Risk Perception

cultural theory of risk

Risk perception is the subjective judgment that people make about the characteristics and severity of a risk. The phrase is most commonly used in reference to natural hazards and threats to the environment or health, such as nuclear power. Several theories have been proposed to explain why different people make different estimates of the dangerousness of risks. Three major families of theory have been developed: psychology approaches (heuristics and cognitive), anthropology/sociology approaches (cultural theory) and interdisciplinary approaches (social amplification of risk framework).

The study of risk perception arose out of the observation that experts and lay people often disagreed about how risky various technologies and natural hazards were. The mid 1960s saw the rapid rise of nuclear technologies and the promise for clean and safe energy. However, fears of both longitudinal dangers to the environment as well as immediate disasters creating radioactive wastelands turned the public against this new technology. The governmental communities asked why public perception was against the use of nuclear energy when all of the scientific experts were declaring how safe it really was. The problem, from the perspectives of the experts, was a difference between scientific facts and an exaggerated public perception of the dangers.

A key early paper was written in 1969 by American electrical engineer and nuclear energy expert Chauncey Starr, who used a revealed preference approach (a statistical tool used in consumer marketing) to find out what risks are considered acceptable by society. He assumed that society had reached equilibrium in its judgment of risks, so whatever risk levels actually existed in society were acceptable. His major finding was that people will accept risks 1,000 greater if they are voluntary (e.g. driving a car) than if they are involuntary (e.g. a nuclear disaster). This early approach assumed that individuals behave in a rational manner, weighing information before making a decision, and that exaggerated fears are due to inadequate or incorrect information. Implied in this assumption is that additional information can help people understand true risk and hence lessen their opinion of danger. While researchers in the engineering school did pioneer research in risk perception, by adapting theories from economics, it has little use in a practical setting. Numerous studies have rejected the belief that additional information, alone, will shift perceptions.

The psychological investigation of risk perception began by trying to understand how people process information. Early research indicated that people use cognitive heuristics (mental shortcuts and rules of thumb) in sorting and simplifying information which lead to biases in comprehension. Later work built on this foundation and became the psychometric paradigm. This approach identifies numerous factors responsible for influencing individual perceptions of risk, including dread, newness, stigma, and other factors. Another school of thought emerging from the early work is valence theory, proposing that that emotions are grouped as either positive, such as happy and hopeful, or negative, such as fear and anger. Overly optimistic risk perceptions are attributed positive emotions while negative emotions are assumed to influence a more pessimistic view of risk.

The earliest psychometric research was done by psychologists Daniel Kahneman and Amos Tversky, who performed a series of gambling experiments to see how people evaluated probabilities. Their major finding was that people use a number of heuristics to evaluate information. These heuristics are usually useful tools for quick thinking, but they may lead to inaccurate judgments in some situations – in which case they become cognitive biases. Heuristics include Representativeness, which Tversky and Kahneman defined as ‘the degree to which [an event] (i) is similar in essential characteristics to its parent population, and (ii) reflects the salient features of the process by which it is generated.’ When people rely on representativeness to make judgments, they are likely to judge wrongly because the fact that something is more representative does not make it more likely. Another common mental shortcut is the Availability heuristic: events that can be more easily brought to mind or imagined are judged to be more likely than events that could not easily be imagined.

Another issue exposed by Kahneman and Tversky is Asymmetry between gains and losses: people are risk averse with respect to gains, preferring a sure thing over a gamble with a higher expected utility but which presents the possibility of getting nothing. On the other hand, people will be risk-seeking about losses, preferring to hope for the chance of losing nothing rather than taking a sure, but smaller, loss (e.g. insurance). Also discussed are Threshold effects: People prefer to move from uncertainty to certainty over making a similar gain in certainty that does not lead to full certainty. For example, most people would choose a vaccine that reduces the incidence of disease A from 10% to 0% over one that reduces the incidence of disease B from 20% to 10%. Another key finding was that the experts are not necessarily any better at estimating probabilities than lay people. Experts were often overconfident in the exactness of their estimates, and put too much stock in small samples of data.

The general public typically expresses a greater concern for problems which appear to possess an immediate effect on everyday life such as hazardous waste or pesticide-use than for long-term problems that may affect future generations such as climate change or population growth. People greatly rely on the scientific community to assess the threat of environmental problems because they usually do not directly experience the effects of phenomena such as climate change. The exposure most people have to climate change has been impersonal; most people only have virtual experience though documentaries and news media in what may seem like a ‘remote’ area of the world. However, coupled with the population’s wait-and-see attitude, people do not understand the importance of changing environmentally destructive behaviors even when experts provide detailed and clear risks caused by climate change.

Research within the psychometric paradigm turned to focus on the roles of affect, emotion, and stigma in influencing risk perception. Melissa Finucane and Paul Slovic have been among the key researchers here. They first challenged Starr’s article by examining expressed preference – how much risk people say they are willing to accept. They found that, contrary to Starr’s basic assumption, people generally saw most risks in society as being unacceptably high. They also found that the gap between voluntary and involuntary risks was not nearly as great as Starr claimed.

Slovic and team found that perceived risk is quantifiable and predictable. People tend to view current risk levels as unacceptably high for most activities. All things being equal, the greater people perceived a benefit, the greater the tolerance for a risk. If a person derived pleasure from using a product, people tended to judge its benefits as high and its risks as low. If the activity was disliked, the judgments were opposite. Research in psychometrics has proven that risk perception is highly dependent on intuition, experiential thinking, and emotions. Psychometric research identified a broad domain of characteristics that may be condensed into three high order factors: 1) the degree to which a risk is understood, 2) the degree to which it evokes a feeling of dread, and 3) the number of people exposed to the risk. A dread risk elicits visceral feelings of terror, uncontrollable, catastrophe, inequality, and uncontrolled. An unknown risk is new and unknown to science. The more a person dreads an activity, the higher its perceived risk and the more that person wants the risk reduced.

In order to better address and understand the risk of complex environmental problems such as climate change, new interdisciplinary models of risk perception have been developed in recent years. For example, Helgeson, van der Linden and Chabay (2012) present a five factor model, where public risk perceptions of climate change are considered to be multidimensional, resulting from a combination of (1) cognitive, (2) emotional, (3) subconscious, (4) socio-cultural, and (5) individual factors. The model integrates insights from behavioral economics, cognitive psychology, cultural anthropology, the psychometric paradigm as well as the heuristics and biases approach.

The anthropology/sociology approach posits risk perceptions as produced by and supporting social institutions. In this view, perceptions are socially constructed by institutions, cultural values, and ways of life. Cultural Theory is based on the work of anthropologist Mary Douglas and political scientist Aaron Wildavsky first published in 1982. They outlined four ‘ways of life’ (Hierarchical, Individualist, Egalitarian, and Fatalist) in a grid/group arrangement. Each corresponds to a specific social structure and a particular outlook on risk. ‘Grid’ categorizes the degree to which people are constrained and circumscribed in their social role. The tighter binding of social constraints limits individual negotiation. ‘Group’ refers to the extent to which individuals are bounded by feelings of belonging or solidarity. The greater the bonds, the less individual choice are subject to personal control. Risk perception researchers have not widely accepted Cultural theory. Even Douglas says that the theory is controversial; it poses a danger of moving out of the favored paradigm of individual rational choice of which many researchers are comfortable.

The Social Amplification of Risk Framework (SARF), combines research in psychology, sociology, anthropology, and communications theory. It outlines how communications of risk events pass from the sender through intermediate stations to a receiver and in the process serve to amplify or attenuate perceptions of risk. All links in the communication chain, individuals, groups, media, etc., contain filters through which information is sorted and understood. The framework attempts to explain the process by which risks are amplified, receiving public attention, or attenuated, receiving less public attention. It may be used to compare responses from different groups in a single event, or analyze the same risk issue in multiple events. In a single risk event, some groups may amplify their perception of risks while other groups may attenuate, or decrease, their perceptions of risk.

The main thesis of SARF states that risk events interact with individual psychological, social and other cultural factors in ways that either increase or decrease public perceptions of risk. Behaviors of individuals and groups then generate secondary social or economic impacts while also increasing or decreasing the physical risk itself. These ripple effects caused by the amplification of risk include enduring mental perceptions, impacts on business sales, and change in residential property values, changes in training and education, or social disorder. These secondary changes are perceived and reacted to by individuals and groups resulting in third-order impacts. As each higher-order impacts are reacted to, they may ripple to other parties and locations. Traditional risk analyses neglect these ripple effect impacts and thus greatly underestimate the adverse effects from certain risk events. Public distortion of risk signals provides a corrective mechanism by which society assesses a fuller determination of the risk and its impacts to such things not traditionally factored into a risk analysis.

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