We know when we are happy. But research shows we are systematically wrong about what will make us happy in the future, and what made us happy in the past.
Daniel Gilbert, a Harvard University professor of psychology, has written an accessible account of research on this topic: Stumbling on Happiness (New York: Knopf, 2006). He describes ingenious experiments that show humans are subject to the mental equivalent of an optical illusion: we are mistaken about what will cause us to be happy.
For example, a large amount of research shows that, for those above the poverty line, extra income does not cause increased happiness. But people think it will, hence their eagerness for salary increases. Indeed, the entire economy depends on this illusion.
But even though more money doesn't bring greater happiness, people don't learn from experience: they continue to want wage increases even though previous increases didn't make them happier. This is because they have a false perception of their past mental states. In one experiment, people were asked to predict how happy or sad they'd feel if their favoured candidate (Bush or Gore) won the election, then on announcement of the result weeks later asked how happy or sad they were, and then months afterwards asked how happy or sad they had been at the time of the announcement. Their predictions and retrospective assessments were identical, saying the result would have a big impact. But the actual measured impact at the time was far less. The implication is that experience doesn't help much in learning what will make us happy.
Gilbert carefully explains the mental processes that lead to this curious phenomenon. For example, he tells how comparisons determine feelings. If you've just published your 5th article, you may feel good if you compare yourself with someone who has none, or feel bad if you compare with someone who has 25. But in predicting feelings, we use present comparisons, not future ones. So we think that we'll feel better when we've published 25 articles, but actually by that time we might well be comparing with someone who has 125. The same analysis can be applied to buying a car or applying for a job.
Another mental quirk is that "the least likely experience is often the most likely memory" (pp. 199-200). So when you think of dealings with colleagues, you may think of the most traumatic experience, or when you think of a holiday, you may think of an idyllic afternoon on the beach. This is bad for predicting what will happen in the future and causes a repetition of mistakes: most of those times on the beach may have been boring!
This is not a self-help book: it tells why we are consistently mistaken about what will make us happy. (If you want a practical guide to happiness, read Martin Seligman's Authentic Happiness. ) But Gilbert does have one recommendation: to find out how you'll feel in a future situation, ask someone who's in that situation now. Instead of imagining how you'll feel after retiring, or being denied tenure, ask someone who is retired, or has been denied tenure, how they feel about their life.
But, Gilbert notes, few people want to ask others, because of another illusion. Most people consider themselves special: they know themselves, they enjoy being special and imagine that people are quite different from each other, so they don't want to use others as surrogates. Actually, says Gilbert, people are fundamentally alike in many ways - including the ways their brains work.
There are lots of ways these ideas can be applied to university activities aside from making decisions about retiring or holidays. Beliefs about happiness influence how much energy people put into teaching, research and administration and how they deal with colleagues and students. Many of the studies cited by Gilbert are relevant to our understanding of the world, for example evaluating theories or job candidates: "When facts challenge our favored conclusion, we scrutinize them more carefully and subject them to more rigorous analysis" (p. 169). If you don't like what Gilbert has to say, that's what you'll probably do!
3 October 2006
Brian's comments to colleagues
Brian Martin's publications
Brian Martin's website