When I, many years ago, met my current partner, he had a PC with a ‘turbo button’. In retrospect, it seems bizarre (although I seem to remember that some games became easier when the button was not pressed), but even then we discussed if we would ever like to work with the button released. Why would you not want to have maximum computing capacity on his computer? It is roughly the same question that I intend to pose here, but linked to the human brain. In the debate on intelligence, it is almost always assumed that intelligence is something worth striving for. We can discuss what intelligence is, if there are multiple intelligences, or just one, and if there is any point in trying to measure intelligence, but the basic positive view of intelligence, we take for granted. What is it that is so good about being smart?

In this article I will assume that intelligence is about what is measured in an intelligence test. This means that the focus is on problem-solving skills, skills in abstract thinking, and how quickly we absorb new information. The ‘turbo button’ represents the power of intelligence, that which makes someone who is good at intelligence tests a bit faster and stronger in thought. We know, of course, a lot of intelligence is defined in this way. First and foremost, individuals with high IQs often cope well in an academic context; they achieve better school results and go on to further education. This relationship is not so surprising given that the first intelligence test was developed specifically to predict how well children would succeed in school. Clearly, in any case, success at school is an insufficient indicator that it is good to be smart. Of course, there is research on the relationship between intelligence and a host of other factors, such as social status, income, and so on.

One problem with this type of relationship is that it is difficult to determine what is affecting what. For example, we find that people with higher IQs tend to have higher social status. However, individuals with higher social status also do better at school and educate themselves more. Which is the chicken and which is the egg? When trying to understand this type of connection you can see that intelligence itself has some influence on such status and professional success, even if there are many other factors. But this is only because people with higher intelligence are more successful in that which they undertake, or is it also that they place themselves in situations where they can be more successful? Does one make better decisions because one is smart?

When one discusses intelligence and decision-making, there seems to often be an underlying assumption that intelligence leads to better decisions: intelligent people can see more options, weigh them against each other in the right way, and can identify the different impacts of each alternative approach. An example of this way of making decisions can be found in Charles Darwin’s notes from 1838. The question of the day was whether he should marry or not, and the decision ultimately taken was a yes. Since his marriage to Emma Wedgewood was said to have been a happy one, we can say that this also was a successful decision. Notes such as these are wonderful, but actually I hope that Emma Wedgewood never saw them. On the list of benefits of marriage you will find things like: ”Children – (if it Please God) – Constant companion, (& friend in old age) who will feel interested in one, – object to be beloved & played with. –better than a dog anyhow.” On the ‘against’ list appears: lack of time, relatives and the risk of splitting up. Even if the details are correct, so irresistible is the general principle of making a list of the different things that might happen if we choose one or the other that is of interest here. It seems that Darwin decided that the combination of potential children and someone who likes one (and everything else that is on the list) outweighs the negatives overall. At the bottom of the list, it says ”Marry – Marry – Marry QED”.

Darwin’s way of deciding for or against marriage is right, like the way of making decisions that is usually recommended by those who have studied decision-making. Leonard Savage, for example, who has had a tremendous influence on psychological and, to some extent, philosophical decision research, recommends a method of decision-making, which is to calculate the value of each possible outcome (how negative is it if you happen to argue sometimes?) and how likely it is to occur (if we marry, how likely is it that we will fight? How often will we fight?). Then this is combined for the various options (married or not), and the aggregate expected benefit of each alternative is what determines the choice. One calculates the likelihood of fights and how bad it is to quarrel over the probability of being liked in old age, and how nice it would be. If all factors are included, and the weighting is correct, it may be said that the decision is good. The goal is simply to ”maximise expected benefit.”

It is easy to see that this way of making decisions would be better if the decision maker were intelligent. Being able to identify the various possible outcomes, to be good at assessing probabilities, and to be able to weigh-up all this properly, seem to be characteristics of the intelligent decision-maker, and less so of the less intelligent. When making decisions in the Darwinian way, there must be an advantage in being able to obtain information quickly, to be good at thinking on many levels, and to be able to apply what we know. If we assume that decisions are made in Darwin’s way, and are best if made in Darwin’s way, we can therefore argue that intelligent people have an advantage over others because they make better decisions. They make the most of their opportunities and, by selecting wisely, make the world look more as they would like.

If intelligence, on the other hand, doesn’t have much to do with good decision-making, perhaps the benefits come from a less interesting character. That school goes better for those who get good results on an intelligence test is, in itself, well established, but it is not necessarily a reason that intelligence is desirable. Rather, you could be led to reflect on the fact that those who are researching intelligence measurements are individuals who have settled on an academic career, and who have managed to survive one. Perhaps there is an excessive focus on qualities that favour this type of life, rather than qualities that give us a good life in general? Are most of our decisions taken in ways that benefit from intelligence? And is it that the ‘intelligent’ way to decide is better than the way that requires less calculation power, or one that does not need a ‘turbo button’ to be pressed?

The first thing worth noting is that we make lots of decisions without consideration of the kind that Darwin does in the example above. We can probably even have reason to doubt that it was Darwin’s list that enabled him to decide on marriage. When I look closely at his presentation, I begin to suspect that his conclusion on marriage was not fully supported by the possible consequences that were on the list. It is of course impossible to prove but, when I read the notes critically, I suspect that he would have been content with a dog and a housekeeper. The only additional benefit that a wife has compared this combination is the opportunity for children, but with these comes cost, worry and responsibility, and these negative factors may require more space in the notes than the positive. Could not the image of ”… a nice soft wife on a sofa with good fire, & books & Music Perhaps” be easily replaced by a nice little half-fat dog on the same couch? I think that it was not the factors found in Darwin’s notes, which prompted him to write QED at the bottom of the page, but rather a lot of things that are not on the list at all.

But regardless of how Darwin made this decision, it is quite obvious that lots of decisions every day are taken without thinking about the consequences. Decision-making simply happens too fast for people to have a chance to even take in even a fraction of that which is relevant to the choice. Even when it comes to the most simple decisions, there is so much that could possibly affect which option is the best that one cannot, even with the best will in the world, take the time to consider them. The second question is whether there is an advantage in making decisions in a considered way. It is not easy to determine because most real decisions have nothing with which to compare them. When Darwin became happily married, it became impossible to find out what would have happened had he not done it. Might he have been even happier unmarried? More successful in his research? Lived longer? But by comparing different decision strategies with each other, in actual fact or in simulations of various kinds, we can at least start to acquire knowledge on how to best make decisions.

Imagine a sought-after education has its admission requirements changed. The number of applications is huge, and there are very limited places. To find the most suitable students, the management has decided to try a variety of methods to assess students. The goal is to find the students who will have the greatest success (academically speaking) during the course. They are looking therefore for those who will pass with the highest marks and, hopefully, also the most knowledge. One method is to form a committee to look at the candidates’ qualifications, letters of recommendation, scores on the entrance exam, how good a school the applicants come from, and interviews. Another option is to try to build a mathematical formula that predicts student success by using parts of the information listed above. We can investigate the relationship between grades, scores on the entrance exam, and previous students’ results (final grade for the course), for example by constructing a simple mathematical model that weighs such factors.

Half a century of research shows that formal assessment methods tend to predict the future (in our case the students will do well on the course) better than do admissions committees or curators. In a large meta-study of human- and formula-based assessment, hundreds of studies were examined in the vi- ka researchers compared with people’s assessments of formulas. In half the cases the formal assessment was clearly the best. In a few cases (six percent) the people fared better but, in general, it was roughly a draw. When the human team had to do interviews (as in the admissions committee above) one could almost be certain that the human assessor would do less well than the formula. From this we can learn at least two things: the first is that it is better to be consistent. It seems to be one of the main reasons that the formulas do better than human assessors. One problem with the interviews could be that they are fooling us to ignore the more formal grading criteria. Second, we can learn from the comparison between human and formula that it can sometimes pay to ignore information. The formulas can only make use of quantifiable information about the candidates, and other factors, such as interviews, one must disregard. But this seems to surely be a great benefit to the formula-based assessment. It seems that it can sometimes be good to have less information.

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One of the strongest demonstrations of less information being an advantage is a series of experiments and simulations conducted by the scientists Gigerenzer and Goldstein. These include a study on American students in Chicago. Students were instructed to try to guess which of a pair of cities was bigger. They had long lists of city pairs, for example, San Diego and Sacramento. Sometimes American and sometimes German. Funnily enough, the students were equally as good at guessing which of two German cities was bigger as they were at guessing U.S. cities. One explanation is that the American volunteers could use their ignorance when they chose between German cities. When the subjects made a prediction, they had three options: they could base their assessment on the information they had on the towns or guess. In addition, they could, where possible, simply select the city name that they recognised and assume that the recognised city was the bigger of the two. Since the American students knew about most American cities, they could not base their assessment on whether they recognised one of the cities. They were instead using their knowledge or guessing. But when they chose between German cities they recognised significantly fewer cities. Researchers hypothesise that the subjects then used the principle: if you choose between a few options and only recognise one of them, choose the one you recognise. As long as it is more likely that we recognise the large cities than small, the principle is going to be relatively successful.

If we look at just the German and American cities the subjects were asked to choose among, it seems that recognition correlates with size. Gigerenzer and Goldstein examined, for example, how often foreign cities were mentioned in German and American newspapers (Die Zeit and The New York Times) and found that larger cities were mentioned more frequently. In this case, it is therefore a good idea to choose the city you will recognise. But such a method works, of course, only if there are cities you do not recognise. Ignorance, as long as it is systematic, can be an advantage. So it is not certain that those best at collecting information will be the ones who make the best decisions. One thing in the above, which suggests that the intelligent can be better decision-makers, is that those who make many decisions on similar grounds (such as the admissions committee) would be wise to be systematic. And an intelligent decision-maker would be better able to follow an abstract rule. But how hard is this to do?

Here comes in the question of aggregate knowledge. It’s not just information gathering at which the decision-maker with a higher IQ will be better. She should also be better able to integrate information – to weigh the various factors. However, there is research that indicates that there is no need to weigh the information in any complicated way to make successful decisions. When trying to assess how important a factor grades are for academic success, relative to other factors such as scores on the entrance exam, one can closely examine exactly how important the different factors are compared with each other. Maybe we should put more emphasis on grades, or maybe we will, on the contrary, focus on the entrance exam? In fact, computational models that take into account these weights cannot do much better in their predictions than models that only add up and may prefer an individual who has both good grades and high scores on the entrance exam, compared with someone that has only one. It seems that as long as we know whether a factor is good or bad (truancy, for example, is assumed to be a negative factor for academic success) and as long as we can find sensible factors, it seems to be sufficient to simply add up the facts. If one accepts these results, it appears that very advanced thinking skills are not needed to make sensible decisions. We even find a relatively successful method for assessing a good marriage in the same literature. As long as Charles and Emma Darwin loved more than they argued, we can be pretty sure that they assessed their own marriages as being happy.