CHAPTER 1 Why Risk Intelligence Matters
He who knows best, best knows how little he knows.
Kathryn, who is a detective, is good at spotting lies. While her colleagues seem to see them everywhere, she is more circumspect. When she’s interviewing a suspect, she doesn’t jump to conclusions. Instead she patiently looks for the telltale signs that suggest dishonesty. Even so, she is rarely 100 percent sure that she’s spotted a lie; it’s more often a question of tilting the scales one way or another, she says.
Jamie is viewed as a bit of an oddball at the investment bank where he works. When everyone else is sure that prices will continue to go up, Jamie is often more skeptical. On the other hand, there are times when everyone else is pessimistic but Jamie is feeling quite bullish. Jamie and his colleagues are not always at odds, but when they disagree it tends to be Jamie who is right.
Diane is overjoyed about her new relationship. When she phones her best friend, Evelyn, to tell her all about the new man in her life, Evelyn urges caution. “What’s the chance that you’ll still be with this guy in twelve months?” she asks, as she has done before. Diane’s reply is just as predictable. “Oh, ninety, maybe ninety-five percent,” she replies, as she always does. “I’m sure Danny is the one!” Two months later, she’s broken up again.
Jeff has just been promoted to the rank of captain in the US Army. Since he is new to the role, he often feels unsure of his decisions and seeks out his colonel for a second opinion. The colonel is beginning to get rather tired of Jeff’s pestering him, and has taken to playing a little game. Whenever Jeff asks his opinion, he responds by asking how confident Jeff is of his own hunch. Usually Jeff replies that he’s only about 40 or 50 percent sure. But nine times of out ten, the colonel agrees with Jeff’s opinion.
These four people display different degrees of risk intelligence. Kathryn and Jamie have high risk intelligence, while Diane and Jeff are at the other end of the spectrum. What exactly do I mean by risk intelligence? Most simply put, it is the ability to estimate probabilities accurately, whether the probabilities of various events occurring in our lives, such as a car accident, or the likelihood that some piece of information we’ve just come across is actually true, such as a rumor about a takeover bid. Or perhaps we have to judge whether a defendant in a murder trial is guilty, or must decide whether it’s safe to take a trip to a country that’s been put on a watch list. We often have to make educated guesses about such things, but fifty years of research in the psychology of judgment and decision making show that most people are not very good at doing so. Many people, for example, tend to overestimate their chances of winning the lottery, while they underestimate the probability that they will get divorced.
At the heart of risk intelligence lies the ability to gauge the limits of your own knowledge—to be cautious when you don’t know much, and to be confident when, by contrast, you know a lot. People with high risk intelligence tend to be on the button in doing this. Kathryn and Jamie, for example, are relatively risk intelligent because they know pretty well how much they know and have just the right level of confidence in their judgments. Diane and Jeff are much less proficient, though in different ways; while Diane is overconfident, Jeff is underconfident.
This is a book about why so many of us are so bad at estimating probabilities and how we can become better at it. This is a vital skill to develop, as our ability to cope with uncertainty is one of the most important requirements for success in life, yet also one of the most neglected. We may not appreciate just how often we’re required to exercise it, and how much impact our ability to do so can have on our lives, and even on the whole of society. Consider these examples, from the relatively mundane to the life-threatening:
You are buying a new 42-inch HDTV, and a sales assistant asks if you would also like to purchase an extended warranty. He explains that if anything goes wrong with your TV in the next three years, the warranty will entitle you to swap it for a brand-new one, no questions asked. When deciding whether or not to purchase the extended warranty, you should consider the price of the TV, the price of the warranty, and the probability that the TV will indeed go wrong in the next three years. But what’s the chance that this will actually happen? Here’s where your risk intelligence comes in.
A bank manager is explaining to you the various options available for investing a windfall that has just come your way. Riskier investment funds pay more interest, but there’s also a higher chance of making a loss. How much of your money should you allocate to the high-risk funds and how much to the low-risk ones? It’s partly a question of risk appetite, but you also need to know more about how much
riskier the high-risk funds are. Are they 2 percent or 10 percent riskier? You need, in other words, to put a number on it.
Doctors have discovered a tumor in your breast. Luckily, it is not malignant. It will not spread to the rest of your body, and there is no need to remove your breast. But there is a chance that it may recur and become malignant at some time in the future, and it might then spread quickly. In order to prevent this possibility, the doctor suggests that you do, after all, consider having your breast removed. It’s a terrible dilemma; clearly you don’t want the cancer to recur, but it seems a tragedy to remove a healthy breast. How high would the chance of recurrence have to be before you decided to have the breast removed?
When making evaluations in situations of uncertainty, people often make very poor probability estimates and may even ignore probabilities altogether, with sometimes devastating consequences. The decisions that we face, both individually and as a society, are only becoming more daunting. The following cases further illustrate how important it is that we learn to develop our risk intelligence. THE CSI EFFECT
The television drama CSI: Crime Scene Investigation
is hugely popular. In 2002, it was the most watched show on American television, and by 2009 the worldwide audience was estimated to be more than 73 million. It isn’t, however, such a hit with police officers and district attorneys, who have criticized the series for presenting a highly misleading image of how crimes are solved. Their fears have been echoed by Monica Robbers, a criminologist, who found evidence that jurors have increasingly unrealistic expectations of forensic evidence. Bernard Knight, formerly one of Britain’s chief pathologists, agrees. Jurors today, he observes, expect more categorical proof than forensic science is capable of delivering. And he attributes this trend directly to the influence of television crime dramas.
Science rarely proves anything conclusively. Rather, it gradually accumulates evidence that makes it more or less likely that a hypothesis is true. Yet in CSI
and other shows like it, the evidence is often portrayed as decisive. When those who have watched such shows then serve on juries, the evidence in real-life court cases can appear rather disappointing by contrast. Even when high-quality DNA evidence is available, the expert witnesses who present such evidence in court point out that they are still dealing only in probabilities. When the jurors contrast this with the certainties of television, where a match between a trace of DNA found at a crime scene and that of the suspect may be unequivocal, they can be less willing to convict than in the past.
The phenomenon has even been given a name: “the CSI
effect.” In 2010, a study published in Forensic Science International
found that prosecutors now have to spend time explaining to juries that investigators often fail to find evidence at a crime scene and hence that its absence in court is not conclusive proof of the defendant’s innocence. They have even introduced a new kind of witness to make this point—a so-called negative evidence witness.
Unrealistic expectations about the strength of forensic evidence did not begin with CSI,
of course. Fingerprints led to the same problem; they have been treated by the courts as conclusive evidence for a hundred years. In 1892, Charles Darwin’s cousin Francis Galton calculated that the chance of two different individuals having the same fingerprints was about 1 in 64 billion, and fingerprint evidence has been treated as virtually infallible ever since, which means that a single incriminating fingerprint can still send someone to jail. But, like DNA evidence, even the best fingerprints are imperfect. After a mark is found at a crime scene, it must be compared to a reference fingerprint, or “exemplar,” retrieved from police files or taken from a suspect. But no reproduction is perfect; small variations creep in when a finger is inked or scanned to create an exemplar.
More important, fingerprint analysis is a fundamentally subjective process; when identifying distorted prints, examiners must choose which features to highlight, and even highly trained experts can be swayed by outside information. Yet the subjective nature of this process is rarely highlighted during court cases and is badly understood by most jurors. Christophe Champod, an expert in forensic identification at the University of Lausanne in Switzerland, thinks the language of certainty that examiners are forced to use hides the element of subjective judgment from the court. He proposes that fingerprint evidence be presented in probabilistic terms and that examiners s...