Time has a short article describing the work of risk assessment expert John Adams.
The point, stresses Adams, is that drivers who feel safe may actually increase the risk that they pose to other drivers, bicyclists, pedestrians and their own passengers (while an average of 80% of drivers buckle up, only 68% of their rear-seat passengers do). And risk compensation is hardly confined to the act of driving a car. Think of a trapeze artist, suggests Adams, or a rock climber, motorcyclist or college kid on a hot date. Add some safety equipment to the equation -- a net, rope, helmet or a condom respectively -- and the person may try maneuvers that he or she would otherwise consider foolish. In the case of seat belts, instead of a simple, straightforward reduction in deaths, the end result is actually a more complicated redistribution of risk and fatalities. For the sake of argument, offers Adams, imagine how it might affect the behavior of drivers if a sharp stake were mounted in the middle of the steering wheel? Or if the bumper were packed with explosives. Perverse, yes, but it certainly provides a vivid example of how a perception of risk could modify behavior.
Adams makes two points:
(1) People who will tolerate a given level of risk will respond to an objective reduction in risk by doing riskier things. (Elsewhere, Adams calls this idea the "risk thermostat" model.)
(2) Risk is interactive and unequally distributed, so that decreasing the risks for one category of individuals may increase it for others.
Car accidents make pretty good illustrations for both. Some people who drive large SUVs feel a greater safety margin and therefore drive more aggressively. Providing these people with a "safer" driving platform tends to increase the risks for drivers of smaller cars. If these effects were strong enough, putting a "safer" class of vehicle on the road would actually increase the overall number of fatalities.
A web search for Adams' work brings up a technical report written for the Cato Institute, discussing risk perception in more detail. After a review of the effect of seat belt laws, he embarks on a discussion of risks identified through science. These kinds of risks are not directly accessible to the senses, and their magnitude can be appreciated only by studying large populations of things. The long-term risk of smoking is one example.
Before discussing these kinds of risks, Adams considers our attitudes toward risks that are accessible to the senses:
Directly perceptible risks are "managed" instinctively; our ability to cope with them has been built into us by evolution--contemplation of animal behavior suggests that it has evolved in nonhuman species as well. Our method of coping is also intuitive; we do not do a formal probabilistic risk assessment before we cross the street. There is now abundant evidence, particularly with respect to directly perceived risks on the road, that risk compensation accompanies the introduction of safety measures that do not reduce people's propensity to take risks. Statistics for death by accident and violence, perhaps the best available aggregate indicator of the way in which societies cope with directly perceived risk, display a stubborn resistance, over many decades, to the efforts of safety regulators to reduce them (Adams 1999:10).
Adams notes that much of the decrease in premature mortality during the past 150 years has been brought about by better understanding and communicating about invisible risks. The germ theory of disease is probably the most notable example.
But he points out the difficulty of measuring reductions in risk. At least, we can measure overall mortality rates -- if they decline after an intervention, then presumably it was effective. But activity-specific mortality rates won't do:
Moreover, risks can be displaced. If motorcycling were to be banned in Britain it would save about 500 lives a year. Or would it? If it could be assumed that all the banned motorcyclists would sit at home drinking tea, one could simply subtract motorcycle accident fatalities from the total annual road accident death toll. But at least some frustrated motorcyclists would buy old clunkers and try to drive them in a way that pumped as much adrenaline as their motorcycling did, and in a way likely to produce more kinetic energy to be dispersed if they crashed. The alternative risk-taking activities that they might pursue range from skydiving to glue sniffing, and there is no set of statistics that could prove that the country had been made safer, or more dangerous, by the ban (Adams 1999:20).
Now, I'm reading this because I'm evaluating strategies toward risk in human evolution. Mortality reductions are a major trend in the emergence of modern humans. That would tend to indicate an objective decrease in risks of various kinds.
But a decrease in mortality risk may not translate to an increase in fitness. For instance, if more adult males survive to older ages, they may prevent younger males from reproducing until they are older. If this happened, a reduction in mortality would impose a tradeoff of a reduction in fecundity for younger individuals. This tradeoff would not prevent the change, by any means -- in the transient after the appearance of a risk-reducing strategy, males who adopted the strategy would immediately have a fitness benefit. But the tradeoff itself might obscure the reasons for the change, or even suggest wrong hypotheses (for instance, the hypothesis that low fecundity for young males forced them to reduce their mortality risk).
Anyway, if professional statisticians are so bad at evaluating the risk landscape, evolutionary biologists are no better. Many evolutionary hypotheses deal explicitly in risks -- with increases in some risks being explained by declines in others. But if you have ever seen an attempt to quantify those risks in terms of fitness, you probably understand how shaky the foundations of such hypotheses can be.
This is the beginning of a multipart series on evolution and risk. There will be some math involved -- calculus, even! -- but at the end something very important will emerge. Risk is the hinge connecting the evolution of human life histories to the evolution of the human brain.