Representativeness, or learning too much from the given information, appears to be per- vasive in its influence on learning and decision making. Nonetheless, people do not always jump to conclusions. In fact, Ward Edwards conducted a series of experiments in the 1960s that found what he termed conservatism. If representativeness is learning too fast, con- servatism can be thought of as learning too slowly. He conducted a series of experiments that look very similar to the later work of David Grether except that there were hundreds of balls in each container and still only a small number of draws. In his experiments hefinds that the base rate, or prior information about which ball is drawn, receives more weight than would be implied by Bayes’ rule. Thus, the subjects stick to their initial beliefs regardless of the information presented. What accounts for the difference?
The work of Robin Hogarth and Hillel Einhorn has tried to answer exactly this question by presenting participants various types and series of information to see how it influences beliefs. When the information is less complicated and easier to understand, people seem to update their beliefs too quickly, displaying a recency effect. Recency is consistent with the representativeness heuristic. When the information is very complicated and requires real cognitive effort to discern, they found that initial beliefs persist—a primacy effect. Primacy is consistent with Edwards’s conservatism. Thus, in Edwards’s experiment, it may be that drawing a small number of balls from distributions with hundreds of balls provides information that is too difficult to process, leading to conservatism. The implication is that simple messages are much more likely to change people’s minds. A well-reasoned, though complex, argument might not have a chance to succeed. corresponding number. Half of the participants were allowed to choose their ticket, and the other half were assigned tickets. On the day of the drawing, participants were approached by one of the experimenters and asked how much they would be willing to sell their ticket for. Those who were assigned the ticket were willing to sell for about $1.96, but those who had chosen would not part with the ticket unless given $8.67. This and similar experiments have shown that people believe that they might somehow control random events. For example, the illusion of control leads people to throw dice harder when they want to roll higher numbers when playing craps. Further, people are willing to bet more on the unknown outcome of a random event when they are told the event will happen in the future than when they are told it happened in the past. In many cases, people might convince themselves that they have the ability to influence things that are well beyond their own control.
EXAMPLE 7.9 Diseases and Accidental Death
Among the decisions most closely associated with risk and risk perceptions are the precautions we take to prolong our lives. There are many different ways one might die and many different actions we might take to prevent each particular mode of death. For example, one who has a family history of stroke could alter one’s diet to reduce the possibility of a stroke. Which actions are worth taking depends heavily on how likely we believe a particular mode of death is. For example, the overwhelming majority (around
80 percent) feel that accidental death (e.g., car accident, accidental fall) is much more likely than death by stroke. This should lead people to worry more about their driving habits or their proximity to cliffs than they would about diet. However, in truth, you are about twice as likely to die from a stroke as you are from all accidental sources combined. In fact you are more than 15 times more likely to die from some disease than you are to die from some accident. Only 57 percent believe that death by disease is more likely than death by accident. About 70 percent believe that there are more victims of homi- cide than suicide. In actuality there are close to 1.5 suicides for every homicide.
Although there are many potential explanations for why people might so poorly predict the possible sources of death, Sarah Lichtenstein and a team of researchers propose that news coverage may be partially to blame. They compared the amount of newspaper coverage for 41 various causes of death to the estimates of 61 participants of the prevalence of the various causes, and they found a very high correlation. Participants believed that causes like homicide, which are covered much more frequently by the press than stroke, were much more prevalent. Importantly, the newspaper coverage was not very related to actual prevalence of the various causes of death.
Consistent with representativeness, Lichtenstein also found evidence that people ignore base rates in their data. For example, participants felt that death due to smallpox was much more likely than death due to complications arising from smallpox vaccination. In fact, partially owing to smallpox vaccinations, cases of smallpox are very rare and thus death by smallpox is very rare. Alternatively, nearly all school-age children have been vaccinated for smallpox. Although the probability death from being vaccinated for smallpox is very small, the sheer number of vaccinations leads to a much higher prev- alence of death by vaccination than death by the disease itself.
EXAMPLE 7.10 Begins with R
If we were to take a Standard English dictionary and tabulate the number of words
contained therein, do you believe we wouldfind more words that begin with the letter R
or that have R in the third position? Amos Tversky and Daniel Kahneman asked 152 participants this question, as well as identical questions for the letters K, L, N, and V. If you were to write down as many words as you know that begin with the letter R, you would likelyfill the list rather easily. This is because we tend to classify words by their first letter. We often list words alphabetically. Further, these words would all have the same initial sound. Alternatively, if you were asked to construct a list of all the words you knew that had R as the third letter, the list would likely be considerably shorter. We tend not to classify words with the same third letter together. This is an unfamiliar task and so we might fail to produce much of a list. In fact, English has more words that have R in the third letter than in thefirst. For example, in this paragraph so far, 16 words have R in the third letter, but only one begins with R. Participants believed that words beginning with the letter R would be about twice as numerous as those with R as the third letter. Similar results were achieved for each of the other letters, though each appears more often as a third letter than as afirst letter.