The affect heuristic

The affect heuristic refers to the way in which subjective impressions of "goodness" or "badness" can act as a heuristic, capable of producing fast perceptual judgments, and also systematic biases.

In Slovic et. al. (2002), two groups of subjects evaluated a scenario in which an airport must decide whether to spend money to purchase new equipment, while critics argue money should be spent on other aspects of airport safety. The response scale ranged from 0 (would not support at all) to 20 (very strong support). A measure that was described as "Saving 150 lives" had mean support of 10.4 while a measure that was described as "Saving 98% of 150 lives" had mean support of 13.6. Even "Saving 85% of 150 lives" had higher support than simply "Saving 150 lives." The hypothesis motivating the experiment was that saving 150 lives sounds diffusely good and is therefore only weakly evaluable, while saving 98% of something is clearly very good because it is so close to the upper bound on the percentage scale.

Finucane et. al. (2000) wondered if people conflated their assessments of the possible benefits of a technology such as nuclear power, and their assessment of possible risks, into an overall good or bad feeling about the technology. Finucane et. al. tested this hypothesis by providing four kinds of information that would increase or decrease perceived risk or perceived benefit. There was no logical relation between the information provided (e.g. about risks) and the nonmanipulated variable (e.g. benefits). In each case, the manipulated information produced an inverse effect on the affectively inverse characteristic. Providing information that increased perception of risk, decreased perception of benefit. Providing information that decreased perception of benefit, increased perception of risk. Finucane et. al. (2000) also found that time pressure greatly increased the inverse relationship between perceived risk and perceived benefit

- presumably because time pressure increased the dominance of the affect heuristic over analytic reasoning.

Ganzach (2001) found the same effect in the realm of finance: analysts seemed to base their judgments of risk and return for unfamiliar stocks upon a global affective attitude. Stocks perceived as "good" were judged to have low risks and high return; stocks perceived as "bad" were judged to have low return and high risks. That is, for unfamiliar stocks, perceived risk and perceived return were negatively correlated, as predicted by the affect heuristic. (Note that in this experiment, sparse information played the same role as cognitive busyness or time pressure in increasing reliance on the affect heuristic.) For familiar stocks, perceived risk and perceived return were positively correlated; riskier stocks were expected to produce higher returns, as predicted by ordinary economic theory. (If a stock is safe, buyers pay a premium for its safety and it becomes more expensive, driving down the expected return.)

People typically have sparse information in considering future technologies. Thus it is not surprising that their attitudes should exhibit affective polarization. When I first began to think about such matters, I rated biotechnology as having relatively smaller benefits compared to nanotechnology, and I worried more about an engineered supervirus than about misuse of nanotechnology. Artificial Intelligence, from which I expected the largest benefits of all, gave me not the least anxiety. Later, after working through the problems in much greater detail, my assessment of relative benefit remained much the same, but my worries had inverted: the more powerful technologies, with greater anticipated benefits, now appeared to have correspondingly more difficult risks. In retrospect this is what one would expect. But analysts with scanty information may rate technologies affectively, so that information about perceived benefit seems to mitigate the force of perceived risk.

Continue reading here: Scope neglect

Was this article helpful?

0 0