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Product Liability and Innovation: Managing Risk in an Uncertain Environment The Inconvenient Public: Behavioral Research Approaches to Reducing Product Liability Risks BARUCH FISCHHOFF JON F. MERZ There would not be any product liability suits if there were not any people involved with engineered systems. Unfortunately, people are everywhere, and they sometimes make mistakes—as consumers, operators, and patients. They misunderstand instructions, overlook warning labels, and employ equipment for inappropriate purposes. In many cases, they realize that any ensuing misfortune is clearly their own fault, as when they have been drinking or using illicit drugs. Often, though, their natural response is to blame someone else for what went wrong. In psychological terms, there are both cognitive and motivational reasons for this tendency. Cognitively, injured parties see themselves as having been doing something that seemed sensible at the time, and not looking for trouble. As a result, any accident comes as a surprise. If it was to be avoided, then someone else needed to provide the missing expertise and protection. Motivationally, no one wants to feel responsible for an accident. That just adds insult to injury, as well as forfeiting the chance for emotional and financial redress. Of course, the natural targets for such blame are those who created and distributed the product or equipment involved in an accident. They could have improved the design to prevent accidents. They should have done more to ensure that the product would not fail in expected use. They could have provided better warnings and instructions in how to use the product. They could have sacrificed profits or forgone sales, rather than let users bear (what now seem to have been) unacceptable risks. It is equally natural for producers and distributors to shift the blame back to the user. Cognitively, the wisdom of hindsight makes it obvious to
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Product Liability and Innovation: Managing Risk in an Uncertain Environment them what the user should have done or seen in order to avoid an accident. They remember all the care that was taken in the design process. They see no ambiguity in the instructions and accompanying warnings. They would not have dreamed of using the system or product in the way that led to the accident. Motivationally, no one wants to be responsible for another's misfortune, even where there are no financial consequences. No one is in the business of hurting people. To the extent that this description is accurate, it depicts an unhappy situation. Accidents keep happening, while each side blames the other. At the extreme, injured users may translate their grievances into lawsuits, while the producers and distributors fume about the irresponsible public. There is, of course, a steady supply of lawyers, politicians, and pundits ready to fan these frustrations. In the short run, it can be reinforcing to hear about the other party's venality or incompetence. In the long run, though, such sweeping claims merely reinforce prejudices and obscure the opportunities for progress. In this light, technical innovation is threatened not just by an unthinking public, but also by an unthinking attitude toward the public. Few people in the technical community have any significant training in the behavioral sciences. As a result, it is hard for them to make sense of the behavior that they see or to devise creative improvements in design. They may have been drawn to engineering because it promised greater predictability than did dealing with fallible people. They may be reluctant to acknowledge the limits of their expertise or to include new kinds of expertise in already complex design processes. This paper will analyze the opportunities for incorporating scientific knowledge about one aspect of human behavior in the product design and management process: how people understand the risks of the products they use. It will look at both quantitative understanding, regarding the magnitude of risks and benefits, and qualitative understanding, regarding how risks are created and controlled. Quantitative understanding is essential if people are to realize what risks they are taking, decide whether those risks are justified by the accompanying benefits, and confer informed consent for bearing them. Qualitative understanding is essential to using products in ways that achieve minimal risk levels, to recognizing when things are going wrong, and to responding to surprises. After presenting some of the empirical and analytical procedures for assessing and improving these kinds of understanding, this paper will consider the extent of their possible contribution to product safety and innovation. Its goal is to encourage attention to these issues in the product stewardship process.
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Product Liability and Innovation: Managing Risk in an Uncertain Environment ARENAS FOR RISK PERCEPTIONS Although technical experts have the luxury of specializing in the management of particular risks, members of the general public do not. They face too many risks in their lives to acquire detailed knowledge of more than a minute portion of those risks. Their risks include affairs of the heart, ballot box, and pocketbook, as well matters of health and safety. Even in matters of physical welfare and survival, the list of concerns can be very long. Table 1 provides an illustrative list of situations in which the risk perceptions of individuals have consequences. The enormous range of risks creates both challenges and opportunities for the manufacturers and distributors of potentially hazardous products. On the one hand, they must fight to divert a portion of the public's scarce attention to the potential risks of their products. In so doing, they may imperil their financial security by diverting attention from the benefits of TABLE 1 Arenas for Risk Perception Workplace On-the-job safety Right-to-know laws Workers' compensation Neighborhood Rumors Emergency response Community right-to-know Siting Courts Informed consent Risk-utility analysis Psychological stress Regulation Agenda setting Safety standards Local initiatives Industry Innovation Public relations Insurance Product differentiation (by safety)
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Product Liability and Innovation: Managing Risk in an Uncertain Environment those products or by making their products seem riskier than other (possibly competing) products whose risks are presented less diligently. On the other hand, they can rely on users having considerable experience with related processes, as well as a repertoire of cognitive and physical skills acquired in a wide variety of situations. Indeed, new product introductions can be particularly complicated when the target audience lacks relevant experience. Introductions may be quicker in the short run, but more expensive in the long run, when that audience puts too much faith in its existing knowledge and skills. SOURCES FOR UNDERSTANDING THE PUBLIC Just as it is sensible for laypeople confronted by a new product to look for familiar experiences and general knowledge, its producers might do the same when anticipating the response of that public. Responsible firms can be trusted to examine the specific experiences that members of the public have with their own and competitors' existing products. They may not, however, find their way to the general research literature on risk-related behavior. The next section of this paper is intended to improve access to that literature by summarizing general patterns and providing representative references. It draws primarily on the research literature in human judgment and decision making and its subspecialty focused on the perceptions of technological hazards. These fields are, roughly, 35 and 20 years old, respectively. Their roots are in the literatures on attitude change, clinical judgment, and human factors, each of which received a major push as part of the U.S. effort during World War II, as well as the much older fields of experimental psychology and decision theory. These literatures provide substantive results that can be tentatively extrapolated to predict or explain people's responses to new products. For example, many studies have found that people are relatively insensitive to the extent of their own knowledge (Fischhoff et al., 1977; Wallsten and Budescu, 1983). The most common result is overconfidence, for example, being correct on only 80 percent of those occasions when one is absolutely certain of being correct. The generality of these findings (in those settings that have been studied) suggests that people might have undue confidence in their beliefs about new products and about how the attendant risks can be controlled. If this seems like a reasonable and worrisome hypothesis, then the research literature might be consulted for procedures able to improve people's judgment. For example, telling people that overconfidence is common seems to have little effect, whereas presenting people with personalized feedback regarding the appropriateness of their own confidence can make a positive difference (Fischhoff, 1982). If one wanted to test these or other hypotheses, then the existing research
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Product Liability and Innovation: Managing Risk in an Uncertain Environment also provides well-understood methodologies for conducting studies specific to particular risks. Ascertaining people's beliefs and values is a craft having as many nuances as does assessing their physiological functions or conducting measurements in the natural or biological sciences. For example, two formally equivalent ways of asking people to estimate how large a risk is can produce estimates that vary by several orders of magnitude (Fischhoff and MacGregor, 1983). A study that used one method might make it seem as though people underestimate the risk, whereas a study using the other method would produce apparent overestimates. As in other sciences, such measurement artifacts are sometimes predicted on the basis of general theories (Poulton, 1968, 1982), whereas in other cases they are discovered by trial and error. Exploiting this experience offers the opportunity to avoid the mistaken interpretations, and perhaps even mistaken policies, that such experimental artifacts can produce. The applications of these methods to people's perceptions of technological hazards have seldom produced results challenging the overall conclusions from the general literature on judgment and decision making. These studies have, however, provided important elaborations, for example, showing just what people believe about particular risks, just how confident they are in those beliefs, or just how far they trust risk information coming from particular sources. They have also drawn attention to general issues with particular significance for consumer products and workplace processes, such as how people evaluate the trustworthiness of risk information (Baum et al., 1983; Johnson and Tversky, 1983; Richardson et al., 1987; Weinstein, 1987). These detailed, systematic empirical studies stand in stark contrast to the casual observations that dominate many discussions of the public's behavior. Perhaps surprisingly, even scientists, who would hesitate to make any statements about topics within their own areas of competence without a firm research base, are willing to make strong statements about the public on the basis of anecdotal evidence. Unfortunately, immediate appearances can be deceiving, as when salient examples of public behavior are not particularly representative. And, as mentioned, even systematic observations can be misleading if not undertaken with a full understanding of the relevant methodology. An unfounded belief in having understood the public is a serious barrier to acquiring a genuine understanding. The limits to casual observation might be seen in the coexistence of conflicting claims about the public, often associated with conflicting recommendations regarding how to deal with it. For example, advocates of deregulation frequently describe members of the public as understanding risks so well that they can readily fend for themselves in an unfettered marketplace. This confidence in the public is usually shared by those who advocate extensive public participation in risk management, through such
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Product Liability and Innovation: Managing Risk in an Uncertain Environment avenues as hearings and information campaigns (Magat and Viscusi, 1992). Quite the opposite conclusion about public competence underlies proposals to leave risk management to technical experts or to force people to adopt risk-management practices that are "for their own good." Examples here include seatbelts, crash helmets, and dietary restrictions. Given the political and safety implications of these conflicting perceptions about the public, laypeople's behavior would seem to merit careful study. Good, hard evidence could provide guidance for managing risks, resolving conflicts between the public and technical experts, supplying the information that the public needs for better understanding, and creating technologies whose risks are acceptable to the public (Viscusi, 1992). The following section provides a summary of conclusions that can be drawn from studies of risk perception, as well as from the general research literature regarding judgment and decision making. WHAT IS KNOWN People Simplify Most substantive decisions require people to deal with more nuances and details than they can readily handle at any one time. People have to juggle a multitude of facts and values when deciding, for example, whether to change jobs, trust merchants, or protest a toxic landfill. To cope with the overload, people simplify. Rather than attempting to think their way through to comprehensive, analytical solutions to decision-making problems, people try to rely on habit, tradition, the advice of neighbors or the media, and on general rules of thumb, such as nothing ventured, nothing gained. Rather than consider the extent to which human behavior varies from situation to situation, people describe other people as encompassing personality traits, such as being honest, happy, or risk seeking (Nisbett and Ross, 1980). Rather than think precisely about the probabilities of future events, people rely on vague quantifiers, such as "likely" or "not worth worrying about"—terms that are used differently in different contexts and by different people (Beyth-Marom, 1982). The same desire for simplicity can be observed when people press risk managers to categorize technologies, foods, or drugs as "safe" or "unsafe," rather than to treat safety as a continuous variable. It can be seen when people demand convincing proof from scientists who can provide only tentative findings. It can be seen when people attempt to divide the participants in risk disputes into good guys and bad guys, rather than viewing them as people who, like themselves, have complex and interacting motives. Although such simplifications help people to cope with life's complexities, they can also obscure the fact that most risk decisions involve
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Product Liability and Innovation: Managing Risk in an Uncertain Environment gambling with people's health, safety, and economic well-being in arenas with diverse actors and shifting alliances. Once People's Minds Are Made Up, It Is Hard to Change Them People are quite adept at maintaining faith in their current beliefs unless confronted with concentrated and overwhelming evidence to the contrary. Although it is tempting to attribute this steadfastness to pure stubbornness, psychological research suggests that some more complex and benign processes are at work (Nisbett and Ross, 1980). One psychological process that helps people to maintain their current beliefs is feeling little need to look actively for contrary evidence. Why look if one does not expect that evidence to be very substantial or persuasive? For example, how many environmentalists read the Wall Street Journal and how many industrialists read the Sierra Club's Bulletin to learn something about risks (as opposed to reading these publications to anticipate the tactics of the opposing side)? A second contributing thought process is the tendency to exploit the uncertainty surrounding apparently contradictory information in order to interpret it as being consistent with existing beliefs (Gilovich, 1993). In risk debates, a stylized expression of this proficiency is finding just enough problems with contrary evidence to reject that evidence as inconclusive. A third thought process that contributes to maintaining current beliefs can be found in people's reluctance to recognize when information is ambiguous. For example, the incident at Three Mile Island would have strengthened the resolve of any antinuclear activist who asked only, ''How likely is such an accident, given a fundamentally unsafe technology? —just as it would have strengthened the resolve of any pronuclear activist who asked only, "How likely is the containment of such an incident, given a fundamentally safe technology?" Although a very significant event, Three Mile Island may not have revealed very much about the riskiness of nuclear technology as a whole. Nonetheless, it helped the opposing sides to polarize their views. Similar polarization followed the accident at Chernobyl, with opponents pointing to the consequences of a nuclear accident, which they see as coming with any commitment to nuclear power, and proponents pointing to the unique features of that particular accident, which are unlikely to be repeated elsewhere, especially considering the precautions instituted in its wake (Krohn and Weingart, 1987). People Remember What They See Fortunately, given their need to simplify, people are good at observing those events that come to their attention and that they are motivated to understand
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Product Liability and Innovation: Managing Risk in an Uncertain Environment (Hasher and Zacks, 1984; Peterson and Beach, 1967). As a result, if the appropriate facts reach people in a responsible and comprehensible form before their minds are made up, there is a decent chance that their first impression will be the correct one. For example, most people's primary sources of information about risks are what they see in the news media and observe in their everyday lives. Consequently, people's estimates of the principal causes of death are strongly related to the number of people they know who have suffered those misfortunes and the amount of media coverage devoted to them (Lichtenstein et al., 1978). Unfortunately, it is impossible for most people to gain first-hand knowledge of many hazardous technologies. Rather, what laypeople see are the outward manifestations of the risk-management process, such as hearings before regulatory bodies or statements by scientists to the news media. In many cases, these outward signs are not very reassuring. Often, they reveal acrimonious disputes between supposedly reputable experts, accusations that scientific findings have been distorted to suit their sponsors, and confident assertions that are disproven by subsequent research (MacLean, 1987; Rothman and Lichter, 1987). Although unattractive, these aspects of the risk-management process can provide the public with potentially useful clues to how well technologies are understood and managed by industry and regulatory agencies. Presumably, people evaluate these clues just as they evaluate the conflicting claims of advertisers and politicians. It should not be surprising, therefore, that the public sometimes comes to conclusions that differ from what risk managers hope or expect. For example, it was reasonable to conclude that saccharin is an extremely potent carcinogen after seeing the enormous scientific attention that it generated some years back. Yet, much of the controversy actually concerned how to deal with a food that was strongly suspected of being a weak carcinogen. In some cases, the public may have a better overview on the proceedings than the scientists and risk managers mired in them, realizing perhaps that neither side knows as much as it claims. People Cannot Readily Detect Omissions in the Evidence They Receive Unfortunately, not all problems with information about risk are as readily observable as blatant lies or unreasonable scientific hubris. Often the information that reaches the public is true, but only part of the truth. Detecting such systematic omissions proves to be difficult (Tversky and Kahneman, 1973). For example, most young people know relatively few people suffering from the diseases of old age, nor are they likely to see those maladies cited as the cause of death in newspaper obituaries. As a result,
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Product Liability and Innovation: Managing Risk in an Uncertain Environment young people tend to underestimate the frequency of these causes of death, while most people overestimate the frequency of vividly reported causes, such as murder, accidents, and tornadoes (Lichtenstein et al., 1978). Laypeople are even more vulnerable when they have no way of knowing about information that has not been disseminated. In principle, for example, one could always ask physicians if they have neglected to mention any side effects of the drugs they prescribe. Likewise, people could ask merchants whether there are any special precautions for using a new power tool, just as they could ask proponents of a hazardous facility if their risk assessments have considered all forms of operator error and sabotage. In practice, however, these questions about omissions are rarely asked. It takes an unusual turn of mind and personal presence to recognize one's own ignorance and insist that it be addressed. As a result of this insensitivity to omissions, people's risk perceptions can be manipulated in the short run by selective presentation. Not only will people not know what they have not been told, but they will not even feel how much has been left out (Fischhoff et al., 1978). What happens in the long run depends on whether the unmentioned risks are revealed by experience or by other sources of information. When deliberate omissions are detected, the responsible party is likely to lose all credibility. Once a shadow of doubt has fallen, it is hard to erase. People May Disagree More about What Risk Is Than about How Large It Is Given this mixture of strengths and weaknesses in the psychological processes that generate people's risk perceptions, there is no simple answer to the question, How much do people know and understand? The answer depends on the risks and on the opportunities that people have to learn about them. One obstacle to determining what people know about specific risks is disagreement about the definition of "risk" (Crouch and Wilson, 1981; Fischhoff et al., 1983; Fischhoff et al., 1984; Slovic et al., 1979). The opportunities for disagreement can be seen in the varied definitions used by different risk managers. For some, the natural unit of risk is an increase in probability of death; for others, it is reduced life expectancy; for still others, it is the probability of death per unit of exposure, where "exposure" itself may be variously defined. The choice of definition is often arbitrary, reflecting the way in which a particular group of risk managers habitually collects and analyzes data. The choice, however, is never trivial. Each definition of risk makes a distinct political statement regarding what society should value when it judges the acceptability of risks. For example, "reduced life expectancy"
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Product Liability and Innovation: Managing Risk in an Uncertain Environment puts a premium on deaths among the young, which would be absent in a measure that simply counted the expected number of premature deaths. A measure of risk could also give special weight to individuals who can make a special contribution to society, to individuals who were not consulted (or even born) when a risk-management policy was enacted, or to individuals who do not benefit from the technology generating the risk. If laypeople and risk managers use the term "risk" differently, then they can agree on the facts about a specific technology but still disagree about its degree of riskiness. Some years ago, the idea circulated in the nuclear power industry that the public cared much more about multiple deaths from large accidents than about equivalent numbers of casualties resulting from a series of small accidents. If this assumption were valid, the industry would be strongly motivated to remove the threat of such large accidents. If removing the threat proved impossible, then the industry could argue that a death is a death and that, in formulating social policy, it is totals that matter, not whether deaths occur singly or collectively. There were never any empirical studies to determine whether this was really how the public defined risk. Subsequent studies, though, have suggested that what bothers people about catastrophic accidents is the perception that a technology capable of producing such accidents cannot be very well understood or controlled (Slovic et al., 1984). From an ethical point of view, worrying about the uncertainties surrounding a new and complex technology, such as nuclear power, is different from caring about whether a fixed number of lives is lost in one large accident rather than in many small accidents. People Have Difficulty Detecting Inconsistencies in Risk Disputes Despite their frequent intensity, risk debates are typically conducted at a distance (Krimsky and Plough, 1988; Mazur, 1973; Nelkin, 1978). The disputing parties operate within self-contained communities and talk principally to one another. Opponents are seen primarily through their writing or their posturing at public events. Thus, there is little opportunity for the sort of subtle probing needed to discover basic differences in how the protagonists think about important issues, such as the meaning of key terms or the credibility of expert testimony. As a result, it is easy to misdiagnose one another's beliefs and concerns. The opportunities for misunderstanding increase when the circumstances of the debate restrict candor. For example, some critics of nuclear power actually believe that the technology can be operated with reasonable safety. However, they oppose it because they believe that its costs and benefits are distributed inequitably. Although they might like to discuss these issues, public hearings about risk and safety often provide
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Product Liability and Innovation: Managing Risk in an Uncertain Environment these critics with their only forum for venting their concern. If they oppose the technology, then they are forced to do so on safety grounds, even if this means misrepresenting their perceptions of the actual risk. Although this may be a reasonable strategy for pursuing their ultimate goals, it makes them look unreasonable to observers who hold opposing views of nuclear power. Individuals also have difficulty detecting inconsistencies in their own beliefs or realizing how simple reformulations would change their perspectives on issues. For example, most people would prefer a gamble with a 25 percent chance of losing $200 (and a 75 percent chance of losing nothing) to a sure loss of $50. However, most of the same people would also buy a $50 insurance policy to protect against such a loss. What they will do depends on whether the $50 is described as a "sure loss" or as an "insurance premium." In such cases, one cannot predict how people will respond to an issue without knowing how they will perceive it, which depends, in turn, on how it will be presented to them by merchandisers, politicians, or the media (Fischhoff, 1991; Fischhoff et al., 1980; Turner and Martin, 1984; Tversky and Kahneman, 1981). Thus, people's insensitivity to the nuances of how risk issues are presented exposes them to manipulation. For example, a risk might seem much worse when described in relative terms, such as doubling their risk, than in absolute terms, as in increasing that risk from one in a million to one in a half million. Although both representations of the risk might be honest, their impacts would be quite different. Perhaps the only fair approach is to present the risk from both perspectives, letting recipients determine which one, or hybrid, best represents their world view. Experts Are People, Too Obviously, experts have more substantive knowledge than laypeople. Often, however, the practical demands of risk management force experts to make educated guesses about critical facts, taking them far beyond the limits of their data. In such situations, debates about risk are often conflicts between competing sets of risk perceptions, those of the public and those of the experts. As a result, one must ask how good those expert judgments are. Do experts, like laypeople, tend to exaggerate the extent of their own knowledge? Are experts more sensitive than others to systematic omissions in the evidence that they receive? Do they, too, tend to oversimplify policy issues? Available studies suggest that when experts must rely on judgment, their thought processes often resemble those of laypeople (Fischhoff, 1989; Kahneman et al., 1982; Mahoney, 1979; Shlyakhter et al., 1994). For example, Figure 1 displays two cases of overconfidence in the judgments of senior
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Product Liability and Innovation: Managing Risk in an Uncertain Environment improves when text has a clear structure and, especially, when that structure conforms to recipients' intuitive representations; that critical information is more likely to be remembered when it appears at the highest level of a clear hierarchy; and that readers benefit from "adjunct aids," such as highlighting, previews (showing what to expect), and summaries. Such aids can even be better than full text for understanding, retaining, and being able to look up information (e.g., Ericsson, 1988; Garnham, 1987; Kintsch, 1986; Reder, 1985; Schriver, 1989). As suggested by the research reviewed earlier, information about the magnitude of risks poses some particular challenges to communicators. The units, orders of magnitude, and even the very idea of quantitative risk estimates may be foreign to many recipients. Under those circumstances, it may seem appealing to provide no more than a general indication of risk levels. However, that situation may also produce the greatest variability in the magnitudes attributed to such verbal quantifiers. The very fact that risks are mentioned may suggest that they are relatively severe, even though that act reflects no more than the caution of a particular producer or the idiosyncrasies of a particular legislative or regulatory process (which mandated labeling). Although there may be no substitute for providing explicit quantitative information, there is also no guaranteed way to do it effectively. For the time being, we must resign ourselves to an imperfect process in which producers gradually learn how to communicate and users gradually learn how to understand. Fortunately, many decisions are relatively insensitive to the precision of perceived risk estimates (von Winterfeldt and Edwards, 1986). As a result, imperfect communication may still allow people to identify the courses of action in their own best interests. Recipients can always choose to ignore quantitative information or to convert it to some intuitive qualitative equivalent (Beyth-Marom, 1982; Wallsten et al., 1986). In the domain of weather forecasting, studies have found that people appreciate the quantitative information in probability of precipitation forecasts, although they are sometimes unsure about exactly what event is being forecast (Krzysztofowicz, 1983; Murphy and Brown, 1983; Murphy et al., 1980). Intuitively recognizing the difficulty that people may have with understanding small risks, technical experts have often sought to provide perspective by embedding a focal risk in a list of equivalent risks. Those lists might show the doses of a variety of activities that produce one chance in a million of premature death, for example, hours of canoeing, teaspoonfuls of peanut butter, years living near the boundary of a nuclear power plant, or the loss of life expectancy from various states and activities (Cohen and Lee, 1979; Wilson, 1979). Assuming that recipients had accurate feelings for the likelihood of some of the items in the list, this strategy might be useful.
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Product Liability and Innovation: Managing Risk in an Uncertain Environment Unfortunately, risk comparisons are often formulated with transparently rhetorical purpose, attempting to encourage recipients' acceptance of the focal risk—"if you like peanut butter, and accept its risks from aflatoxin, then you should love nuclear power." By failing to consider the other factors entering into others' decisions, for example, the respective benefits from peanut butter and nuclear power, such comparisons have no logical force (Fischhoff et al., 1981; Fischhoff et al., 1984). They can, however, alienate recipients, who prefer to make their own decisions. To date, there is no clear demonstration of risk comparisons being an effective communication technique (Covello et al., 1988; Roth et al., 1990). Improving the Usage of Existing Products Telling people about residual risks is, in effect, an admission of engineering failure. It says, "this is the best that we could do, see if you want to live with it." To some extent, that failure may be inevitable. Engineers cannot do it all, and must rely on responsible use of their products. Indeed, in many situations, the product user is in the best position to assess and minimize the risks. However, to fulfill their obligation, engineers must provide users with the information that they need for successful operation. Providing estimates of the magnitude of potential risks (discussed in the previous section) is a part of that story, insofar as it helps users decide how seriously to take safety issues. Additional steps range from general warnings ("poisonous"), to specific warnings ("use in a well-ventilated area"), to detailed instructions, to training courses of various length. The challenge in designing such materials and procedures is to achieve an acceptable level of understanding at minimal cost in time, money, and effort to producer and user. The required understanding might be defined as whatever is needed to achieve that announced safety level, assuming responsible use. Training is a heavily studied topic, another beneficiary of the demands of World War II and the Cold War. A producer who did not exploit its potential would arguably bear some responsibility for whatever misfortunes followed. However, it could not be expected to eliminate all risks. Many modern products are so complex and used in such diverse circumstances that it is impossible to anticipate all contingencies or to train users to the desired proficiency. One response to this reality has been to shift the focus of training from what to do to what is happening. It attempts to provide users with accurate mental models of how the product works, so that they can anticipate the results of their actions and diagnose potentially problematic circumstances. Doing so requires a user-centered, rather than a product-centered approach. It might be advantageous also in situations
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Product Liability and Innovation: Managing Risk in an Uncertain Environment that less obviously strain the limits of traditional training (Laughery, 1993; Norman, 1988; Reason, 1990). The state of the art for written instructions seems rather more primitive. As with informing users about the magnitude of risks, the selection and organization of operational information often seem somewhat arbitrary. To take an example that we have studied intensively, the U.S. Environmental Protection Agency (EPA) invested heavily in the development, evaluation, and dissemination of a Citizen's Guide to Radon. Yet, despite this laudably broad and deep effort, the resulting brochure uses a question-and-answer format, with little attempt to summarize or impose a general structure. It relies on an untested risk-comparison scale, which, for example, uses relatively similar risks, but presents them on a logarithmic scale. It does not explicitly confront a misconception that could undermine the value of other correct beliefs about radon: because radon is radioactive, it can contaminate permanently, making it infeasible to remediate should a problem be found (hence not even worth testing). That misconception was identified in a series of open-ended interviews intended to characterize laypeople's mental models of this risk and confirmed in studies using structured questionnaires (Bostrom, 1990; Bostrom et al., 1992). This set of procedures was used to examine lay understanding of a variety of risks, including those from electromagnetic fields, Lyme disease, lead poisoning, and nuclear energy sources in space (Fischhoff et al., 1993; Morgan et al., 1992). Leventhal and his colleagues have used similar approaches in studying adherence to medical regimes such as routine screening, hypertension drugs, and diets (Leventhal and Cameron, 1987). Yet other investigators have looked at lay conceptualizations of such diverse processes as macroeconomics, physics, computers, and climate change (Carroll and Olson, 1988; Chi et al., 1981; Jungermann et al., 1988; Kempton, 1991; MacGregor, 1989; Voss et al., 1983). Typically, these studies find a mixture of accurate beliefs, on which instructions can build; misconceptions, which need to be eliminated; peripheral beliefs, which need to be placed in proper perspective; and vague beliefs, which need to be sharpened before they can be used, or judged for accuracy. Such procedures provide one of the only ways of identifying beliefs that would not have occurred to technical experts. Open-ended procedures also provide one of the few ways of identifying discrepancies in how terms are used by people from different linguistic communities. Consider, for example, the common, simple warning, "Don't drink and drive." Recipients could hear, but not get, the message if they guessed wrong about what was meant in terms of the kind and amount of "drinking" and "driving,'' not to mention any special pleading as far as how the general message applied to them personally (Svenson, 1981). Quadrel (1990) asked adolescents to estimate risks using deliberately
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Product Liability and Innovation: Managing Risk in an Uncertain Environment vague questions, such as, "What is the probability of getting into an accident if you drink and drive?" She found that even teens with poor education were quite sensitive to imprecisions in how risks were described. There was also considerable variability in how her subjects "filled in the blanks," in the sense of supplying missing details. As a result, they ended up answering different questions even when looking at the same words. As mentioned, earlier studies found that the disagreements between experts and laypeople about the magnitude of risks are due, in part, to disagreements about the definition of "risk" (Slovic et al., 1979; Vlek and Stallen, 1980). Effective risk communications can help people to reduce their health risks or to get greater benefits in return for those risks that they do take. Ineffective communications not only fail to do so but also incur opportunity costs, in the sense of occupying the place (in recipients' lives and society's functions) that could be taken up by more effective communications. Even worse, misdirected communications can prompt wrong decisions by omitting key information or failing to contradict misconceptions, create confusion by prompting inappropriate assumptions or by emphasizing irrelevant information, and provoke conflict by eroding recipients' faith in the communicator. By causing undue alarm or complacency, poor communications can have greater public health impact than the risks that they attempt to describe. It may be no more acceptable to release an untested communication than an untested drug. Because communicators' intuitions about recipients' risk perceptions cannot be trusted, there is no substitute for empirical validation (Fischhoff, 1987; Fischhoff et al., 1983; National Research Council, 1989; Rohrmann, 1990; Slovic, 1987). Failing to develop and test messages systematically raises legal, ethical, and management questions. Improving Product Design Instructing users in how to avoid potential problems leads, in effect, to teaching them how to make the best of an imperfect situation. A more satisfying response is designing user problems away. That means treating users as a resource, rather than as a source of difficulties. Understanding their problems might mean gaining market share, as well as avoiding litigation. Even an explicit commitment to safety and operability can mean something in the marketplace. Delivering on that commitment could be worth even more. Industries, companies, and even divisions differ greatly in their commitment to the human factors engineering needed to achieve operability. For example, on the same plane, one might find fancy cockpit displays, clumsy tray tables, and metal coffee pots that induce carpal tunnel syndrome.
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Product Liability and Innovation: Managing Risk in an Uncertain Environment Inattention to these issues may reflect disinterest in the users (pilots may matter more than flight attendants) or simply the pecking order in design departments. An examination of the skills appearing in a firm's organizational chart provides one indication of how seriously it takes human factors, and of how well it is positioned to exploit the opportunities. A second indicator of a firm's ability to improve its design is its reluctance to attribute mishaps to human (or user or operator) error. The demands of product liability suits may force a firm to make and defend such claims. However, making improvements requires sharing responsibility. The sort of user-centered, or mental-models, procedure described earlier provides one place to start that process. It means trying to bring designs closer to users' expectations, rather than vice versa (as discussed in the previous section). One common source of discouragement is sometimes called the theory of "risk homeostasis" (Wilde, 1982). It holds that users frustrate safety improvements by finding ways to use products more aggressively. The evidence supporting this hypothesis is mixed (Slovic and Fischhoff, 1983). Were it true, it might suggest that users are so irrational that there is no point in trying to improve safety. An alternative interpretation would be that users are responding rationally, trying to get more benefit from a product, at the price of forfeiting the increase in safety. If users understand the risks and benefits involved, then they have, arguably, given informed consent for whatever happens. Their desire for greater benefit suggests a design opportunity: providing that benefit without sacrificing safety. CONCLUSION The suggestions in the preceding sections dealt with strategies that are within the control of a product's manufacturer. They are, in effect, proposals for improved product stewardship. How effective each proposal is depends, in part, on how skillfully it is implemented and, in part, on how good it conceivably could be. The limits to performance depend, in turn, partly on the strategy. A warning label cannot do as much as a user-centered redesign, although it may be the most cost-effective response. Those limits also depend on the environment and how it rewards or punishes different strategies. For example, there is no incentive to sweat the details of message design if presenting a laundry list of potential problems is construed as ensuring informed consent. There is a disincentive for doing so if changing how risks are described can be construed as admitting the inadequacy of previous descriptions, which may be in litigation. There may be a disincentive for creating safer designs if that, too, can be construed as an admission of previous failure, or if stricter demands are made of new products. Firms may be penalized for rigorous testing if they
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Product Liability and Innovation: Managing Risk in an Uncertain Environment can later be accused of releasing products with imperfections that they themselves have documented. In addition to removing such obstacles to considering behavioral issues, incentives are needed to take them seriously. Generally speaking, firms should get credit for vigorously studying the behavior of potential users, for having behavioral specialists involved throughout the design process, for evaluating the residual risks of their products, for communicating both the extent and the sources of those risks to users, and for measuring how successfully those messages have gotten across. NOTES 1. The FDA licensing process is laid out in 21 Code of Federal Regulations, Parts 310, 312, and 314 (1993). Manufacturing requirements are set forth in Parts 210-211. Post-marketing reporting requirements and Food and Drug Administration withdrawal of approval are in §310.305 and §314.150, respectively. Similar requirements for premarket testing of chemical substances may be imposed by the Environmental Protection Agency under the Toxic Substances Control Act, 15 U.S.C. §§ 2601-71 (1982 and Suppl. 1992). See generally (Hanan, 1992). 2. In the case of prescription drugs, as post-marketing information accumulates, a drug will either remain a prescription drug, be released as an over-the-counter drug if safe enough, or pulled from the market if found to be more dangerous than initially believed. The idea behind the drug licensing scheme is to manage the uncertainty inherent in drug design and clinical trials both to ensure that efficacious drugs are supplied in a timely manner to sick people and to minimize the likelihood that there are unacceptable undiscovered risks of drug use. 3. A classic example (Fitts and Posner, 1967) involves two versions of a World War II aircraft, differing solely in the functions assigned to three key operating levers. Although aviators were instructed in the differences, they sometimes "forgot" under the strain of operations, acting as though they were flying a previously learned configuration. Lacking the influence needed to change the physical design of the aircraft, the human factors engineers compensated by placing tactually distinctive knobs on the levers. REFERENCES Aftermath of Chernobyl. 1986. Groundswell 9:1–7. American Law Institute. 1965. Restatement (Second) of the Law of Torts. Baum, A., R. Gatchel, and M. Schaeffer. 1983. Emotional, behavioral and physiological effects of chronic stress at Three Mile Island. Journal of Consulting and Clinical Psychology 12:349–359. Berendes, H. W., and Y. J. Lee. 1993. Suspended judgment: The 1953 clinical trial of diethylstilbestrol during pregnancy: Could it have stopped DES use? Controlled Clinical Trials 14:179–182. Beyth-Marom, R. 1982. How probable is probable? Journal of Forecasting 1:257–269. Bostrom, A. 1990. A Mental Models Approach to Exploring Perceptions of Hazardous Processes. Ph.D. dissertation. School of Urban and Public Affairs, Carnegie Mellon University. Bostrom, A., B. Fischhoff, and M. G. Morgan. 1992. Characterizing mental models of hazardous
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Representative terms from entire chapter: