Vincent Gable’s Blog

Bruce Schneier has a new essay, How to Sell Security. As usual, it’s well worth reading.

The most interesting tidbit, to me, is that people have a bias to choose a small certain gain over an uncertain but possibly larger gain. But with loss, it’s the opposite. People avoid certain losses; preferring to “play double or nothing” — risking a larger loss for the chance of not sustaining a loss.

Here’s an experiment that illustrates Prospect Theory. Take a roomful of subjects and divide them into two groups. Ask one group to choose between these two alternatives: a sure gain of $500 and 50 percent chance of gaining $1,000. Ask the other group to choose between these two alternatives: a sure loss of $500 and a 50 percent chance of losing $1,000.

These two trade-offs are very similar, and traditional economics predicts that the whether you’re contemplating a gain or a loss doesn’t make a difference: People make trade-offs based on a straightforward calculation of the relative outcome. Some people prefer sure things and others prefer to take chances. Whether the outcome is a gain or a loss doesn’t affect the mathematics and therefore shouldn’t affect the results. This is traditional economics, and it’s called Utility Theory.

But Kahneman’s and Tversky’s experiments contradicted Utility Theory. When faced with a gain, about 85 percent of people chose the sure smaller gain over the risky larger gain. But when faced with a loss, about 70 percent chose the risky larger loss over the sure smaller loss.

This experiment, repeated again and again by many researchers, across ages, genders, cultures and even species, rocked economics, yielded the same result. Directly contradicting the traditional idea of “economic man,” Prospect Theory recognizes that people have subjective values for gains and losses. We have evolved a cognitive bias: a pair of heuristics. One, a sure gain is better than a chance at a greater gain, or “A bird in the hand is worth two in the bush.” And two, a sure loss is worse than a chance at a greater loss, or “Run away and live to fight another day.” Of course, these are not rigid rules. Only a fool would take a sure $100 over a 50 percent chance at $1,000,000. But all things being equal, we tend to be risk-adverse when it comes to gains and risk-seeking when it comes to losses.

This cognitive bias is so powerful that it can lead to logically inconsistent results. Google the “Asian Disease Experiment” for an almost surreal example. Describing the same policy choice in different ways–either as “200 lives saved out of 600” or “400 lives lost out of 600”– yields wildly different risk reactions.

Evolutionarily, the bias makes sense. It’s a better survival strategy to accept small gains rather than risk them for larger ones, and to risk larger losses rather than accept smaller losses. Lions, for example, chase young or wounded wildebeests because the investment needed to kill them is lower. Mature and healthy prey would probably be more nutritious, but there’s a risk of missing lunch entirely if it gets away. And a small meal will tide the lion over until another day. Getting through today is more important than the possibility of having food tomorrow. Similarly, it is better to risk a larger loss than to accept a smaller loss. Because animals tend to live on the razor’s edge between starvation and reproduction, any loss of food — whether small or large — can be equally bad. Because both can result in death, and the best option is to risk everything for the chance at no loss at all.