered States: Ricardian and Cartesian dreams". UCL Institute for Innovation and Public Purpose. Retrieved 2024-03-10.
  32. ↑ "Reformation in the Church of Science". The New Atlantis. Retrieved 2024-03-10.
  33. 1 2 J. Corbett, "Interview 1424 – Andrea Saltelli on The Crisis of Science," The Corbett Report, 2019.
  34. ↑ Saltelli, A., van der Sluijs, J., Guimarães Pereira, Â., 2013, Funtowiz, S.O., What do I make of your Latinorum? Sensitivity auditing of mathematical modelling, International Journal Foresight and Innovation Policy, 9 (2/3/4), 213–234.
  35. ↑ Science Advice for Policy by European Academies, Making sense of science for policy under conditions of complexity and uncertainty, Berlin, 2019.
  36. ↑ European Commission, November 2021. Better Regulation: Guidelines and Toolbox
  37. ↑ "Sensitivity Analysis | Wiley". Wiley.com.
  38. ↑ "Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models | Wiley". Wiley.com.
  39. ↑ "Global Sensitivity Analysis: The Primer | Wiley". Wiley.com.
  40. ↑ "Science on the Verge; CSPO". CSPO.org/publication/.
  41. ↑ "The Politics of Modelling; Wiley". Wiley.com.

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