Herbert Simon's idea of satisfying solves that problem. A satisfier, searching for a mate, would have an aspiration level. Once this aspiration is met, as long as it is not too high, he will find the partner and the problem is solved. But satisfying is also a purely cognitive mechanism. After you make your choice you might see someone come around the corner who looks better, and there's nothing to prevent you from dropping your wife or your husband and going off with the next one.

Here we see one function of emotions. Love, whether it be romantic love or love for our children, helps most of us to create a commitment necessary to make us stay with and take care of our spouses and families. Emotions can perform functions that are similar to those that cognitive building blocks of heuristics perform. Disgust, for example, keeps you from eating lots of things and makes food choice much simpler, and other emotions do similar things. Still, we have very little understanding of how decision theory links with the theory of emotion, and how we develop a good vocabulary of building blocks necessary for making decisions. This is one direction in which it is important to investigate in the future.

Another simple example of how heuristics are useful can be seen in the following thought experiment: Assume you want to study how players catch balls that come in from a high angle — like in baseball, cricket, or soccer — because you want to build a robot that can catch them. The traditional approach, which is much like optimization under constraints, would be to try to give your robot the complete representation of its environment and the most expensive computation machinery you can afford. You might feed your robot a family of parabolas because thrown balls have parabolic trajectories, with the idea that the robot needs to find the right parabola in order to catch the ball. Or you feed him measurement instruments that can measure the initial distance, the initial velocity, and the initial angle the ball was thrown or kicked. You're still not done because in the real world balls are not flying parabolas, so you need instruments that can measure the direction and the speed of the wind at each point of the ball's flight to calculate its final trajectory and its spin. It's a very hard problem, but this is one way to look at it.

A very different way to approach this is to ask if there is a heuristic that a player could actually use to solve this problem without making any of these calculations, or only very few. Experimental studies have shown that actual players use a quite simple heuristic that I call the gaze heuristic. When a ball comes in high, a player starts running and fixates his eyes on the ball. The heuristic is that you adjust your running speed so that the angle of the gaze, the angle between the eye and the ball, remains constant. If you make the angle constant the ball will come down to you and it will catch you, or at least it will hit you. This heuristic only pays attention to one variable, the angle of gaze, and can ignore all the other causal, relevant variables and achieve the same goal much faster, more frugally, and with less chances for error.

This illustrates that we can do the science of calculation by looking always at what the mind does — the heuristics and the structures of environments — and how minds change the structures of environments. In this case the relationship between the ball and one's self is turned into a simple linear relationship on which the player acts. This is an example of a smart heuristic, which is part of the adaptive tool box that has evolved in humans. Many of these heuristics are also present in animals. For instance, a recent study showed that when dogs catch frisbees they use the same gaze heuristic.

Heuristics are also useful in very important practical ways relating to economics. To illustrate I'll give you a short story about our research on a heuristic concerning the stock market. One very smart and simple heuristic is called the recognition heuristic. Here is a demonstration: Which of the following two cities has more inhabitants — Hanover or Bielefeld? I pick these two German cities assuming that you don't know very much about Germany. Most people will think it's Hanover because they have never heard of Bielefeld, and they're right. However, if I pose the same question to Germans, they are insecure and don't know which to choose. They've heard of both of them and try to recall information. The same thing can be done in reverse. We have done studies with Daniel Gray Goldstein in which we ask Americans which city has more inhabitants — San Diego or San Antonio? About two-thirds of my former undergraduates at the University of Chicago got the right answer: San Diego. Then we asked German students — who know much less about San Diego and many of whom had never even heard of San Antonio — the same question. What proportion of the German students do you think got the answer right? In our study, a hundred percent. They hadn't heard of San Antonio, so they picked San Diego. This is an interesting case of a smart heuristic, where people with less knowledge can do better than people with more. The reason this works is because in the real world there is a correlation between name recognition and things like populations. You have heard of a city because there is something happening there. It's not an indicator of certainty, but it's a good stimulus.

In my group at the Max Planck Institute for Human Development I work alongside a spectrum of researchers, several of whom are economists, who work on the same topics but ask a different kind of question. They say, "That's all fine that you can demonstrate that you can get away with less knowledge, but can the recognition heuristic make money?" In order to answer this question we did a large study with the American and German stock markets, involving both lay people and students of business and finance in both countries. We went to downtown Chicago and interviewed several hundred pedestrians. We gave them a list of stocks and asked them one question: Have you ever heard of this stock? Yes or no? Then we took the ten percent of the stocks that had the highest recognition, which were all stocks in the Standard & Poor's Index, put them in the portfolio and let them go for half a year. As a control, we did the same thing with the same American pedestrians with German stocks. In this case they had heard of very few of them. As a third control we had German pedestrians in downtown Munich perform the same recognition ratings with German and American stocks. The question in this experiment is not how much money the portfolio makes, but whether it makes more money than some standards, of which we had four. One consisted of randomly picked stocks, which is a tough standard. A second one contained the least-recognized stocks, which is according to the theory an important standard, and shouldn't do as well. In the third we had blue chip funds, like Fidelity II. And in the last we had the market — the Dow and its German equivalent. We let this run for six months, and after six months the portfolios containing the highest recognized stocks by ordinary people outperformed the randomly picked stocks, the low recognition stocks, and in six out of eight cases the market and the mutual funds.

Although this was an interesting study, one should of course be cautious, because unlike in other experimental and real world studies, we have a variable and very random environment. But what this study at least showed is that the recognition of ordinary citizens can actually beat out the performance of the market and other important criteria. The empirical evidence, of course — the background — is consumer behavior. In many situations when people in a supermarket choose between products they go with the item with name recognition. Advertising by companies like Benetton exploits the use of the recognition heuristic. They give us no information about the product, but only increase name recognition. It has been a very successful strategy for the firm.

Of course the reaction to this study, which is published in our book Simple Heuristics that Make Us Work, has split the experts in two camps. One group said this can't be true, that it's all wrong, or it could never be replicated. Among them were financial advisers, who certainly didn't like the results. Another group of people said, "This is no surprise. I knew it all along. The stock market's all rumor, recognition, and psychology." Meanwhile, we have replicated these studies several times and found the same advantage of recognition — in bull and bear market — and also found that recognition among those who knew less did best of all in our studies.

I would like to share these ideas with many others, to use psychological research, and to use what we know about how to facilitate people's understanding of uncertainties to help to promote this old dream about getting an educated citizenship that can deal with uncertainties, rather than denying their existence. Understanding the mind as a tool that tries to live in an uncertain world is an important challenge.

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