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Assessment of Sustainability is Essential for Performability Evaluation Read chapter Read first chapter

2021 | OriginalPaper | Chapter

28. The Neglected Pillar of Science: Risk and Uncertainty Analysis

Author : Terje Aven

Published in: Handbook of Advanced Performability Engineering

Publisher: Springer International Publishing

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Abstract

Science, in general, is built on two pillars: on the one hand, confidence, obtained through research and development, analysis, argumentation, testing, data and information, and on the other humbleness, acknowledging that the knowledge—the justified beliefs—generated can be more or less strong and even erroneous. The main thesis of the present conceptual work is that the latter pillar—humbleness—has not been given the scientific attention it deserves. This pillar is founded on risk and uncertainty analysis, but the fields of this type of analysis are weak, lacking authority. The volume of research on risk and uncertainty analysis is small and the quality of current approaches and methods is not satisfactory. A strengthening of the fields of risk and uncertainty analysis is urgently and strongly needed. Several suggestions for how to meet these challenges are presented, including measures to stimulate further research on the fundamentals of these fields—and crossing established study borders, and initiatives to be taken by relevant societies to increase the awareness of the issue and deriving suitable strategies for how to develop risk and uncertainty analysis as a distinct science.

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Literature
1.
Aven, T. (2020). The science of risk analysis. New York: Routledge.
2.
Flanders, W. D., Lally, C. A., Zhu, B.-P., Henley, S. J., & Thun, M. J. (2003). Lung cancer mortality in relation to age, duration of smoking, and daily cigarette consumption. Cancer Research, 63, 6556–6562.
3.
Yamaguchi, N., Kobayashi, Y. M., & Utsunomiya, O. (2000). Quantitative relationship between cumulative cigarette consumption and lung cancer mortality in Japan. International Journal of Epidemiology, 29(6), 963–968.CrossRef
4.
Proctor, R. N. (2011). The history of the discovery of the cigarette–lung cancer link: Evidentiary traditions, corporate denial, global toll. Tobacco Control, 21, 87–91.CrossRef
5.
ITC Netherlands Survey. (2011). Report on smokers’ awareness of the health risks of smoking and exposure to second-hand smoke. Ontario, Canada: University of Waterloo.
6.
IPCC Guidance Notes for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties: IPCC Cross Working Group Meeting on Consistent Treatment of Uncertainties, 2010.
7.
8.
9.
Aven, T., & Renn, O. (2015). An evaluation of the treatment of risk and uncertainties in the IPCC Reports on Climate Change. Risk Analysis, 35(4), 701–712 (Open access).
10.
11.
Aven, T. (2017). The flaws of the ISO 31000 conceptualisation of risk. Journal of Risk and Reliability, Editorial, 231(5), 467–468 (Open access).
12.
Aven, T., & Ylönen, M. (2019). The strong power of standards in the safety and risk fields: A threat to proper developments of these fields? Reliability Engineering and System Safety, 189, 279–286 (Open access).
13.
14.
15.
Hansson, S. O. (2013). Defining pseudoscience and science. In M. Pigliucci & M. Boudry (Eds.), Philosophy of pseudoscience. Chicago, IL: University of Chicago Press.
16.
Hansson, S. O., & Aven, T. (2014). Is risk analysis scientific? Risk Analysis, 34(7), 1173–1183.CrossRef
17.
Aven, T., & Ylönen, M. (2018). The enigma of knowledge in the risk field. In T. Aven & E. Zio (Eds.), Knowledge in risk assessments. NY: Wiley.
18.
Bourdieu, P., & Wacquant, L. J. D. (1992). An invitation to reflexive sociology. Chicago: University of Chicago Press.
19.
Aven, T. An emerging new risk analysis science: Foundations and implications. Risk Analysis, 38(5), 876–888 (Open access).
20.
Aven, T., & Zio, E. (2014). Foundational issues in risk analysis. Risk Analysis, 34(7), 1164–1172.CrossRef
21.
Lindley, D. V. (2000). The philosophy of statistics. The Statistician, 49, 293–337 (With discussions).
22.
Aven, T. (2013). How to define and interpret a probability in a risk and safety setting. Discussion paper Safety Science, with general introduction by Associate Editor. Genserik Reniers, 51(1), 223–231.
23.
24.
Aven, T. (2011a). Quantitative risk assessment: The scientific platform. Cambridge University Press.
25.
Bergman, B. (2009). Conceptualistic pragmatism: A framework for Bayesian analysis? IIE Transactions, 41, 86–93.CrossRef
26.
Deming, W. E. (2000). The new economics (2nd ed.). Cambridge, MA: MIT CAES.
27.
Lewis, C. I. (1929). Mind and the world order: Outline of a theory of knowledge. New York, NY: Dover Publications.
28.
Cowell, R. G., Dawid, A. P., Lauritzen, S. L., & Spiegelhalter, D. J. (1999). Probabilistic networks and expert systems. New York: Springer.MATH
29.
30.
31.
Bedford, T., & Cooke, R. (2001). Probabilistic risk analysis. Cambridge: Cambridge University Press.CrossRef
32.
Lindley, D. V. (1985). Making decisions. New York: Wiley.
33.
Kaplan, S., & Garrick, B. J. (1981). On the quantitative definition of risk. Risk Analysis, 1, 11–27.CrossRef
34.
Miller, B. (2013). When is consensus knowledge-based? Distinguishing shared knowledge from mere agreement. Synthese, 190, 1293–1316.CrossRef
35.
Flage, R., & Aven, T. (2009). Expressing and communicating uncertainty in relation to quantitative risk analysis (QRA). Reliability and Risk Analysis: Theory and Applications, 2(13), 9–18.
36.
Aven, T., & Flage, R. (2018). Risk assessment with broad uncertainty and knowledge characterisations: An illustrating case study. In T. Aven & E. Zio (Eds.), Knowledge in risk assessments. NY: Wiley.
37.
Funtowicz, S. O., & Ravetz, J. R. (1990). Uncertainty and quality in science for policy. Dordrecht: Kluwer, Academic Publishers.
38.
Funtowicz, S. O., & Ravetz, J. R. (1993). Science for the post-normal age. Futures, 25, 735–755.CrossRef
39.
Kloprogge, P., van der Sluijs, J., & Petersen, A. (2005). A method for the analysis of assumptions in assessments. Bilthoven, The Netherlands: Netherlands Environmental Assessment Agency (MNP).
40.
Kloprogge, P., van der Sluijs, J. P., & Petersen, A. C. (2011). A method for the analysis of assumptions in model-based environmental assessments. Environmental Modelling and Software, 26, 289–301.CrossRef
41.
Laes, E., Meskens, G., & van der Sluijs, J. P. (2011). On the contribution of external cost calculations to energy system governance: The case of a potential large-scale nuclear accident. Energy Policy, 39, 5664–5673.CrossRef
42.
van der Sluijs, J., Craye, M., Futowicz, S., Kloprogge, P., Ravetz, J., & Risbey, J. (2005). Combining quantitative and qualitative measures of uncertainty in model-based environmental assessment. Risk Analysis, 25(2), 481–492.CrossRef
43.
van der Sluijs, J., Craye, M., Funtowicz, S., Kloprogge, P., Ravetz, J., & Risbey, J. (2005). Experiences with the NUSAP system for multidimensional uncertainty assessment in model based foresight studies. Water Science and Technology, 52(6), 133–144.CrossRef
44.
Taleb, N. N. (2007). The Black Swan: The impact of the highly improbable. London: Penguin.
45.
Aven, T. (2015). Implications of black swans to the foundations and practice of risk assessment and management. Reliability Engineering & System Safety, 134, 83–91 (Open access).
46.
47.
48.
Borgonovo, E., & Plischke, E. (2015). Sensitivity analysis: A review of recent advances. European Journal of Operational Research, 248, 869–887.MathSciNetCrossRef
49.
O’Hagan, A., & Oakley, J. E. (2004). Probability is perfect, but we can’t elicit it perfectly. Reliability Engineering and System Safety, 85, 239–248.CrossRef
50.
Flage, R., Aven, T., Baraldi, P., & Zio, E. (2014). Concerns, challenges and directions of development for the issue of representing uncertainty in risk assessment. Risk Analysis, 34(7), 1196–1207.CrossRef
51.
Aven, T. (2011b). On the interpretations of alternative uncertainty representations in a reliability and risk analysis context. Reliability Engineering and System Safety, 96, 353–360.CrossRef
52.
53.
54.
Metadata
Title
The Neglected Pillar of Science: Risk and Uncertainty Analysis
Author
Terje Aven
Copyright Year
2021
Book
Handbook of Advanced Performability Engineering

Print ISBN: 978-3-030-55731-7

Electronic ISBN: 978-3-030-55732-4

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-55732-4_28