Concerns,Challenges, and Directions of Development for the Issue of Representing Uncertainty in Risk Assessment

In the analysis of the risk associated to rare events that may lead to catastrophic consequences with large uncertainty, it is questionable that the knowledge and information available for the analysis can be reflected properly by probabilities. Approaches other than purely probabilistic have been suggested, for example, using interval probabilities, possibilistic measures, or qualitative methods. In this article, we look into the problem and identify a number of issues that are foundational for its treatment. The foundational issues addressed reflect on the position that “probability is perfect” and take into open consideration the need for an extended framework for risk assessment that reflects the separation that practically exists between analyst and decisionmaker.     

Foundational Challenges for Advancing the Field and Discipline of Risk Analysis

Risk analysis as a field and discipline is about concepts, principles, approaches, methods, and models for understanding, assessing, communicating, managing, and governing risk. The foundation of this field and discipline has been subject to continuous discussion since its origin some 40 years ago with the establishment of the Society for Risk Analysis and the Risk Analysis journal. This article provides a perspective on critical foundational challenges that this field and discipline faces today, for risk analysis to develop and have societal impact. Topics discussed include fundamental questions important for defining the risk field, discipline, and science; the multidisciplinary and interdisciplinary features of risk analysis; the interactions and dependencies with other sciences; terminology and fundamental principles; and current developments and trends, such as the use of artificial intelligence.     

On Funtowicz and Ravetz's “Decision Stake—System Uncertainties” Structure and Recently Developed Risk Perspectives

The Funtowicz and Ravetz model for classifying problem‐solving strategies into applied sciences, professional consultancy, and postnormal sciences is well known in the social science risk literature. The model is illustrated in a diagram based on the two axes: (i) decision stakes—the value dimension (costs, benefits) and (ii) the system uncertainties—the knowledge dimension. These axes resemble the same two dimensions that characterize some recently developed risk perspectives: (a) consequences and the severity of these consequences and (b) associated uncertainties. In this article, we make a detailed comparison of these two types of risk frameworks. We point to similarities and differences in motivation and use. A main conclusion of the article is that these risk perspectives all provide adequate scientific bases for the Funtowicz and Ravetz model. New insights are provided on the understanding of what the outcome stakes/consequences and uncertainty dimensions really capture in these perspectives and frameworks.     

On the Meaning and Use of the Risk Appetite Concept

The risk appetite concept has been given considerable attention recently in enterprise risk management contexts. A number of definitions exist, most with a link to risk acceptability, but also values and goals. The usefulness of the concept is, however, disputed; some authors argue that we can in fact do better without it. In this article, we provide a thorough discussion of what the risk appetite concept is actually trying to express and how it best can be used in the relevant decision making. The main purposes of the article are (i) to argue that the risk appetite concept, suitably interpreted, has a role to play in risk management, (ii) to show that the risk appetite concept is well supported by some types of risk perspectives and not by others, and (iii) to show how the risk appetite concept is linked to other related concepts, such as risk seeking and risk acceptability. The risk perspectives studied range from expected value and probability based definitions of risk to views on risk, that are founded on uncertainties.     

Social Competence and Antisocial Behavior: Continuity and Distinctiveness Across Early Adolescence

The degree of continuity and distinctiveness in social competence and antisocial behavior was examined in a longitudinal structural equation model. Participants were 391 typically developing Norwegian middle school students (51% boys), their parents, and teachers and were assessed when they were approximately 13 years of age (a school cohort in 8th grade) and again 17 months later, when they were about 15 years old (in 10th grade). Social competence showed considerable stability across middle school, more than did antisocial behavior. Low social competence at age 13 predicted antisocial behavior at age 15, over and above the variance explained by the earlier assessment of antisocial behavior. While social competence and antisocial behavior both showed a relatively strong negative association concurrently and demonstrated considerable overlap, results suggested that the two constructs should be considered separate dimensions. Findings are presented within a transactional framework and implications for prevention efforts and directions for future research are discussed.     

Expressing Economic Risk—Review and Presentation of a Unifying Approach

Risk related to economic values is treated by many disciplines, including safety and production engineering, business, and project management. Within each of these and across these disciplines different nomenclature and principles are adopted for describing and communicating risk. The situation is rather confusing. In this article, we review various approaches and concepts that are used to express risk. We present and discuss a unifying approach for dealing with economic risk, with uncertainty being the key risk concept. The approach represents a rethinking on how to implement the Bayesian paradigm in practice to support decision making.     

Foundational Issues in Risk Assessment and Risk Management

In spite of the maturity reached by many of the methods used in risk assessment and risk management, broad consensus has not been established on fundamental concepts and principles. The risk fields still suffer from a lack of clarity on many key scientific pillars. The purpose of this article is to point to this situation and through some illustrating examples discuss the challenges that the fields here face. Moreover, the purpose of the article is to reflect on how to improve the present situation and enhance the risk fields. We argue that the establishment of some common scientific pillars as well as a strong and continuous research focus on foundational issues are critical success factors. The article specifically addresses the role of the peer‐reviewed journals and the international standards in the fields. We hope that the article can contribute to a revitalization of the discussion of foundational issues in risk assessment and risk management.     

The Role of Quantitative Risk Assessments for Characterizing Risk and Uncertainty and Delineating Appropriate Risk Management Options, with Special Emphasis on Terrorism Risk

The purpose of this article is to discuss the role of quantitative risk assessments for characterizing risk and uncertainty and delineating appropriate risk management options. Our main concern is situations (risk problems) with large potential consequences, large uncertainties, and/or ambiguities (related to the relevance, meaning, and implications of the decision basis; or related to the values to be protected and the priorities to be made), in particular terrorism risk. We look into the scientific basis of the quantitative risk assessments and the boundaries of the assessments in such a context. Based on a risk perspective that defines risk as uncertainty about and severity of the consequences (or outcomes) of an activity with respect to something that humans value we advocate a broad risk assessment approach characterizing uncertainties beyond probabilities and expected values. Key features of this approach are qualitative uncertainty assessment and scenario building instruments.