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Understanding Risk: Informing Decisions in a Democratic Society (1996)

Chapter: 2 JUDGMENT IN THE RISK DECISION PROCESS

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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Page 45
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Page 46
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Page 47
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Page 48
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Page 50
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Page 54
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Page 55
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
×
Page 65
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
×
Page 66
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
×
Page 67
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
×
Page 68
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
×
Page 69
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
×
Page 70
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
×
Page 71
Suggested Citation:"2 JUDGMENT IN THE RISK DECISION PROCESS." National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. Washington, DC: The National Academies Press. doi: 10.17226/5138.
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Page 72

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2 Judgment in the Risk Decision Process A risk characterization is part of a process that begins with the formulation of a problem the likelihood of a harm-and ends with a decision. A risk characterization cannot make up for deficiencies in other parts of the process; inversely, if the other parts of the process are done well, it is far more likely that the risk characterization will be both clear and useful. Some of the analytical difficulties affecting risk characterization are well known, such as the difficulty of determining an appropriate math- ematical model for extrapolating from animal toxicological data to assess the health consequences of human exposures and of comparing best esti- mates of different risks when their uncertainty distributions differ in shape or in variability (see, e.g., Finkel, 1990; National Research Council, 1994a). In this chapter we focus on other difficulties, often overlooked in the extensive literature on risk analysis, that are equally important for understanding and coping with risk. Many of these difficulties result from judgments made at each step of the process that can undermine the quality of risk characterization and, if they are unacceptable to some of the interested and affected parties, become lightning rods for conflict. Such difficulties tend to arise when the knowledge and perspectives of these parties were not adequately incorporated into the process that led to the judgments. Many of the difficulties can be prevented or reduced if the process is recognized from the start to require both analysis and delibera- tion and if it is organized to ensure that the judgments are informed by appropriate deliberations. 37

38 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOC~TIC SOCIETY We consider in detail the steps of problem formulation, selecting op- tions and outcomes to consider, and information gathering, as well as synthesis, usually the major focus of risk characterization. We discuss process design at the end of the chapter. We document the variety of judgments made during each of these steps and some of the ways these judgments can undermine understanding of risks and contribute to mis- trust and public conflict about risk decisions. The chapter concludes with a strategy for avoiding these outcomes by designing the analytic-delib- erative Process so as to inform the kev judgments with the knowledge 1 J J (I and perspectives of the range of decision participants. Certainly, many risk characterizations and risk decision processes have been appropriate for the decision at hand. However, as we note in Chapter 1, some high-profile, controversial risk characterizations have suffered from deficiencies, and sometimes the damage to decision mak- ing has been significant. The deficiencies also threaten some lower-pro- file risk characterizations. PROBLEM FORMULATION Perhaps the most basic difficulty with risk characterization is that the people who will or should participate in the risk decision process fre- quently have divergent perspectives on the decision at hand. Differences of perspective cause problems because efforts to inform decisions neces- sarily proceed from some implicit formulation of the problem: a risk characterization that deals selectively with only one perspective on a prob- lem will be inadequate for those with significantly different perspectives. The Concept of Risk ~. ~. ~ Judgments pervade any understanding of risk (National Research Council, 1994a). Some writers even question the idea that risk should be conceptualized as a quantifiable physical reality (e.g., Douglas and Wildavsky, 1982; Funtowicz and Ravetz, 1992; Krimsky and Golding, 1992; Otway, 1992; Pidgeon et al., 1992; Slovic, 1992; Watson, 1981; Wynne, 1992~. They argue that the concept of risk helps people interpret and cope with the dangers and uncertainties of life, including but not limited to the prospect of physical harm, and that the concept is shaped by human minds and cultures. That is, there are many different kinds and qualities of dangers and many potentially useful ways of making sense of them, and even though many of these are measurable in prin- ciple, it is judgments and values that determine which ones are defined in terms of risk and actually subjected to measurement. The multidimensionality of risk and the many ways it can be viewed

JUDGMENT IN THE RISK DECISION PROCESS 39 help explain why risk characterizations sometimes lack authority for some of the interested and affected parties to a decision, even when the charac- terizations are supported by high-quality analysis. Individuals and groups that do not share the judgments and assumptions about the prob- lem formulation that underlie a risk characterization may well see the information it provides as invalid, illegitimate, or not pertinent. They may see the characterization as flawed because the underlying risk analy- sis is based on controversial assumptions (often implicit) about which perspectives are legitimate, which solutions are reasonable, and which types of information are useful or relevant (Vaughan and Seifert, 1992~. The history of risk analysis is filled with instances in which analysis, at least to some of the parties, seemed to beg the question. One such case is the risk analysis for the Yucca Mountain nuclear waste repository site, mentioned in Chapter 1. Billions of dollars were spent on assessing the quantitative and calculable risks associated with permanent disposal at one site, when many people believe it would have been more productive to assess the risks of temporary storage while engaging in a more thor- ough debate on the merits of a permanent solution. Another example was the comparison of coal and nuclear power generation in the 1970s that did not consider slowing the growth of energy demand as one approach to finding sufficient electric generating capacity to meet national needs. Even the apparently straightforward act of defining the hazardous pollutant to be characterized can embed important assumptions about the nature of the problem. Should one consider narrow classes of compounds such as dioxins, or broad classes such as the thousands of organochlorines and assess chlorine as the relevant environmental risk? Such choices, though they should be well informed by toxicology and other relevant science, involve important acts of judgment that shape risk characteriza- tion and even decision making (Fischhoff et al., 1981; O'Brien, 1995~. In the chlorine example, the definition of the hazard is highly consequential for the chemical industry and for proponents of pollution prevention; a risk characterization based solely on either formulation might be unsatis- factory to one of the interested and affected parties. Missing Considerations Three considerations that are often missing from the formulation of risk problems have led to disputes about the subsequent risk character- izations: fairness, prevention (of pollution or risk), and rights. Acknowl- edging these concerns may lead to different (usually broader) problem formulations than those that emerge from the ordinary routines of gov- ernment agencies. The way such concerns are or are not addressed can

40 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMO C~TIC SOCIE~ directly affect choices about the options and outcomes to consider in char- acterizing risk. F. alrness For some interested and affected parties in risk decisions, managing environmental risks has become a question of fairness, moral responsibil- ity, and distributional equity (Beach, 1990; Bullard and Wright, 1992; Law- less, 1977; Nelkin, 1989; Sandman, Weinstein, and Klotz, 1987; Vaughan and Seifert, 1992~. An example from Chester, Pennsylvania, shows how fairness issues can arise in risk characterization. Chester is an industrial city with a declining population (now about 40,000) consisting largely of low-income African Americans. It has become the site of numerous haz- ardous facilities, including two oil refineries, a trash incinerator, some Superfund sites, and an autoclave facility for infectious materials. When a proposal arose to site a soil decontamination plant in Chester, the Penn- sylvania Environmental Protection Agency proposed to do a risk assess- ment of the plant project, examining its likely emissions and projecting the incremental health risks to the local population on the basis of models of exposures and dose-response relationships. But community represen- tatives raised several other issues, one of which was the claim that adding a new hazardous facility was unfair in a city where residents were al- ready bearing more than their share of toxic exposures. The city's questions led the regional office of the U.S. Environmental Protection Agency (EPA) to agree to conduct an analysis based on a dif- ferent problem formulation: a cumulative risk assessment that would characterize pollution in Chester generally and identify the areas of high- est risks. Such a risk analysis would focus serious scientific attention on matters that are not considered in an incremental-risk analysis, including the interactive effects of the hazards present in the city, the health effects of the new hazard on a population whose health status may be compro- mised by other exposures, and the comparison of overall pollution risks in the exposed population with those in more affluent communities nearby. These issues would not have been addressed in the original state- proposed analysis. The city's position was that any risk characterization that ignored these issues would be incomplete and inadequate in terms of providing the information needed to make a major decision about public health (personal communication, Gregory Schirm, 1994~. Some fairness concerns, described in terms of "environmental jus- tice" for minority and low-income populations, were given prominence by Presidential Executive Order 12898, issued in February 1994. The Executive Order recognized that federal agencies' risk analyses had not previously made equity issues a routine part of the problem definition

JUDGMENT IN THE RISK DECISION PROCESS 41 and directed them to do so. Effective implementation of the order would make the analysis of some aspects of fairness and equity an essential input into risk characterization. Prevention Current debates about preventing pollution and risk also show clearly how problem formulation shapes risk characterization and the entire risk decision process. One proponent of pollution prevention has criticized standard practice in risk analysis for asking the question, "Which envi- ronmental problems can we ignore?" (because their risks are negligible), rather than the question, "How can we avoid exposures to hazards?" (O'Brien, 1995~. While both formulations omit the key question of cost, the latter question invites consideration of a much wider range of possible policy options (especially, pollution prevention). For many interested and affected parties, a risk characterization that does not address preven- tion could never provide the information they need to accept a risk deci- sion, no matter how well the narrower problem is analyzed or character- ized. The controversy over control of the Mediterranean fruit fly, a major pest to the $2 billion fruit and vegetable industry in California, illustrates, among other things, how judgments about which aspects of risk to char- acterize can obscure or highlight debates over pollution prevention. Much of the Medfly debate and the associated risk analysis and characterization in the early 1990s focused on estimates of risks to the health of residents who might be exposed to the malathion spray. The debate centered on dose-response questions and on the appropriateness of assumptions about the behavior and therefore the exposure of residents who are warned to stay indoors during an imminent spraying but who might not do so. It is based on the formulation that the Medfly problem in California comes from flies that have recently entered the state on infested fruit and that spraying where flies have been seen will eradicate the problem (Califor- nia Department of Food and Agriculture, 1994~. Some critics argue that this formulation is incorrect because the flies are now established as breeding populations in California and cannot be eradicated by a spraying program (Carey, 1991; 1994~. They argue further that the state has a vested interest in the isolated infestation assumption because under it spraying might easily and cheaply convince potential importers of California produce that it is fly free. If, however, the Medfly is an established pest, malathion will not perform as claimed, and biologi- cal pest control would become an alternative option worth considering. Biological control would also avoid the projected human exposures to malathion spray. The formulation of the problem as one of keeping an

42 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMO CRITIC SOCIETY established pest population under control changes the questions for risk analysis: the focus shifts to the risks of biological control approaches and the comparative effectiveness of chemical and biological Medfly control; it makes pollution prevention, in the form of nonchemical means of pest control, a key policy option. If the Medfly problem has been incorrectly formulated, much of the risk analysis and characterization has focused on an incomplete set of options, and the needs of decision participants for understanding have been poorly served. Rights Risk characterizations have also become controversial when they pay little attention to issues of the rights of individuals or groups to control their own lives. An example is the continuing debate about the fluorida- tion of public water supplies. Advocates declare that this technique is a safe and cost-effective method of improving people's dental health. Op- ponents in addition to questioning the certainty of the scientific esti- mates and raising the issues of increased risk of bone fractures in the elderly and fluoridosis in those with poor kidney function speak about individual rights and the undesirability of a public health policy that eliminates individual choice in regard to exposure to a chemical agent that has both benefits and risks (Lawless, 1977; Martin, 1989~. Another example is the contentious debate about environmental "un- funded mandates,', federal decisions that require states and localities to spend their money on certain environmental and health projects, which consequently reduces funds available for other projects. Many interested and affected parties claim that they have rights to clean air and water and that the federal government should protect these rights. Other parties, chiefly state and local officials, complain that federal decisions that com- pel their action, even if based on sound risk analyses, abrogate the right of localities to use their funds to reduce risks in the most cost-effective ways. While federal officials may have sponsored risk analyses to focus on re- ducing the risks of environmental chemicals, a state public health depart- ment or a mayor faces a different problem: a choice between reducing risks to citizens from chemical residues in water or from birth defects, traffic accidents, or violent crime. A risk characterization for water pollu- tion alone may be quite beside the point for a local official confronting such a choice. SELECTION OF OPTIONS AND OUTCOMES Problem formulation has practical implications for other steps in the risk decision process. Among the most important is the way it shapes

JUDGMENT IN THE RISK DECISION PROCESS 43 choices about which options to consider and which possible adverse out- comes to analyze- choices that are critical to the success of risk character- ization.1 For a risk characterization to meet the needs of participants in a decision, it must consider the range of plausible decision options. The parties to a decision may not agree on which options are worth consider- ing, but a risk characterization that does not consider an option that one of the participants views as promising is likely to be seen as biased and inadequate. The controversies over the Medfly and unfunded mandates are examples. When problem definitions truncate the list of options too severely, risk characterizations can be doomed to controversy long before they are undertaken. Organizations responsible for risk characterizations should make ef- forts to identify the range of decision options that experts and the spec- trum of interested and affected parties consider viable. Generating an adequate list of options may be difficult. It demands familiarity with the context of the decision, knowledge about the scientific and technical as- pects of the possible risks, and, sometimes, creativity and imagination. Also, it often demands that organizations listen to the interested and affected parties. Although identifying the range of options is challenging, it is a key to successful risk characterization. Considering a sufficiently broad range of possible harms or losses is equally important to risk characterization. Typically, analysis focuses on only a few adverse outcomes such as cancer or birth defects in human beings, loss of a species, or elimination of a habitat that are judged to be the most serious of the possible harms. The analysis is sometimes further restricted to the effects of exposure to a particular agent (a substance or process), through a particular medium (e.g., air, water, or food intake). Agencies may narrow the list of outcomes because they have narrow responsibilities under law, because funds for analysis are limited, because of political pressures, or for other reasons. Consideration of only a few possible outcomes is usually justified on the assumption that if a decision protects adequately against the selected outcomes, it will also protect against the others, because environmental and health hazards are strongly correlated. This assumption becomes increasingly suspect as the range of outcomes of concern expands from overt human health risks to effects on the immune system and related systems (e.g., allergenicity); behavioral effects; psychological effects, such 1Selection of outcomes has sometimes been treated as a stage within problem formula- tion: for example, the U.S. Environmental Protection Agency (1992a:12) refers to outcomes as "ecologically based endpoints". We prefer to make a sharper conceptual distinction between the two tasks.

44 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOC~TIC SOCIETY as anxiety and depression; ecological effects; and social, economic, and ethical impacts. Some participants may doubt that protection against one of these adverse outcomes is tantamount to protection against all. Some of the nonmeasured outcomes may be more salient to some parties, and they may argue that these other adverse outcomes should be subject to analysis and characterization. Demands for such expansion of the out- comes to be included can be especially meritorious when data are sparse on certain outcomes, but the risks have nevertheless been dismissed on the assumption that they are small enough to ignore. An adequate risk characterization must address all the outcomes or consequences of a hazardous situation that are reasonably important to the relevant public officials and to the interested and affected parties to the decision. Agencies should tailor their analyses to the decision to be made, addressing the potential adverse outcomes most significant for that decision. Ecological Effects One important class of nonhealth outcomes is harm to nonhuman organisms and ecosystems. The EPA has taken the lead in developing a conceptual framework for conducting ecological risk assessment (U.S. Environmental Protection Agency, 1992a, 1992b, 1992c, 1992f, 1992g, 1993h) and is preparing guidelines for this activity. Analysis is difficult because the effects may fall on individual animals or plants, on local populations of a certain species, on ecosystems (thus affecting many spe- cies), or on the survival of endangered species. At larger scales, effects on the distribution of ecological communities across the landscape are cen- tral to regional-scale ecosystem management (Grumbine, 1994; Harwell et al., in press). There may be important ecological outcomes to consider and characterize at each of these hierarchical levels of ecological systems (Harwell et al., 1990~. Ecological risk analysis requires an understanding of how the af- fected ecosystem functions. There are numerous interrelationships among taxa, across responses, and across organizational levels. In addition, some of the most important effects may be indirect, operating through several interrelationships. Many of these effects are inadequately understood, difficult to measure, or laden with uncertainty (National Research Coun- cil, 1993a). Some ecologists even dispute whether the concept of ecologi- cal risk (or its inverse, ecological health) is useful for policy analysis (e.g., Lackey, 1994, 1995~. None of these scientific difficulties of estimation, however, negate the importance for policy decisions of considering eco- logical outcomes. Interested and affected parties may want to take ac- count of ecological effects even if the level of scientific understanding of

JUDGMENT IN THE RISK DECISION PROCESS 45 them is poor. Qualitative assessments of relative ecological risks can provide useful insights for environmental decision making (Harwell et al., 19921. A critical need is to develop appropriate tools for assessing the value of ecological systems, including both economic and noneconomic (e.g., intrinsic) values. Economic and Social Effects Economic consequences are sometimes inextricable from the other aspects of a risk. We are not referring here to the well-recognized eco- nomic costs of regulating risks, but to the economic costs of the hazards themselves. Many risk characterizations do not consider the full range of adverse economic outcomes, even though they are important for decision purposes and amenable to scientific analysis. A 1987 example from Brazil is illustrative. When two men seeking scrap metal pried open a metal capsule containing 100 grams of cesium 137, subsequent exposures to neighbors and family resulted in 4 deaths and 50 cases of radioactive contamination that required medical treatment. Described in this sense, the accident appears to have been of local significance, without major national or international impact. But that depiction fails to capture the $20 million dollars in cleanup costs and the subsequent 50 percent drop in the wholesale value of agricultural products from the Brazilian state in which the accident occurred. Sales of manufactured goods were also affected, despite the lack of plausible contamination (Freudenburg,1988~. The incident illustrates that losses in terms of human health may not be the only adverse outcomes of a hazardous situation that are worth charac- terizing. One important class of economic effects are those a given hazard has on nearby property values (Greenberg, 1995; Gregory, Flynn, and Slovic, 1995~. A relationship between changes in property values and proximity to hazardous waste sites has been repeatedly demonstrated (Greenberg and Hughes, 1992, 1993; Schulze et al., 1994; Skaburskis, 1989~. For fami- lies living near hazardous facilities, property value losses are sometimes a significant factor that they want estimated and considered in a decision process. Such information can provide guidance for making decisions about the costs of risk remediation plans (McClelland et al., 1990~. An- other kind of economic effect is the cost of insurance premiums and emer- gency preparedness that flow directly from the possibility of an adverse event (Freudenburg, 1988~. These costs are borne by the potentially af- fected population regardless of whether they actually suffer from the adverse event. Risk characterizations typically do not address social effects, perhaps because they are considered outside the purview of formal risk analysis.

46 UNDERSTANDING RISK: INFORMING DECISIONS INA DEMOC~TIC SOCIETY Yet they are legitimate objects for risk characterization because partici- pants in decisions need to understand them to make informed choices, and many social effects are amenable to systematic analysis. Social effects that may need to be considered in a risk decision include neighborhood disruption and issues of social equity and stigma (Gregory, Flynn, and Slovic, 1995~. Some risk decisions can significantly alter a community's character. Neighbors often express fears that a hazardous facility will be destructive to the community (Zeiss and Atwater, 1991~. It is not uncom- mon to see these kinds of concerns taken seriously in negotiations about citings, but they are not usually treated in conventional risk characteriza- tions. In part, what is at stake is community control (Elliot, 1984; Zeiss and Atwater, 1991~. People are more willing to tolerate a risk if they feel they have some control over the exposure (Slovic, 1987~. By the same token, removing control from a community has social costs, even if the commu- nity accepts a risk. For example, cleaning up a contaminated site near a residential community is a disruptive process. Several studies have docu- mented the tension between residents who want total removal of con- tamination (usually younger families with children) and those who want minimal disturbance and cost (usually older couples living on fixed in- comes who have owned their homes for many years and have no children living at home). The latter group sometimes opposes clean-ups that would disrupt their lives (e.g., remove their gardens, demand temporary evacuation, or involve high costs), while the former group finds the status quo more disruptive (Claus, 1995; Fessenden-Raden et al., 1987; Levine, 1982~. Risk analyses could, but rarely do, explicitly consider the effects of such kinds of neighborhood disruption. If the analyses implicitly set this potential loss equal to zero, affected parties may find the risk character- ization unsatisfactory. Many affected parties in risk decisions expect the government to en- deavor to achieve some fair balance between the risks a community or an individual bears and the benefits received. Recently, this expectation has been voiced as a concern for environmental justice for minority communi- ties (Bullard and Wright, 1992; Greenberg, 1993~. There is evidence of unequal distribution of noxious facilities between communities as a func- tion of economic and racial or ethnic differences (Bullard, 1990; Commis- sion for Racial Justice, 1987; U.S. Environmental Protection Agency, 1992h) and of differential harm associated with these risk sources (Greenberg, 1995~. However, equity concerns had rarely been considered in conven- tional risk assessments until Executive Order 12898, in 1994. To the extent that this directive is implemented, agency risk characterizations will be

JUDGMENT IN THE RISK DECISION PROCESS 47 gin to provide information that will inform public deliberation on equity issues.4 People sometimes hold negative associations for things, places, orga- nizations, or people they connect to risks (Slovic, 1993b). Such stigma can have a tangible economic impact: in 1989, concerns about the use of Alar on apples led to nationwide decline in apple sales of over $100 million (about 10%) after risk assessments were publicized that linked the sub- stance to cancer in children (Rosen 1990~. Researchers have also identi- fied the potential economic effects from stigma associated with the pro- posal to construct a high-level radioactive waste facility in Yucca Mountain, Nevada (Slovic, Layman, et al., 1991~. For many siting deci- sions, the effects of stigma cannot be reduced by engineering and design alone, but it may be possible to address them through compensation or insurance (Fort, Rosenman, and Budd, 1993~. Although these effects or potential losses from stigma are difficult to quantify or compensate (Gregory, Flynn, and Slovic, 1995), they are nevertheless important to consider. Effects on Future Generations Many risk decisions may impose risks on future generations that re- quire a different kind of consideration from risks to people living today. The high-level nuclear waste disposal facility planned for Yucca Moun- tain, Nevada, is a striking example: releases of radioactive material from this facility could cause harm thousands of years in the future. Such situations present two questions for risk analysis: How can one be certain that the risks to future generations are known? How can one represent the interests of future generations in a current risk decision process? The difficulty of the first question is illustrated well by the Yucca Mountain controversy. As described in Chapter 1, a fundamental as- sumption of U.S. and international policy on radioactive waste disposal has been that safe, permanent disposal was the strategy most likely to reduce the risks to future generations. But a 1993 technical review com- mittee set up by the state of Nevada one of the interested and affected parties questioned even that most basic assumption. Arguing that no one today can predict what human beings might be able, or motivated, to do at the Yucca Mountain site over the next 10,000 years, the Technical Review Committee (1993:14) concluded that rather than protecting future 2Various formal analytical techniques exist for informing discussions about distributional equity: all involve controversial techniques for valuing human lives (e.g., Zeckhauser, 1975; Anderson, 1988; Leigh, 1989; Ellis, 1993).

48 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMO CRITIC SOCIE~ generations, entombment leaves thein in charge of dangerous waste, while "making it as difficult as the state of our technology permits" for them to do anything about it if future knowledge or social conditions require such action. That report suggests, among other things, that people today can- not assess the risks to future generations without carefully considering possible social changes as well as the operation of physical and biological processes over the long term. The second question (the interests of future generations) is sometimes addressed by using economic techniques of time discounting (see, e.g., Viscusi and Moore, 1989; Cropper, Aydede, and Portney, 1994~. How- ever, this practice reduces the significance of risks that lie more than a generation or two in the future almost to zero. This technique is unac- ceptable to many people. Another way to address the interests of future generations is to bypass explicit analysis on the assumption that living persons can act as proxies for future generations. But this strategy is also vulnerable to criticism because it assumes that people in the future would support decisions made by people today and accept the processes by which those decisions were reached (see Shrader-Frechette, 1993b). Al- though intergenerational equity is difficult to resolve by formal or quan- titative analysis, it nevertheless raises important issues for risk character . . zahon. Ripple Effects Some hazards have "ripple effects" (Slovic, 1987) effects that extend far beyond their direct harms and that can impose very large costs. Com- panies in an industry may be affected by a mishap, regardless of whether they caused it; even industries unrelated to the mishap may be affected. The case of the radioactive materials accident in Brazil, described above, is an example. Another is the 1979 nuclear power accident at Three Mile Island, Pennsylvania, which killed no one, but had extensive ripple ef- fects. It devastated the utility that operated the plant; resulted in greatly increased costs for regulating, constructing and operating nuclear power plants; and led to "reduced operation of reactors worldwide, greater pub- lic opposition to nuclear power, and reliance on more expensive energy sources" (Slovic, 1987:201; see also Evans and Hope, 1984; Heising and George, 19861. Researchers are working to understand the mechanisms that produce these ripple effects, which Kasperson and his colleagues (Kasperson et al., 1988; Kasperson, Golding, and Tuler, 1992) call the "social amplification of risk" (see also Mazur, 1981, 1984; Kunreuther and Linnerooth, 1982; Slovic, Lichtenstein, and Fischhoff, 1984~.

JUDGMENT IN THE RISK DECISION PROCESS Effects on Democracy, Governance, and Ethical Beliefs 49 Some of the actions that may be taken in response to risks can have widespread reverberations throughout society. An example that relates to governance is the federal imposition of unfunded mandates for envi- ronmental protection on state and local governments, noted above. Th affected governments complain that federal risk decisions decrease their power and that of their constituents to control their lives, and they want this risk considered before policy decisions are made. Another example, noted in Chapter 1, is the possibility that risk decisions and the way they are made may undermine public trust in the organizations making the decisions. This effect may not only make it more difficult to implement a decision, but may lead some individuals to distrust all information pro- vided by an organization, withdraw from the decision, or express frustra- tion in destructive ways. The legitimacy of government may, in this sense, be one of the things at risk, although this risk is rarely characterized formally. Decisions about risks may also violate deeply held values or ethical beliefs of affected parties. For example, during the early years of the cold war, decisions were made by the U.S. Department of Defense and the Atomic Energy Commission (a predecessor of the U.S. Department of Energy) to conduct radiation experiments without the informed consent of those exposed in some of the experiments, on the grounds of national security. When these decisions became public, there was widespread outrage. In other cases, policies may threaten what some people see as the intrinsic value of natural phenomena, such as the survival of species and the maintenance of ecosystems, and violate their belief that humanity has no right to interfere with these natural phenomena. The possibility that a risk decision will violate such ideas of what is morally right is rarely given explicit attention in risk characterization. Conclusion We do not suggest that all conceivable options for action or possible adverse outcomes can or should be the subject of detailed analysis in every risk decision process. In most instances, such detailed analyses would be unnecessary, not to mention the demands they would put on analysts and on scarce resources. We recognize that government agencies and other organizations must make decisions and that some of these will inevitably be opposed by some of the interested and affected parties. We emphasize, however, that the options and outcomes that risk analysts and managers traditionally choose for analysis may not be the only ones that are necessary to analyze and characterize for the decision at hand. These

50 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOC~TIC SOCIETY choices deserve careful and explicit consideration before analysis begins. (We discuss strategies for making such choices in Chapter 6.) INFORMATION GATHERING AND INTERPRETATION After the risk problem, the options for action, and the important out- comes have been defined, analysts, together with public officials and in- terested and affected parties, gather and interpret information. This task, like the others, involves judgments that can create problems in risk char- acterization. This section discusses two key types of judgments that color information gathering and interpretation and can affect the success of a risk characterization: choosing a risk measure and making simplifying assumptions. Choosing a Risk Measure Even the apparently simple task of choosing a risk measure for a well- defined outcome such as human fatalities can be surprisingly complex and judgmental. The list below shows a few of the many different ways that risks of death have been measured: deaths per million people in the population deaths per million people within x miles of the source of exposure deaths per unit of concentration deaths per facility deaths per ton of toxic substance released deaths per ton of toxic substance absorbed by people deaths per ton of chemical produced deaths per million dollars of product produced loss of life expectancy associated with exposure to the hazard The choice of a measure can make a big difference in a risk analysis, especially when one risk is compared with another. It can also make a big difference in whether interested and affected parties see the analysis as legitimate and informative. An example from coal mining demonstrates how the choice of one measure or another can make a technology look either more or less risky (Crouch and Wilson, 1982~. Between 1950 and 1970 coal mines became much less risky in terms of deaths from accidents per ton of coal, but they became marginally riskier in terms of deaths from accidents per employee: see Figures 2-1 and 2-2. Which measure one thinks more useful for in- forming decisions depends on one's point of view (Crouch and Wilson, 1982:12-13~:

JUDGMENT IN THE RISK DECISION PROCESS 1.5 - o c' o In Q S Id a) ~ 1.5 a) ~5 C) Cat it: 1.0- - O- _ 1950 1955 1960 Year 1 1 1 1965 1970 51 FIGURE 2-1. Accidental deaths per million tons of coal mined in the United States, 1950-1970. SOURCE: Crouch and Wilson (1982:12~. Used with permis- sion. 2.50 In O 2.25 Q a) 2.00 Q 1.75 a) =~ 1.50 a) .= lo: ,~, ol 1950 1955 a, 1 1 1 1960 1965 1970 Year FIGURE 2-2. Accidental deaths per thousand coal mine employees in the United States, 1950-1970. SOURCE: Crouch and Wilson (1982:13~. Used with permis slon.

52 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOC~TIC SOCIETY From a natiorral point of view, given that a certain amount of coal has to be obtained, deaths per million tons of coal is the more appropriate measure of risk, whereas from a labor leader's point of view, deaths per thousand persons employed may be more relevant. A risk analysis that presented either measure of fatalities, by itself, might well be seen by some participants as misleading. Every way of summarizing deaths embodies its own set of values (National Research Council, 1989~. For example, reduction in life expect- ancy treats deaths of young people as more important than deaths of older people, who have less life expectancy to lose. Simply counting fatalities treats deaths of the old and the young as equivalent; it also treats as equivalent deaths that come immediately after mishaps and deaths that follow painful and debilitating disease. Also in the case of delayed illness and death, a simple count of adverse outcomes places no value on what happens to exposed people who may spend years living in daily fear of illness, even if they ultimately do not die from the hazard. Using number of deaths as the summary indicator of risk implies that it is as important to prevent deaths of people who engage in an activity by choice as it is to prevent deaths of those who bear its effects unwillingly. Thus, the death of a motorcyclist in an accident is given the same weight as the death of the pedestrian hit by the motorcycle. It also implies that it is as important to protect people who have been benefiting from a risky activity or technology as it is to protect those who get no benefit from it. One can easily imagine a range of arguments to justify different kinds of unequal weightings for different kinds of deaths, but to arrive at any selection requires a judgment about which deaths one considers most undesirable. To treat all deaths as equal also involves a judgment. In sum, even so simple and fundamental a choice as how to measure fatali- ties is value laden. It can present a dilemma in which no single summary measure, no matter how carefully the underlying analysis is done, can satisfy the expectations of all the participants in a risk decision process. Other methods may be needed to allow the parties' various perspectives to be addressed. Needless to say, the difficulties of choosing a measure expand when the adverse outcomes are less precisely defined. Measures of morbidity, for example, raise questions of judgment about which measures appro- priately aggregate different types of morbidity. Should morbidity be measured in terms of the value of lost work time? If so, is it appropriate to value at zero the health of people who do not work in paying jobs? Should severity of incapacitation be measured, and if so, how? Should long illnesses count the same as multiple short illnesses with the same total duration? Measuring risks to ecosystems present additional judgments because

JUDGMENT IN THE RISK DECISION PROCESS 53 of uncertainties about such matters as which ecological changes consti- tute threats and whether measurement should focus on biotic popula- tions, species, habitats, or other levels of analysis. Measuring economic and social risks requires still other judgments. Measuring each type of outcome presents its particular set of judgments, and each judgment em- beds values. Making Simplifying Assumptions Risk analysis requires making simplifying assumptions when infor- mation is incomplete or difficult to gather by regularly used methods. For example, a toxicologist's quantitative estimate of a chemical's carcino- genic risk may be based on theoretical models and assumptions that are partly subjective and depend on judgment. There are many such as- sumptions: about how toxic substances cause cancer and how the body resists toxins; about the shape of the dose-response function; and that the cause of the cancer can be modeled as resulting from a single chemical without taking into account other unknown or identified causative fac- tors. Nonscientists' risk models and assumptions likewise rest on simpli- fying assumptions about the physical and social worlds (e.g., Kempton, 1991; Bostrom, Fischhoff, and Morgan, 1992~. Although these models are rarely as consistent or mathematical as scientists' models, they may be no more subjective or dependent on judgment. Simplifying assumptions generate especially serious problems when some of the assumptions are unreasonable in the face of information avail- able to people outside the analytical process. For example, sometimes decision makers understandably rely on generalizations, and direct risk analysts to do the same, even though local conditions lie outside the range of applicability of the particular generalizations. The contamination of British pasturelands in Cumbria from the Chernobyl nuclear plant acci- dent presents an example of assumptions that were unreasonable because they misrepresented local conditions (Wynne, 1989~. British scientists based their advice on the assumption that radioactive cesium would quickly become immobilized in soils and so would not pose a long-term threat to the sheep feeding on local grass. Apparently, however, that assumption was based on the response of the clay mineral soils of south- ern England. The high-organic matter, acidic soils of Cumbria did not immobilize cesium as expected. It remained available for root uptake into the grass and found its way into the bodies of the sheep. Being unaware of the local soil conditions, or unaware that cesium behaves differently in different kinds of soils, public officials made a decision and gave advice that turned out to be wrong: they assured farmers the exposure to their

54 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOCRATIC SOCIETY lambs would last only a few weeks when in fact the problem lasted much longer. Simplifying assumptions may also misrepresent local habits and cus- toms that affect the incidence or magnitude of risks. Indeed, the success of exposure assessments relies on being able to accurately model the be- havior of individuals. In epidemiological studies, considerable effort is expended to document patterns of behavior so that risks can be calculated for different groups of exposed individuals. Failure to consider the habits and customs of populations in sufficient detail may undermine simplify- ing assumptions and be directly responsible for events that cause loss. For example, part of the debate about the health effects of malathion spraying for Medfly control concerned whether local residents some of whom did not understand English-would respond appropriately to broadcast warnings to stay indoors during sprayings. Risk characterizations and the resulting decisions can fail because they include incorrect assumptions about geographical, economic, struc- tural, organizational, and other conditions that may constrain the way those at risk respond to a hazard. For example, in the Cumbrian sheep farming areas after the Chernobyl accident, British officials set up a sys- tem for keeping contaminated lambs off the market. They demanded that farmers apply for permission to sell lambs 5 days before the actual sale, not recognizing the farmers' needs to act spontaneously as conditions change (health of lambs, market volume, location of market at which to sell, condition of pasture, etc.~. Officials also advised farmers to keep the lambs out of the valleys to minimize radiation exposure, but the farmers found such advice preposterous because they could not control their flocks' movements in the unfenced fields (Wynne, 1989~. The risk esti- mates erred by assuming management strategies that farmers could not reasonably be expected to adopt. Risk characterizations often implicitly (and inaccurately) assume that individuals will do as instructed and that organizations will function as routines or regulations specify. In estimating migrant farm workers' exposures to pesticides, for example, risk analysts may be directed to assume that pesticides are applied as required by regulations and that workers wear the prescribed protective gear. This assumption may be unreasonable: Inspection of the working conditions where migrants are employed suggests a much different pattern of behavior, both of the grow- ers and the workers. One result of assuming that rules are followed is, in this instance, a serious underestimate of actual exposures, in part because large numbers of migrants do not regularly use self-protective measures (Vaughan, 1993a, 1993b). Individuals may fail to follow instructions be- cause of inability to read or understand them, failure to make sense of the language of risk estimation, lack of motivation to comply, various pres

JUDGMENT IN THE RISK DECISION PROCESS 55 sures for noncompliance, a belief that their actions will not really reduce risk, or other reasons. Such factors alter risks of many kinds, including the risks of pesticides to farm workers (Vaughan, 1993a) and various conventional health risks (Ell and Nishimoto, 1989; Peterson and Stunkard, 1989; Vaughan, 1995~. Risk analyses and characterizations sometimes make unreasonable assumptions about so-called human factors, such as breakdowns in the interaction between equipment and its operators; unanticipated interven- tions of "outsiders" (from disgruntled former employees to uninformed legislators); "organizational factors," such as failures of commitment to controlling risks, bureaucratic attenuation of information flows, diffusion of responsibility, coordination problems among subunits, and the low status of safety and maintenance units in many organizations; the atro- phy of vigilance over time, both in individuals and organizationally; and a skewed distribution of organizational resources (e.g., Perrow, 1984; Shrivastava, 1987; Freudenburg, 1992; Clarke, 1993; Clarke and Short, 1993~. Unrealistic assumptions that such phenomena are unimportant can be easily recognized by individuals with long experience observing the relevant behaviors, who have a kind of expertise the professional risk analysts may lack. Risk characterizations often assume that organizations will function according to plan in a crisis. The validity of this assumption is critical for accurately understanding many risks, including those from nuclear power plant failures, various kinds of industrial and shipping accidents, and air traffic accidents. These situations present workers, work teams, and or- ganizations with the generic problem of shifting from a routine mode of operation to a crisis mode without losing effectiveness. For individuals, performance depends on the ability to function well under stress; with fatigue or sleep disruption; and in the context of environmental stressors such as heat, noise, and vibration. For individuals and work groups, performance depends on the ability to switch tasks effectively, to manage task priorities, to retain skills and routines from past training, and to meet challenges of leadership and coordination. Individuals and groups do often meet all these challenges, and crisis responses are often quite effec- tive, but research does not support the baseline assumption that task groups will reliably function as planned (see National Research Council, 1993b). Risk characterizations based on such an assumption, especially if they do not consider the past record of an organization in managing the particular risk or other relevant evidence on individual and organiza- tional performance, are likely to be misleading and to be criticized as inadequate by people who are well acquainted with the organization or the kinds of behavioral changes a particular crisis demands. Risk characterizations may be based on unrealistic assumptions about

56 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOC~TIC SOCIETY how well an organization will stay vigilant against low-probability catas- trophes. For example, for the first several years after the Alaska pipeline opened, the Alyeska Pipeline Service Company maintained an emergency response team and escorted each tanker out of Nlaldez harbor with a tug as precautionary measures. Both practices were abandoned after several years without tanker accidents, so neither was in place in March 1979 when the Exxon Valdez grounded on leaving the harbor, spilling 260,000 barrels of oil into Prince William Sound (Clarke, 1993~. filyeska has also been criticized for systematically disregarding infor- mation suggesting that a catastrophe was likely; it had drafted and prob- ably believed in unreasonably optimistic contingency plans (Clarke, 1993~. Organizational tendencies, such as to disregard warnings about possible dangers, have also been implicated in the accident at Three Mile Island (President's Commission on the Accident at Three Mile Island, 1979) and the explosion of the space shuttle Challenger (Pate-Cornell and Fischbeck, 1993; Presidential Commission on the Space Shuttle Challenger Accident, 1986; Vaughan, 1990~. Some analysts see such organizational responses as predictable, especially given production pressures and the tendency for bad news to be filtered out as it passes up the organizational chain of command (Freudenburg, 1992; Clarke, 1993~. The state of an organization's emergency preparedness is relevant for risk characteriza- tion, and it is more appropriate to estimate it, when possible, on the basis of information than on general assumptions about organizational behav- ior. SYNTHESIS Synthesizing information is a well-recognized difficulty that affects risk characterization, and it will remain so even if all the other steps in the process better address the issues discussed above. This section considers four major sources of difficulties in synthesizing information: summari- zation; the multidimensional nature of risk; the meaning of risk estimates; and communication. Summarization The fundamental challenge in synthesis, from a technical standpoint, is to produce an unbiased summary of existing knowledge. Even a single piece of scientific evidence can often be summarized in various ways, equally correct and truthful, that convey strikingly different understand- ings or meanings to audiences. One example (discussed above) is fatality estimates from the Chernobyl accident. U.S. analysts summarized the risk in terms of the absolute numbers of excess cancer deaths predicted

JUDGMENT IN THE RISK DECISION PROCESS 57 from a linear no-threshold model about 50,000, which seemed high; the Soviet government summarized the information from the same model as a percentage increase in deaths among the millions of people who had been exposed an increase of about one-quarter of 1 percent, which seemed low (Smith, 1986~. Numerous research studies have demonstrated that different (but logically equivalent) ways of summarizing the same risk information can lead to different understandings and different preferences for decisions. One dramatic example comes from a study that asked people to imagine that they had lung cancer and had to choose between two therapies, surgery or radiation (McNeil et al., 1982~. The two therapies were de- scribed in some detail. Then, some subjects were presented with the cumulative probabilities of surviving for varying lengths of time after the treatment, while other subjects received the same cumulative probabili- ties, but framed in terms of dying rather than surviving (see the table below). For example, one group was told that 68 percent of those having surgery will have survived after 1 year, and the other group was told that 32 percent will have died. As the table shows, framing the statistics in terms of survival lowered the percentage of subjects choosing radiation therapy over surgery from 44 percent to 18 percent (McNeil et al., 1982~: Mocle of Summarization Mortality Rates Survival Rates Surgery Radiation Surgery Radiation Treatment 10% 0% 90% 100% After 1 year 32% 23% 68% 77% After 5 years 66% 78% 34% 22% Subjects choosing radiation therapy 44% 18% The effect was as strong when the subjects were physicians as when they were lay people. Such systematic differences in preferences that depend on the way information is summarized or "framed" can be explained by the prospect theory of Kahneman and Tversky (1979), which has been applied to the question of presenting risk information for policy purposes (see, e.g., Cole and Whithey, 1981; Gregory, Lichtenstein, and MacGregor, 1993; Heimer, 1988; Stern, 1991~. According to prospect theory, outcomes of a decision are evaluated as gains or losses from some reference point usually the status quo. The psychological impact of these gains and losses follows a "value function," such as that shown in Figure 2-3. According to this function, the impacts of gains and losses are nonlinearly related to their magnitudes. That is, gaining $200 gives less than twice the value that is

58 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOCRATIC SOCIETY obtained from gaining $100. Moreover, losses have more impact than comparable gains: a $200 loss hurts more than a $200 gain pleases. Prospect theory leads to some dramatic illustrations of the effects of subtle variations in problem framing, Including the above example of lung cancer treatment. Another example comes from a public health problem given to separate groups of respondents (Tversky and Kahneman, 1981~: Problem 1. Imagine that the United States is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Assume that the consequences of the programs are as follows: If Program A is adopted, 200 people will be saved. If Program B is adopted, there is a one-third probability that 600 people will be saved and a two-thirds probability that no people will be saved. Which of the two programs would you favor? Problem 2. (Same introduction as in Problem 1.) If Program C is adopted, 400 people will die. If Program D is adopted, there is a Value - $500 Losses / 1 / / + $500 - - Gains FIGURE 2-3. A hypothetical value function in prospect theory. SOURCE: Kah- neman and Tversky (1979~. Used with permission of the Econometric Society.

JUDGMENT IN THE RISK DECISION PROCESS one-third probability that nobody will die and a two-thirds prob- ability that 600 people will die. Which of the two programs would you favor? 59 - Rio The two problems are formally identical Programs A and C are the same, as are Programs B and D but the preferences tend to be quite different. In one study, 72 percent of the respondents given-Problem 1 chose Program A over Program B. while 78 percent of those given Prob- lem 2 chose Program D (which is formally equivalent to Program B) over Program C (formally equivalent to Program A). This reversal of prefer- ence was predicted by prospect theory on the basis of the concept of a reference point and the nonlinearity of the value function: Program A is chosen over Program B because people see little additional gain from saving 600 lives (which is uncertain), and Program D is chosen over Pro- gram C because people see little extra loss from 600 deaths (which might not even occur) in comparison with 400 deaths that are certain. The policy implications of characterizing risks in terms of potential gains or potential losses can be important. Vaughan and Seifert (1992) note that in a typical decision situation, any choice or policy strategy involves the acceptance of some nonzero level of risk, as well as potential economic or other gains. Such situations easily lend themselves to alter- native conceptualizations, which may highlight either what is to be gained or what is to be lost by a particular course of action. In California, for example, the debate about eradicating the Medfly through aerial spraying of malathion over populated areas brought into focus two contrasting formulations of the policy question. Some groups initially framed the problem as a consideration of what options would minimize the chances of a loss of millions of dollars for California's agricultural industry. Oth- ers framed the question in terms of whether the relative gains associated with aerial spraying were sufficient to justify accepting any additional risks to human health (Roe, 1989~. Similarly, debates about the costs of decreasing workers' exposure to occupational hazards often feature two contrasting positions: one evaluates protective action in terms of maxi- mizing the numbers of lives saved per dollar; the other evaluates the action in terms of the number of lives that could be lost if additional safety provisions are not implemented (Hilgartner, 1985~. In the past, several major public controversies over technological and environmental issues have been marked by contrasting frames that differed by describing policy options either in terms of potential gains or potential losses (e.g., Brunner, 1991; Heimer, 1988; Lawless, 1977~. Prospect theory also implies that decision makers who differ in their views of the status quo will choose different policy options because they begin the decision task from different reference points. For example, a

60 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOC~TIC SOCIETY a: "Present" reference point Value Value of improvement / ___ Past / ~(8) \ Present \ Status I(5) ~\ 1 11 Future Present (8) ~ (5) ~/ I / 1 / 1/ _ _ _ _ b: "Past" reference point Value - // Status Value of restoration FIGURE 2-4. The value of an improvement in prospect theory. SOURCE: Grego- ry, Lichtenstein' and MacGregor, 1993. Used with permission. study asked people to evaluate the desirability of improving the water quality in Oregon's Willamette River from its present state of Grade 5 on a 10-point scale to Grade 8 (Gregory, Lichtenstein, and MacGregor, 1993). In one condition, respondents were told that the river once had quality equivalent to Grade 8; thus, the improvement would represent a restora- tion of lost quality. A second group of respondents were told that the change represented an improvement from the current level of 5 to a level of 8. These two framing conditions, which differed in terms of how they characterized the status quo, are illustrated in Figure 2-4, within the con- text of the value function from prospect theory. Because of the asymme- try of the value function (steeper for losses than for gains), prospect theory predicts that the improvement from 5 to 8 will be more attractive when framed as restoring lost quality (2-4b) than when framed as improving the present quality (2-4a). Indeed, the study found that the desirability of water of Grade 8 was greater for people who believed this quality signi- fied a restoration of lost water quality.3 These examples demonstrate that every way of presenting risk in- formation is a "frame" that can shape the judgments of the participants in a risk decision. The same information can be presented as lives saved or lives lost, mortality rates or survival rates, restoring lost (or "natural") 3This finding might also be interpreted in other ways. Respondents may have placed inherent value on nature and therefore believed that water should be kept at its "natural" quality. They may also have interpreted the information that the water quality was once Grade 8 as evidence that this was an achievable goal.

JUDGMENT IN THE RISK DECISION PROCESS 61 water quality or improving present water quality, and so forth. Neither frame is right or wrong they are just different. There is no scientific way to determine that one summary is more correct, or less biased, than an- other when both accurately reflect the data. Thus, the problem of gener- ating a single unbiased summary of information about risk to meet the needs of participants in risk decisions has no purely technical solution. Any decision about how to synthesize risk information involves judg- ments of considerable practical importance. Because subtle differences in how risk is summarized can have marked effects on understanding, those responsible for synthesis may have considerable ability to influence per- ceptions and behaviors. This possibility creates procedural and ethical problems that experts and public officials must recognize and address in their efforts to characterize risks (MacLean, 1995~. In Chapters 3, 4, and 5 we discuss ways to address these problems by combining analysis with deliberation to arrive at a publicly acceptable, decision-oriented synthesis of available risk information. The Multidimensional Nature of Risk Risk characterizations often focus on a single outcome, most often human fatalities, but as discussed above, even a single outcome has mul- tiple attributes. Furthermore, many risk decisions involve multiple out- comes, so that there are at least several attributes and kinds of informa- tion to synthesize. The general problem is how to characterize what is known about a risk when there is no clear way to combine its many attributes into a single scale or metric. Over the past several decades, research on how people understand, think about, and react to risk has shown that judgments of risk can be described in terms of numerous characteristics or dimensions. Figure 2-5 presents a spatial display of hazards within a perceptual space derived from individual judgments by people who were not experts in risk analy- sis. The factors in this space reflect the degree to which a risk is perceived to be known or understood (vertical dimension) and the degree to which it evokes perceptions of dread, uncontrollability, and catastrophe (hori- zontal dimension). People's response to risk is closely related to the position of a hazard within this space. In particular, the further to the right a hazard appears, the higher its perceived risk, the more people want to see its current risks reduced, and the more they want to see strict regulation to reduce the risk (Slovic, 1987~. In contrast, specialists in risk analysis tend to understand risk in ways not closely related to these dimensions or the characteristics that underlie them. Instead, they tend to see riskiness as synonymous, especially for policy purposes, with expected annual mortality, consistent

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64 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOC~TIC SOCIETY with the ways that risks tend to be characterized in quantitative risk assessments (Slovic, Fischhoff, and Lichtenstein, 1979; The Royal Society Study Group, 1992; Lindell and Malmfors, 1994~. Conflicts over "risk" may reflect differences between specialists in risk analysis and others on their definitions of the concept. In this light, it is not surprising that citations of statistics about "actual risks" often do little to change most people's attitudes and perceptions. Nonspecialists factor complex, qualitative considerations into their estimates of risk, in- cluding judgments about uncertainty, dread, catastrophic potential, con- trollability, equity, and risk to future generations. The legitimate, value-laden issues that underlie these multiple di- mensions of risk need to be considered in risk policy decisions (Fischhoff, Watson, and Hope, 1984~. For example: Is risk from cancer (a dread disease) worse than risk from auto accidents (not so dreaded)? Is a risk imposed on a child more serious than a risk accepted voluntarily by an adult? Are the deaths of 50 passengers in separate automobile accidents equivalent to the deaths of 50 passengers in one airplane crash? Is the risk from an industrial emission worse if the facility is located in a neighbor- hood that has a number of other hazardous facilities nearby? The difficult questions multiply when outcomes other than human health and safety are also considered. As noted in an earlier study (National Research Council, 1989:51~: Technological choices sometimes involve weighing the value of a river vista, a small town style of living, a holy place, or the survival of an endangered species, in addition to human health, against probable ben- efits. Such matters are ultimately matters of values. The fact that hazards differ dramatically In their attributes or charac- teristics helps explain why certain technologies or activities, such as nuclear power, evoke much more intense public opposition than others, such as motorcycle riding, that cause many more fatalities. The implica- tions of "risk perception" for synthesis have been well described in a previous study (National Research Council, 1989:52~: Those quantitative risk analyses that convert all types of human health hazard to a single metric carry an implicit value-based assumption that all deaths or shortenings of life are equivalent in terms of the impor- tance of avoiding them. The risk perception research shows not only that the equating of risks with different attributes is value laden, but also that the values adopted by this practice differ from those held by most people. For most people, deaths and injuries are not equal some kinds or circumstances of harm are more to be avoided than others. One need not conclude that quantitative risk analysis should weight the risks to conform to majority values. But the research does suggest that it is presumptuous for technical experts to act as if they know, without

JUDGMENT IN THE RISK DECISION PROCESS careful thought and analysis, the proper weights to use to equate one type of hazard with another. When lay and expert values differ, reducing different kinds of hazard to a common metric (such as number offatalities per year) and presenting comparisons only on that metric have great potential to produce misunderstanding and conflict and to engender mistrust of expertise. 65 This analysis is still pertinent with reference both to techniques for char- acterizing relative risks in terms of expected deaths and to techniques that compare hazards on a common monetary metric, such as contingent valu- ation methods or various forms of cost-benefit analysis. A number of risk analysts have sought technical solutions to the prob- lem of taking qualitative aspects of risk into account. Generally, they have proposed broadening risk analysis to incorporate one or more of the various characteristics identified in studies of perceived risk: for example, distinguishing between voluntary and involuntary activities in assessing risk-benefit balances (Starr, 1969~; giving proportionally more weight to large accidents than to numerous small accidents that cause the same amount of damage or number of deaths (Wilson, 1975; Griesemeyer and Okrent,1981~; and adjusting risk estimates to take into account the impor- tance of various risk-perception characteristics (Rowe, 1977; Litai, Lanning, and Rasmussen, 1983~. None of these proposals has yet been developed to the point of application in actual risk assessments. A related approach has successfully integrated several of the dimen- sions of risk in a formal way and done so in real applications. This approach has been developed by two Swiss analysts to aid decisions about the safety of ammunition storage depots and transportation systems, in- cluding the design of a high-speed railway in Germany (Bohnenblust and Schneider, 1984~. The method characterizes the risk reduction in terms of cost-effectiveness, and it attributes more value to reducing risks that are involuntary, poorly understood, potentially catastrophic, and hard to con- trol. Although this Swiss model has been applied to a number of impor- tant decision problems, there is a need to align the model more closely with recent research that has been done on social, cultural, and psycho- logical factors (see, e.g., Krimsky and Golding, 1992~. This might be ac- complished, at least in principle, by refining quantitative approaches to risk analysis (see Chapter 4~; it might also be achieved qualitatively through deliberative processes (see Chapters 3 and 5~. Another way to incorporate some of these dimensions into risk char- acterizations is to apply multiattribute utility analysis (e.g., von Winter- feldt and Edwards, 1986; Fischhoff, Watson, and Hope, 1984; Gregory, Lichtenstein, and Slovic, 1993; Brody and Rosen, 1994; see also Appendix A). In this technique, individuals identify value dimensions, attributes, or outcomes that are important to them, assign relative weights to them, and evaluate the outcomes identified by risk analysis (or a set of policy

66 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOCRATIC SOCIETY options) on each attribute. Multiattribute utility analysis allows individu- als to compare options that yield different packages of risks and benefits. It allows for evaluations to be explicitly subjective: individuals can, for example, assign a numerical value to a quality such as "incidental en- counters with neighbors." But it does not, by itself, solve the problem of providing risk estimates for populations because there is no acceptable formula for aggregating individuals' evaluations. Should each indivi- dual's evaluation have equal weight, or should those who might bear the risk have a greater weight? This problem of estimating risks for whole groups when the risks are of various kinds pushes the limits of analysis. (In Chapter 4 we discuss the strategy of using analytical techniques to reduce the dimensionality of risk. In Chapter 5 we discuss the alternative strategy of combining deliberative processes with analysis to help the participants in decisions develop working understandings of multi- attribute risks.) The Meaning of Risk Estimates Separable from the technical questions about how best to estimate the risk of a particular agent with respect to a particular outcome is the ques- tion of what the risk estimate means, or should mean, to participants in risk decisions. Risk characterizations often fail because they attribute meaning to scientific estimates in ways that mislead participants in the risk decision process or that are incomprehensible to them. This section discusses several such sources of failure: in the treatment of uncertainty, in inferences about which populations will be affected, and in inferences about how a risk estimate should be interpreted in light of other risks to which a population is exposed. Uncertainty Risk characterizations often give misleading information about un- certainty in several ways. They may give the impression of more scien- tific certainty or unanimity than exists (or of more uncertainty or dissen- sion). They may suggest that uncertainty is a matter of measurement when in fact it is a matter of disagreement about whether a particular theory applies or differences in judgment about how to infer something that is unknown from something that is known. And they may give the impression that certain risks do not exist when in fact they have not been analyzed. Civil engineers, public health professionals' and others often take account of uncertainty by a strategy of "conservatism." This means that they recommend decisions or actions that leave a margin for error that is

JUDGMENT IN THE RISK DECISION PROCESS 67 intended to protect the public if the actual risk turns out to be greater than they predict. It is often argued that risk analysts should instead present their best available estimate to decision makers, along with an explicit characterization of its uncertainty, and allow the decision makers to de- cide explicitly how much margin of safety to allow.4 Either approach embodies a value choice about the best way to characterize risk and pro- tect public health and safety, and there is no scientific technique for deter- mining which approach is preferable (National Research Council, 1994a). There is strong agreement that risk analysts should explicitly summa- rize uncertainty, and there are methods for doing so (e.g., Morgan and Henrion, 1990~. But despite the admonitions of officials in some govern- ment agencies (Habicht, 1992; Browner, 1995) and the recommendations of outside panels (e.g., National Research Council, 1994a), many risk char- acterizations still present point estimates of risk, representing these as upper-bound estimates and providing little or no analysis of the extent of overestimation. In spite of the obvious shortcomings of point estimates and the efforts to develop alternative ways of describing uncertainty- such as with probability distributions or scenario approaches no alter- native has gained widespread recognition as acceptable and practical within EPA and other regulatory agencies. It is difficult to characterize what is known about uncertainty without making the risk appear either larger or smaller than analysts believe it to be (see, e.g., Johnson and Slovic, 1995~. And the difficulties are not yet yielding to analysis: the more that characterizing uncertainty is debated as an analytical problem, the more complex it appears to be (see, e.g., Finkel, 1990; National Re- search Council, 1994a:Chapter 9~. Characterizing uncertainty analytically puts risk analysts on the horns of a dilemma: simple characterizations are likely to give an erroneous impression of the extent of uncertainty, but more careful and elaborate characterizations may be incomprehensible to nonspecialists and so un- usable by decision makers and some other participants. Like the problem of finding a single, unbiased summary of accepted scientific knowledge, the problem of summarizing uncertainty may have no technical solution. We believe, however, that a solution might be found in the processes that lead to a risk decision, processes that combine iterative deliberation and analysis and provide participants with enough understanding of uncer- tainty to appreciate where scientists agree and where they disagree. (The last section of this chapter outlines key issues in process design; Chapter 4 presents a more detailed discussion of understanding uncertainty.) 4For an illuminating exchange of views on the "conservatism" issue, see Finkel (1994) and McClellan and North (1994).

68 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOCRATIC SOCIETY Specific Populations The question of who is at risk is important both for decision makers and the persons whose health and safety is of concern (Vaughan and Seifert, 1992; see also Konheim, 1988; Nelkin, 1989~. In presenting aggre- gate risk estimates to community residents who are concerned about a hazard, officials often fail to answer the important question for many interested and affected parties: "What does this mean for me or my family?" (e.g., Sharlin, 1986~. When confronted with statistical risk esti- mates, people often seek to reframe the question in terms of personal risk (Plough and Krimsky, 1987; Siegel and Gibson, 1988~- an issue not ad- dressed by the aggregate numbers. If a risk characterization does not address such questions, both it and the analysis behind it may be discred- ited by participants in the decision process. If it does address them, different ways of framing the same information can create different un- derstandings. Such failings often arise when a risk characterization assumes that estimates of risks to one population are sufficient to answer risk questions about what may be a different population. For example, the 1989 contro- versy over the use of Alar on apples centered on the risks to children, who drink more apple juice than adults, but the standard was set on the as- sumption that an adult male weighing 70 kilograms was an adequate surrogate for everyone (lasanoff,1987~. The risk reduction expected from vaccination programs is usually presented for the entire population al- though rural children, who live far from treatment centers, may not re- ceive as much benefit as other children because vaccination programs may not reach them. Migrant farm workers and their families may be inadequately protected against workplace risks because standards are based on exposure under very different working conditions (Vaughan, 1993a). To adequately summarize risks to some populations may require be- havioral analyses as well as the traditional analyses of exposure and sen- sitivity. For example, different groups of farm workers who are exposed to pesticides vary in their ability to understand warning materials and in their propensity to take self-protective action when given the opportunity (Vaughan, 1993a). Knowledge about reading ability and the psychologi- cal factors underlying self-protective behaviors are not usually incorpo- rated in risk characterizations although they can obviously affect both the risks to exposed individuals and the effectiveness of options to reduce those risks. Thus, a risk characterization that fails to carefully consider which populations the estimate is for may be inadequate to inform deci . . . slon magma.

JUDGMENT IN THE RISK DECISION PROCESS Multiple Exposures 69 Risk analyses for multiple exposures are often based on the assump- tion that risk from genotoxic carcinogens are additive and that non-cancer risks are not, unless the agents operate by similar mechanisms. The de- gree to which this assumption holds is subject to debate because of the limited data available to address it. It is even less clear how well the assumption may apply for combinations of biological, chemical, and phy- sical risks to an ecosystem. EPA has considered multiple chemical eco- logical risks, but only at certain sites and within narrow bands. Although the agency also recognizes physical hazards and those that arise from management practices (U.S. Environmental Protection Agency, 1992a), it has not considered their possible interactions. For humansr evidence of serious drug interactions suggests that even with chemical hazards there are some instances in which the assumption of additivity may be ques- tionable. Increasing concerns about synergistic effects warrant careful consideration of how to address them in risk characterizations. A related issue is the treatment of past exposures or the past health conditions of some of the population at risk. This issue may arise as one of health (e.g., the possibility that past exposures have synergistic effects with present ones) or of equity. As the Chester, Pennsylvania, case sug- gests, residents of an industrial community who believe that they have already had more than their share of exposure to chemical risks may demand on equity grounds that past exposures be considered as part of the risk characterization. Communication The success of a risk characterization depends on its effective delivery to the participants in a risk decision. Typically, not all participants will understand a risk message in the same manner. Analogies are often used to make risk summaries more understandable, but analogies are usually very specific and sometimes depend on culture, status, age, gender, and other characteristics for their interpretation. If the manner in which the risk message will be interpreted by different groups or participants is not considered, uneven risk protection across groups could result (Vaughan, 1993a, 1995~. Another even more fundamental problem is that of compre- hension. Non-English-speaking people obviously get no benefit from a risk characterization in English. Messages prepared in written form will be ignored by people who cannot read or who are used to receiving information in other forms. The history of interaction between an organization that is presenting a risk characterization and the interested and affected parties can be an

70 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOC~TIC SOCIETY other source of communication problems (e.g., Krimsky and Plough, 1988~. A party that has had unsatisfactory experiences with that organi- zation or that issue may simply be unreceptive to new information from that source. For example, in a decision-making process to permit experi- mental land application of sewage sludge on farmland, an elaborate pub- lic involvement process collapsed partly because the same community had been involved in a landfill siting controversy just one year earlier. A widespread belief that the community was targeted as a "dumping ground" overpowered any positive reaction to the public involvement plans. People in the community organized against the new proposal partly because of ill feelings toward the state regulatory agency (Renn et al., 1991~. CONCLUSION: THE IMPORTANCE OF PROCESS DESIGN This chapter surveys the variety of judgments made sometimes, without careful consideration in the course of analyzing and character- izing risk that can become lightning rods for controversy. They become problematic when they conflict with the judgments of some of the inter- ested and affected parties to a decision, so that the resulting risk charac- terization does not address these parties' needs. The best way to prevent such problems, we believe, is not to call all such judgments into question in every decision process. Doing this would make risk analysis and char- acterization inordinately complex and resource intensive. We believe the best preventive is to devise analytic-deliberative processes that will pay appropriate attention to the judgments involved in problem formulation and the other tasks, inform these judgments with the best available knowl- edge and the perspectives of the spectrum of decision participants, and thus guide risk characterizations toward addressing the needs of the deci slon. When understandings of risk depend on potentially controversial judgments, it seems prudent to involve those who are likely to be affected by the decisions that rely on those judgments. If, for instance, there are many scientifically defensible ways of counting deaths and if the choice has serious implications for the concerns of some of the interested and affected parties, it makes sense to involve those parties in selecting the measures of death that will be used to characterize risk. Organizations responsible for characterizing risk should anticipate the value-based judg- ments that are likely to become contentious in the context of a particular risk characterization and consider putting them on the agenda for the analytic-deliberative process. We emphasize strongly that improved risk characterization based on

JUDGMENT IN THE RISK DECISION PROCESS 71 a better designed process will not eliminate conflict about risk. The best it can hope to do is to eliminate or reduce those conflicts that are based on misunderstandings, mistrust, miscommunication, inadvertent neglect of a point of view, and the like. It might be said that although good practice does not predictably lessen conflict, bad practice predictably increases it. Designing an analytic-deliberative process involves many choices. Who should be involved in the tasks that support risk characterization, beginning with problem formulation? In what ways and through what procedures should they be involved? At what points in the process should they be involved? Under what conditions should past assumptions, con- clusions, or decisions be reconsidered? These choices can affect the ulti- mate content of a risk characterization, the ways participants in a decision understand the risks, and acceptance of the process. Federal agency officials with a legislative mandate to protect the pub- lic against dangerous exposures to a toxic substance commonly respond to preliminary evidence of a possible hazard by directing toxicologists, epidemiologists, and other technical experts on the hazard to estimate the health risks associated with the substance. The process involves these experts, agency officials and policy makers, attendees at any required public hearings (whose ideas may or may not be given serious consider- ation), and any legislators and interest groups that know about the pend- ing decision and are able to gain access to the process. This standard process often leads to objections from interested and affected parties that they have been disenfranchised, that their ideas have been ignored, that their concerns have not been taken seriously, that the risk analysis was incomplete or irrelevant, that the analyses are so complex and arcane that they cannot participate meaningfully, and so forth in short, serious dis- affection with the process and the resulting risk characterization. Such outcomes have led many observers to recommend increased public involvement in risk decision making, better two-way communica- tion between agencies and interested and affected parties, involvement of these parties early in the decision process, and other changes that would make risk decision making processes more broadly participatory (e.g., Kunreuther, Fitzgerald, and Aarts, 1993; Leroy and Nadler, 1993; Slovic, 1993a; National Research Council, 1994b). We agree that more complete involvement of interested and affected parties in risk characterization is often essential for improving the process. It can also be essential for arriving at sound analyses. We note here some key principles of increas- ing meaningful participation in risk characterization that are developed in more detail in the next several chapters: · give explicit attention to the design of the process that informs risk . . . clec~s~ons;

72 UNDERSTANDING RISK: INFORMING DECISIONS IN A DEMOCRATIC SOCIETY · solicit and seriously consider input from the interested and af- fected parties as appropriate at various points in the process leading to risk characterizations; and · plan for iteration in the decision process, that is, for reconsidering past assumptions, conclusions, and process-related decisions on the basis of new data and changes in the decision situation. We reiterate that risk characterization is more than a synthesis of information developed by analytical techniques. Analysis has inherent limitations in the face of the multidimensional and value-laden nature of many risk decisions. The success of risk characterization depends not only on doing and describing analysis well, but also on choosing analyses that address the needs of decision participants and on making the choice through a process that those parties trust. Organizations responsible for characterizing risks should plan to blend analysis with deliberative pro- cesses that clarify the concerns of interested and affected parties, help prevent avoidable errors, offer a balanced and nuanced understanding of the state of knowledge, and ensure adequately broad participation for a given risk decision.

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Understanding Risk addresses a central dilemma of risk decisionmaking in a democracy: detailed scientific and technical information is essential for making decisions, but the people who make and live with those decisions are not scientists. The key task of risk characterization is to provide needed and appropriate information to decisionmakers and the public. This important new volume illustrates that making risks understandable to the public involves much more than translating scientific knowledge. The volume also draws conclusions about what society should expect from risk characterization and offers clear guidelines and principles for informing the wide variety of risk decisions that face our increasingly technological society. Understanding Risk

  • Frames fundamental questions about what risk characterization means.
  • Reviews traditional definitions and explores new conceptual and practical approaches.
  • Explores how risk characterization should inform decisionmakers and the public.
  • Looks at risk characterization in the context of the entire decisionmaking process. Understanding Risk discusses how risk characterization has fallen short in many recent controversial decisions. Throughout the text, examples and case studies--such as planning for the long-term ecological health of the Everglades or deciding on the operation of a waste incinerator--bring key concepts to life. Understanding Risk will be important to anyone involved in risk issues: federal, state, and local policymakers and regulators; risk managers; scientists; industrialists; researchers; and concerned individuals.
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