Final Program - Society for Risk Analysis

W1-C.3 Belzer RB; belzer@regulatorycheckbook.orgRegulatory CheckbookFINALLY, A SCIENTIFIC DEFINITION OF ADVERSE EFFECTThe scientific assessment of human health risk has been predicated on the existenceof a scientific definition for adverse effects. Yet, ever since Arnold Lehmanintroduced the dawn of health risk assessment in 1949, and proceeding through thousandsof scholarly articles, hundreds of scholarly books, scores of National ResearchCouncil reports, dozens of Federal and State agency guidance documents, myriadlaws and regulations, and the creation in 1980 of the Society for Risk Analysis, adverseeffect still lacks a scientific definition. Channeling their inner Justice Potter Steward,theoreticians and practitioners alike profess to know an adverse effect when they seeone. This is surely true, at least for effects so bad that even an economist could recognizethem. But it is not true at the margin, where fine distinctions separate adversefrom nonadverse effects and the risk management consequence of assignment aremost meaningful. This paper reviews the domain of conventional definitions of adverseeffect, adding to them several refinements that have been recently proposed byvarious individuals and groups. It is shown that none are genuinely scientific. Someare measurable but not refutable, and all are dependent on the policy judgment of therisk assessor. Most conventional methods are further compromised because they imposethe strong assumption of monotonicity in dose-response, and thus they cannotreconcile the possibility that an effect may be adverse at some doses but beneficial atothers. Finally, none can address the case where, at any given dose, effects may be adversefor some persons but beneficial for others, or even adverse or beneficial for thesame person at the same time. An alternative definition is proposed that is measurableand refutable, and unlike every competing definition, it is independent of the discretionand policy judgment of the risk assessor. Thus, unlike conventional definitionsand their progeny it is scientific in every respect.W2-F.1 Ben-Haim Y; yakov@technion.ac.ilTechnion - Israel Institute of TechnologyOPTIMIZING AND SATISFICING IN THE MANAGEMENT OF RISKWe admire excellence in all areas of endeavor: art, sport, science, business, andrisk management. The fastest runner wins the race and our admiration. The lowestriskdesign - all else being equal - is preferred. `Better`, almost by definition, is `moredesirable` and - by the logic of preference - the best is most preferred. The logic ofpreference is so compelling that there is a moral imperative to do our best. Optimizationalso has deep roots in the physical and natural realms. The laws of physics canbe derived from optimization principles. Biological evolution is a process of selectionof the better over the less good leading - all else being stable - to optimal morphologies.Mathematical economics was quick to adopt the imperative of optimization,which underlies modern theories of economic dynamics. Decision makers oftenface severe uncertainties. Is optimization a good strategy under uncertainty? Uncertaintyhas profound implications for any attempt to optimize the outcome of decisions.We first discuss the equity premium paradox from financial economics whichbelies the cardinality of performance-optimization by economic agents. We contrastperformance-optimization with a strategy of robustly achieving critical goals. Wethen apply this concept to technological risk analysis, and consider a schematic designof a critical but risky infra-structure. Finally, we discuss the importance of disasterrecovery as an integral part of risk management.M2-H.4 Bennett SP, Cheesebrough AJ, Waters J; bennett.steve@gmail.comUS Department of Homeland Security, Office of Risk Management and Analysis“INTELLIGENT” INTEGRATION OF INTELLIGENT ADVERSARYMODELING INTO HOMELAND SECURITY RISK ANALYSES: THEO-RY AND PRACTICEAs a risk management organization, the U.S. Department of Homeland Security(DHS) is charged with producing relevant and technically defensible risk assessmentsof a wide range of potential adverse events within its mission domain in orderto inform and support decision making. Many of these potential adverse events, suchas pandemics and many forms of natural disasters (as well as drug smuggling and illegalimmigration to a degree) are 1) stochastic in nature, and 2) replete with historicalfrequency and consequence data making analysis of event risks relatively straightforward.However, many events that are intentionally initiated, such as terrorism, are neitherstochastic in nature, nor frequent enough (thankfully) to yield statistically usefulfrequency data. Currently referred to as the “intelligent adversary” problem, the abilityto estimate reasonable and defensible frequencies (or at least relative probabilities)for terrorism events is an important research focus of the Department’s risk analysiscommunity. Current DHS “solutions” to this problem have tended to assume thatprobability elicitations of relevant experts capture the equilibrium position of eventprobabilities, incorporating the adaptation, deterrence, and threat-shifting tendenciesof different adversary groups. However, there has been no lack of proposed alternativesolutions from as evidenced from the pages of Risk Analysis and other topjournals over the past two years. These alternatives have ranged from game theoreticand agent-based methods to recommendations that DHS not attempt to characterizethese likelihoods at all. This presentation will discuss a number of these proposedalternatives from both theoretical and practical perspectives and present a frameworkfor evaluating and incorporating intelligent adversary models for estimating terrorismfrequencies/probabilities into existing Department risk analysis frameworks.61