For this, the ninth nomination in the Top Ten Psychology Studies, it’s Nobel Prize-winning research. Daniel Kahneman and Amos Tversky were interested in the apparently strange way in which people make decisions in risky situations.

One example is: would you bet £10 on the flip of a coin if you stood to win £20? So you’ve got a 50% chance of losing £10 and a 50% chance of winning £20. This seems like a good bet to take and yet studies show that people tend not to take it. Why?

Changes in wealth

Before Kahneman and Tversky (1979) published their ground-breaking research, risky decisions were usually analysed by thinking about the total wealth involved. When you look at this bet in the context of the total wealth it makes sense to gamble. It’s obvious you’ve got more to gain than you have to lose. So, why do people tend not to?

“It is actually the changes in wealth on which people base their decision-making calculations.”What Kahneman and Tversky suggested was that, in fact people think about small gambles like this in terms of losses, gains and neutral outcomes. It is actually the changes in wealth on which people base their decision-making calculations. But that doesn’t completely explain why people don’t take the bet. There’s a further piece to the puzzle.

It turns out that at low levels of risk, such as this coin flip situation, people are more averse to the loss of £10 than they are attracted by the chance of winning the £20. Studies have shown that people actually need the chance of winning £30 before they’ll consider risking their own £10.

Just as people show illogical risk aversion in some circumstances, they also show risk seeking behaviour in other circumstances.

Imagine you have to choose between these two options. The first is that you have an 85% chance of losing £1,000 along with a 15% chance of losing nothing. The second is a 100% chance of losing £800. Not much of a choice, right!? You’re between a rock and hard place. Still, sometimes we have to cut our losses.

“When the potential for loss is there, suddenly people prefer to take a risk.”According to the maths you should choose the sure loss of £800, but most people don’t. Most people choose to gamble. So when the potential for loss is there, suddenly people prefer to take a risk. They’ve become risk seekers. Yet, when there’s the potential for gains, people are often risk averse.

Framing bias

This way of thinking about how people behave in risky situations, which Kahneman and Tversky called Prospect Theory, has a second major insight that follows on from the risk aversion and risk seeking described above.

What they realised was that people behaved in different ways depending on how the risky situation was presented. Remember that if a risk is presented in terms of losses, people will be more risk seeking, and if it’s expressed in terms of gains, people will be more risk averse.

Their classic example involves this fictional situation:

“Imagine your country is preparing for the outbreak of a disease expected to kill 600 people. If program A is adopted, exactly 200 people will be saved. If program B is adopted there is a 1/3 probability that 600 people will be saved and a 2/3 probability that no people will be saved.”

Here, the risk is presented in terms of gains so people tend to choose option A (72%), which is, in fact, worse. Here’s the same problem but this time presented in terms of losses:

“Imagine your country is preparing for the outbreak of a disease expected to kill 600 people. If program A is adopted, exactly 400 people will die. If program B is adopted there is a 1/3 probability that no one will die and a 2/3 probability that 600 people will die.”

Now most people (78%) choose B because the problem is presented in terms of losses. People suddenly prefer to take a risk. In fact, if you look at both the situations you’ll see that, mathematically, they’re identical and yet people’s decision is heavily influenced by the way the problem is framed. This effect has been termed preference reversal.

Now back to the real world

After considering these sorts of problems for a few minutes, it’s easy to wonder what all of this abstract reasoning has to do with the real world. Quite a lot argue Kahneman and Tversky. The Nobel Prize committee agreed.

“Everyday life involves endless ‘gambles’.”Everyday life involves endless ‘gambles’ and betting examples are just one of the easiest ways to understand how humans make decisions in risky situations. Certainly Kahneman and Tversky’s work has plenty to say about some of the apparently strange decisions people make in everyday life.

So, next time you’re agonising over a decision in terms of losses, try this simple trick. Re-imagine the whole decision in terms of gains. I can’t promise it will help you make your decision, but at least you’ll better understand Kahneman and Tversky’s insightful research. Humans are not as rational as we would like to think.