Some people say the secret to happiness is low expectations… So it’s a very good theory, but it turns out to be wrong for three reasons.
Number one: Whatever happens, whether you succeed or you fail, people with high expectations always feel better. Because how we feel when we get dumped or win employee of the month depends on how we interpret that event.
When people with high expectations succeed, they attribute that success to their own traits. “I’m a genius, therefore I got an A, therefore I’ll get an A again and again in the future.” People with low expectations do the opposite. So when they failed it was because they were dumb, and when they succeeded it was because the exam just happened to be really easy.
Number two: Regardless of the outcome, the pure act of anticipation makes us happy. Imagine getting a passionate kiss from a celebrity, any celebrity. If you get the kiss now, it’s over and done with. But if you get the kiss in three days, well that’s three days of jittery anticipation, the thrill of the wait. Anticipation made them happy.
So optimists are people who expect more kisses in their future, more strolls in the park. And that anticipation enhances their wellbeing. In fact, without the optimism bias, we would all be slightly depressed. People with mild depression, they don’t have a bias when they look into the future. They’re actually more realistic than healthy individuals. But individuals with severe depression, they have a pessimistic bias. So they tend to expect the future to be worse than it ends up being.
So optimism changes subjective reality. It acts as a self-fulfilling prophecy. And that is the third reason why lowering your expectations will not make you happy.
We asked people to estimate their likelihood of experiencing different terrible events in their lives. So, for example, what is your likelihood of suffering from cancer? And then we told them the average likelihood of someone like them to suffer these misfortunes. So cancer, for example, is about 30 percent. And then we asked them again, “How likely are you to suffer from cancer?”
Do people take the information that we gave them and change their beliefs? Yes they did — but mostly when the information we gave them was better than what they expected. So for example, if someone said, “My likelihood of suffering from cancer is about 50 percent,” and we said, “Hey, good news. The average likelihood is only 30 percent,” the next time around they would say, “Well maybe my likelihood is about 35 percent.” So they learned quickly and efficiently. But if someone started off saying, “My average likelihood of suffering from cancer is about 10 percent,” and we said, “Hey, bad news. The average likelihood is about 30 percent,” the next time around they would say, “Yep. Still think it’s about 11 percent.”
So it’s not that they didn’t learn at all — they did — but much, much less than when we gave them positive information about the future. And it’s not that they didn’t remember the numbers that we gave them; everyone remembers that the average likelihood of cancer is about 30 percent and the average likelihood of divorce is about 40 percent. But they didn’t think that those numbers were related to them.
What this means is that warning signs such as these may only have limited impact. Yes, smoking kills, but mostly it kills the other guy.
Unrealistic optimism can lead to risky behavior, to financial collapse, to faulty planning.
So what we would really like to do, is we would like to protect ourselves from the dangers of optimism, but at the same time remain hopeful, benefiting from the many fruits of optimism. But the good news is that becoming aware of the optimism bias does not shatter the illusion. It’s like visual illusions, in which understanding them does not make them go away. And this is good because it means we should be able to strike a balance, to come up with plans and rules to protect ourselves from unrealistic optimism (eg increase budgets, timescales to compensate), but at the same time remain hopeful.”
[Tali Sharot, TED.com]