Society For Risk Analysis Annual Meeting 2013

Session Schedule & Abstracts


* Disclaimer: All presentations represent the views of the authors, and not the organizations that support their research. Please apply the standard disclaimer that any opinions, findings, and conclusions or recommendations in abstracts, posters, and presentations at the meeting are those of the authors and do not necessarily reflect the views of any other organization or agency. Meeting attendees and authors should be aware that this disclaimer is intended to apply to all abstracts contained in this document. Authors who wish to emphasize this disclaimer should do so in their presentation or poster. In an effort to make the abstracts as concise as possible and easy for meeting participants to read, the abstracts have been formatted such that they exclude references to papers, affiliations, and/or funding sources. Authors who wish to provide attendees with this information should do so in their presentation or poster.

Common abbreviations

M3-C
Symposium: Foundational Issues in Risk Analysis, Part I

Room: Key Ballroom 3   1:30 PM - 3:00 PM

Chair(s): Terje Aven, Tony Cox   terje.aven@uis.no

Sponsored by DASG



M3-C.1  13:30  Foundational issues in risk assessment and management. Aven T*, Zio E; University of Stavanger, Norway   terje.aven@uis.no

Abstract: The risk assessment and risk management fields still suffer from a lack of clarity on many key issues. Lack of consensus on even basic terminology and principles, lack of proper support and justification of many definitions and perspectives adopted lead to an unacceptable situation for operatively managing risk with confidence and success. In this talk we discuss the needs, obstacles and challenges for the establishment of a strong foundation for risk assessment and risk management. We i) review and discuss the present situation and ii) reflect on how to best proceed in the future, to develop the risk discipline in the directions needed.

M3-C.2  13:50  Adapting Risk Management to Reduce Regret. Cox T*; Cox Associates and University of Colorado   tcoxdenver@aol.com

Abstract: Two principles for choosing among alternative risk management policies are: (a) Seek to maximize ex ante expected social utility (roughly equivalent to expected net benefit); and (b) Seek to minimize ex post regret, defined as the difference between the maximum value (or net benefit) that could have been achieved, as assessed in hindsight, and the value that actually was achieved. We show that these two principles typically lead to different recommended choices, for both individuals and groups, especially when there are uncertainties or disagreements about probabilities or preferences. Under these realistic conditions of conflict and uncertainty, effective policy-making requires learning to make choices that adaptively reduce or minimize regret. Risk-cost-benefit and expected utility maximization principles that instead seek to identify the best next action, using realistically imperfect information, are subject to over-fitting and other biases that typically over-estimate the net benefits from costly interventions. We discuss conditions under which policy-making can be improved by switching from trying to maximize expected net benefits to trying to minimize ex post regret. This change helps to resolve some long-standing difficulties in risk-cost-benefit analysis, such as how to avoid over- or under-discounting of far future effects and how to decide what to do when future preferences and effects of current actions are highly uncertain.

M3-C.3  14:10  Is Risk Analysis Predictive? Prediction, Validation, and the Purpose(s) of Risk Analysis. Guikema SD*; Johns Hopkins University   sguikema@jhu.edu

Abstract: Risk analysis methods make statements, often probabilistic, about future states of the world. There are many possible purposes behind conducting a risk analysis, including supporting risk management decision making, determining if a system or situation is safe enough, and meeting regulatory or other policy requirements. But is a risk analysis meant to be predictive? Does a risk analysis make predictive statements about future states of the world? If so, why and how? If not, why not? This talk will explore this question and discuss prediction and validation in the context of risk analysis done for different purposes.

M3-C.4  14:30  What Military Strategy can Teach Us about Risk-Management and Uncertainty. Ben-Haim Y*; Technion    yakov@technion.ac.il

Abstract: War entails vast risks and uncertainties. Risk managers can learn valuable lessons from the disputes among military theorists. We discuss a foundational dispute between Clauswitz and Jomini in their attempts to understand Napoleon's overwhelming military success. What was the key to his military invincibility? Clauswitz felt that it is futile to seek governing rules or patterns or laws of successful military strategy. The dominant factors in war, according to Clauswitz, are uncertainty and friction (by which he meant the inherent resistance of reality to the will of men at war). Jomini disagreed. He felt that, while war is not a science like the study of nature, it nonetheless has patterns and rules that can be discovered. He felt that he uncovered the rules that made Napoleon so successful. In modern language we would say that Jomini identified successful methods of operational art: rules for the manipulation of large field units. The main claim of this talk is that the analysis, and even more so the management, of risk, must be approached in the tradition of Clauswitz far more than of Jomini. It is the uniqueness and uncertainty of risk situations that present the special challenges that risk analysts and mangers must face. Once a risk becomes well known and thoroughly understood it is no longer a risk, and it is managed by a routine. Risks are "risky" precisely because of the endless possibility for surprise. Sound science, careful measurement, accurate monitoring and reporting, are all crucial. Nonetheless, a successful risk professional is able to analyze and manage uncertainty, variability and surprise (info-gap theory is one tool). This is very Clauswitzian and not Jominian at all.



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