In Risk Savvy, Gigerenzer makes the contrarian case that the world doesn’t need more experts, more number crunching, more big data, but rather, a better education about the nature of risk. He contrasts risk with uncertainty. Risk is associated with controlled environments with fixed rules, such as casinos.
These are places that allow us to make precise probability calculations. Uncertainty, often mistaken for risk, is quite different. The stock market is not about risk, it’s about uncertainty. Since stock prices are determined by real world events, and unlike casinos, real world events don’t operate under a controlled environment with fixed rules, then we cannot apply our typical understanding of probabilities to the messy and highly complex world of the stock market.
That’s why stock market “experts” are no better than amateurs at picking stocks; often, they are even worse. Big life decisions such as who to start a company with, who to marry, and where to live, are decisions that are not about risk, but about uncertainty. In these cases, Gigerenzer thinks that we should depend on our intuition and simple rules of thumb. Intuition is not some magical ability that only some people have. All humans have intuition, and it is based on unconscious learning, and is therefore, a highly intelligent mechanism for making decisions. Rules of thumb are also highly intelligent, since it considers only the most important variable, rather than try to optimize for complicated variables.
Take for instance, the act of catching a ball. If you wanted to reliably become a good catcher, it would a lot more effective for you to simply fix the center of your visual field on the ball as it moves, and to keep it there by moving with it, rather than mathematically calculate the trajectory and speed of the ball in order to determine your location and the position of your hands a few moments later.
Should you always go with shortcuts (or heuristics) and intuition rather than rely on mathematics? No. But people are often confused about when to use either. In casinos and in fixed environments, it is obviously better to go with the numbers. It would be silly to think that your intuition can help you beat a slot machine that is designed to pay out 80 percent of the time. But it would also be silly to use mathematical equations to try to predict the movements of the stock market. The ironic thing is that many people do exactly that. They forget about the mathematics inside a casino, but when they are trying to play the stock market, they suddenly develop the urge to rely on Fibonacci sequences and mathematical instruments. This illustrates a basic confusion between risk and uncertainty.
Gigerenzer also explains how medical doctors fall prey to the same mistakes when calculating risk. For example, regular check ups are not effective at preventing disease, yet people are obsessed with getting them. Much more important is to avoid things that make you sick in the first place, like smoking, unhealthy food, and a sedentary lifestyle.
Traffic Accidents and 9/11
The increase in road travel had sobering consequences. Before the attack (of 9/11), the number of fatal traffic accidents remained closely around the average of the previous five years (the zero line in Figure 1-2). Yet in each of the twelve months after 9/11, the number of fatal crashes was above average, and most of the time, even higher than anything that happened in the previous five years. All in all, an estimated sixteen hundred Americans lost their lives on the road due to their decision to avoid the risk of flying. P.10
Risks Vs Uncertainty
RISK: If risks are known, good decisions require logic and statistical thinking.UNCERTAINTY: If some risks are unknown, good decisions also require intuition and smart rules of thumb.Most of the time, a combination of both is needed. Some things can be calculated, others not, and what can be calculated is often only a crude estimate.
The Three Faces of Probability
One important fact is often overlooked. Probability is not one of a kind; it was born with three faces: frequency, physical design, and degrees of belief.And these have persisted to this day.Frequency: In the first of its identities, probability is about counting. Counting the number of days with rainfall or the number of hits a baseball player makes and dividing these by the total number of days or strikes results in probabilities that are relative frequencies. Their historical origins lie in seventeenth-century mortality tables, from which life insurances calculated probabilities of death.Physical Design.Second, probability is about constructing. For example, if a die is constructed to be perfectly symmetrical, then the probability of rolling a six is one in six. You don’t have to count. Similarly, mechanical slot machines are physically designed to pay out, say, 80 percent of what people throw in, and electronic machines have software that determines the probabilities. Probabilities by design are called propensities. Historically, games of chance were the prototype for propensity. These risks are known because people crafted, not counted, them.Degrees of Belief.Third, probability is about degrees of belief. A degree of belief can be based on anything from experience to personal impression. Historically, its origin is in eyewitness testimony in courts and, more spectacularly, in the Judeo-Christian lore of miracles. To this day, the testimony of two independent witnesses counts more than that of two who talked with each other beforehand, and the same holds for the testimony of a witness who did not know the defendant than that of his brother. But how to quantify these intuitions? That was the question that gave rise to degrees of belief expressed as probabilities. P 25Uncertainty (Stocks, Romance, Earthquake, Health, Business) is confused with Risk (Casino, Slots, Lottery) which is confused with Certainty.
The Turkey Illusion
It is not always easy to know how uncertain the situation is in which we find ourselves, whether it contains known risks or is largely unpredictable. Let’sbegin with a story by writer Nassim Taleb.24 Put yourself into the mind of aturkey. On the first day of your life a man came. You were afraid that he might kill you, but he was kind and gave you food. Next day, you see the man approach you once more. Will he feed you again? Using probability theory, you can calculate the chance that this will happen. The rule of succession, derived by the great mathematician Pierre-Simon Laplace, provides the answer:Probability that something happens again if it happened n times before = (n+1)/(n+2)Here, n is the number of days the farmer fed you. That is, after the first day, the probability that the farmer will feed you the next day is 2/3, after the second day it increases to 3/4, and so on, growing more and more certain every day. At the same time, the alternative that he might kill you becomes less and less likely. On day one hundred, it is almost certain the farmer will come to feed you, or so you might think. But unknown to you, that day is the day before Thanksgiving. Just when the probability of being fed is higher than ever before, you’re dead meat.Let’s sum up:1. RISK ≠ UNCERTAINTY. The best decision under risk is not the best decision under uncertainty.2. RULES OF THUMB ARE NOT DUMB. In an uncertain world, simple rules of thumb can lead to better decisions than fancy calculations.3. LESS IS MORE. Complex problems do not always require complex solutions. Look for simple solutions first.Future is hard to predict.
The Uncertain Future Is Hard to Predict
“Predictions are hard, especially about the future.” – Niels Bohr (also attributed to Mark Twain, Yogi Berra, and a host of others)
Telephones
In 1876 Western Union, the largest American telegraph company, refused to buy Graham Bell’s patent for one hundred thousand dollars, arguing that people are not savvy enough to handle a phone: “Bell expects that the public will use his instrument without the aid of trained operators. Any telegraph engineer will at once see the fallacy of this plan. The public simply cannot be trusted to handle technical communications equipment.”29 A group of British experts thought somewhat differently: “The telephone may be appropriate for our American cousins, but not here, because we have an adequate supply of messenger boys.”
Lightbulbs
A few years later, a committee of the British Parliament evaluated Thomas Edison’s lightbulb and concluded that it would be “good enough for our trans-Atlantic friends…but unworthy of the attention of practical or scientific men.”
Radios
“Radio has no future.” Attributed to Lord Kelvin, former president of the Royal Society, ca. 1897.
Trains
“Rail travel at high speed is not possible because passengers, unable to breathe, woulddie of asphyxia [suffocation].” Dr. Dionysius Lardner (1793–1859), professor at University College London, and author of a book on the steam engine, was one of several doctors who prophesized that the rapid movement of trains would cause death or brain trouble among travelers and vertigo among onlookers.
Cars
Car pioneer Gottlieb Daimler (1834–1900) believed that there would never be more than one million cars worldwide because of the lack of available drivers. Daimler based this prediction on the false assumption that cars would have to be operated by chauffeurs.
Computers
Howard Aiken, who constructed the Mark I computer for IBM in 1943, reminisced: “Originally one thought that if there were a half dozen large computers in this country, hidden away in research laboratories, this would take care of all requirements we had throughout the country.” This prediction was based on the false assumption that computers would solve scientific problems only.
Good Errors
As we have seen, experiencing a visual illusion means making a good error. Good errors are errors that need to be made. Children are known for these. Consider a three-year-old who uses the phrase “I gived” instead of “I gave.” The child cannot know in advance which verbs are regular and which are irregular. Because irregular verbs are rare, the child’s best bet is to assume the regular form until proven wrong. Such errors are good, or functional, because if the child decided to play it safe and use only those verbs he has already heard, he would learn at a much slower pace. Learn by failing, or you fail to learn.
Serendipity, the discovery of something one did not intend to discover, is often a product of error. Christopher Columbus wanted to find a sea route to India. He believed he could reach India by ship because he made an error: He grossly underestimated the diameter of the globe. Others knew better and criticized his plan as foolish. They were right. But because of his error, Columbus discovered something else, America. Similarly, some of my own discoveries were never planned, such as the discovery of the “less-is-more effect.” Here is the story.
For an experiment, we needed a set of easy questions and a set of hard ones. Because those who took part in the experiment were German, we came up with questions about the population of German cities (which we assumed would be easy) and U.S. cities (hard). We chose the seventy-five largest cities in each country. For instance,“Which city has a larger population: Detroit or Milwaukee?”“Which city has a larger population: Bielefeld or Hanover?”The result blew our minds. Germans didn’t do best on questions about German cities, about which they knew lots, but slightly better on American cities, about which they knew little. We’d made an error in assuming that knowing more always leads to better inferences. The experiment was ruined.But this error led us to discover something new, which we called the recognition heuristic:If you recognize the name of one city but not that of the other, then infer