It’s hard to overstate the pleasures in these two books. Both are playful, readable, charming and suffused with the puzzled joy of discovery.
Michael Lewis is a deft popularizer. His books on Wall Street, including The Big Short and Flash Boys, provided splendid descriptions of the 1998 mortgage-securities crisis and the Street’s fine art of front-running customer orders. His Moneyball (2003), which I haven’t read, explores the use of statistics in sports management. The first 50 pages of The Undoing Project focus on the problem of uncertainty again through a sports lens, but it’s really unnecessary: Kahneman and Tversky needn’t come in through the back door. When he gets to the two men, and the zig-zag careers that brought them together, Lewis shines. Amos Tversky emerges as an almost mythical figure, Israeli-born geek who became a paratrooper, the smartest, most confident and happiest man in any room. What an event when Danny Kahneman, the self-doubter, invites Tversky to address a seminar at Hebrew University in Jerusalem in 1969 and then declares that he disagrees with everything Tversky said.
What developed over fifteen years was a partnership in which both men preferred one another’s company to anyone else’s. As they devised tests to determine how people actually make decisions, passers-by outside their offices heard rollicking laughter. The partners were fascinated by the willingness of rational people, including statisticians, to contradict themselves depending on how a number of options were presented. In the simplest form, telling someone there’s a 90 percent chance of success in a life-saving medical procedure induces a different response from telling him there is a 10 percent chance of failure. How is that people who are risk-averse when offered one gamble become risk-seekers when offered an inverted version that is statistically identical? The venerable model of utility theory, which addressed how people viewed gains and losses, was wanting. By 1975, the authors presented a draft of one of their seminal papers: a discussion of decision-making under uncertainty. The work, developed as Prospect Theory, made them famous.
The partnership became strained. Tversky accepted a lifetime appointment at Stanford. Kahneman headed for a less illustrious post at the University of British Columbia. By the end of the decade, reflecting on people’s reaction to the death of a nephew in a fighter-plane accident, and on his own reactions to upheavals in his private life, Kahneman was looking at the use of counter-factual stories as a way of dealing with regret. The partnership had defined three heuristics that shaped thought: availability, anchoring and representativeness. Now Kahneman was thinking of a fourth heuristic, a “simulation heuristic,” described by Lewis as “all about the power of unrealized possibilities to contaminate people’s minds.”
As Tversky’s fame grew, so did Kahneman’s insecurity. They were collaborating at a distance when Tversky proposed a counterattack on a German critic. Reluctantly Kahneman joined in the research and the Problem of Linda emerged as a test of subjects’ rationality. The results were dumfounding. It didn’t matter whether the test was given to undergraduates, graduate students or professors. “People were blind to logic,” Lewis reports, “when it was embedded in a story.” Kahneman fed the test to a dozen students, and all of them fell for it. They tightened the test to an essential alternative—shoving “their subjects’ noses right up against logic,” Lewis recounts. Which statement is more probable: “Linda is a bank teller.” or “Linda is a bank teller and is active in the feminist movement.” Eighty-five percent chose the latter statement, defying logic. It was a stunning discovery. They tried other versions of the same problem. Their conclusion, presented in a 1983 paper, was that even well-educated, mathematically literate people do not instinctively think statistically or logically when presented with a story.
The partnership’s insights are broadly applicable, seemingly reaching into any theory-driven non-mathematical work as well as into day-to-day practical decision-making. Regarding the narrative fallacy, Tversky commented, “In contrast to our skill in inventing scenarios, explanations, and interpretations, our ability to assess their likelihood, or to evaluate them critically, is grossly inadequate. Once we have adopted a particular hypothesis or interpretation, we grossly exaggerate the likelihood of that hypothesis, and find it very difficult to see things any other way.” Equity investors who “buy the story” will know what he meant. Almost in passing, Tversky gave a talk to historians that cut the ground out from under their causal narratives: “All too often, we find ourselves unable to predict what will happen; yet after the fact we explain what did happen with a great deal of confidence. This ‘ability’ to explain that which we cannot predict, even in the absence of any additional information, represents an important, though subtle, flaw in our reasoning. It leads us to believe there is a less uncertain world than there actually is. . . .”
Lewis’s book benefits from access to memos the partners wrote, the recollections of people who knew one or both of them, and of Kahneman’s description of their experiences working separately and together. The final chapter’s triumphal tone, as assorted acolytes such as Cass Sunstein use Kahneman and Tversky’s work as a basis for public policy decisions, is laughably counter-factual and a pretty good example of what the partners noted as a tendency to be blinded by theory. But it’s a minor blemish, as is the absence of an index, in an excellent introduction to two important thinkers.
In Thinking, Fast and Slow, published in 2011, Kahneman walks us through the partnership’s work (and other researchers’) like a tour guide wearing a straw hat and waving a black cane. “Here,” he says engagingly, “is this absurdity. Here is another. Can you believe that we don’t notice how often our conclusions defy logic?” Revisiting this book after Lewis’s adds to the pleasure. Kahneman and Tversky worked primarily from noticing their own mistakes and wondering: If we believed that, how many other people do—surely it’s not that many?—and in any case why?
What, for example, do you make of the fact that a tiny county in West Virginia has the highest bladder cancer rate in the nation? Or the fact that a year later it has the lowest? How is it that we perform less well in a state of cognitive ease, and that our focus and performance can be improved by the simple act of frowning? (For years we’ve reminded our son heading into an exam, Scowl at the damned thing!) Why do we succumb to the simplest forms of emphasis in messages, favoring a statement in bold-face type? Why do we find banal aphorisms truer if they are rhymed? How can we be primed into falling for the gimmick of repeating “shop” a dozen times and then responding to the question, “What do you do at a green light?” by answering “Stop.” These aren’t, as it happens, trivial questions. People who understand how we think are adept at manipulating our opinions and decisions. Imagine the television cameras descending on the small county in West Virginia with the highest bladder cancer rate in the U.S. The reporters look around, discover a paper mill upstream. An environmental professor is found to declare causation. The story of corporate greed goes viral. We’re outraged at the callousness. A year later, the mill is still operating, and the bladder cancer rate is zero. The reporters do not return to discuss the “law of small numbers.” Kahneman does, and his reader will take a deep breath before accepting casually reported statistics in the future.
Or you’re thinking of buying a house. You find one you love. The comparable for similar houses in the area is $200,000. Ideally, you would like to get your house for a bit less than it’s worth. The seller has listed the house at $275,000. You know that’s too much. What do you offer? Offering seven percent less than a house is worth is a normal buyer’s strategy. But offering $186,000 looks like you’re trying to steal the place compared to the $275,000 listing price. The listing price is an example of “anchoring,” and many people’s opening bid will be north of $200,000. Auditors try to avoid being anchored by previous years’ results as they review corporate records. Other professionals try to avoid being anchored by prior information. Does a patient have a recurrence of last year’s inner ear disturbance, or is there a brain tumor this time?
Much of the charm in Kahneman’s book is in his admission of error—and the persistence of belief in the face of that admission. His account of testing soldiers for leadership roles in the Israeli army is a delight; the assessments prove worthless, but his team presses on anyway. His discovery of senior Israeli Air Force officers’ neglect of regression to the mean in assessing pilot performance—and in determining a proper reaction to pilot underperformance—could be applied across many disciplines. His encounters with prominent American money managers who reject evidence that their results are random will surprise few investors.
A reader will find that he wants to be tried by a judge who has had a good lunch, or graded by a professor who admires the first exam answer and proceeds directly to the others. Discussions of the sometimes overlapping phenomena of priming, cognitive ease, halo effects, focus, endowment effects, associative memory, representativeness, information availability and intensity, framing, and the classic gambles offered in studies of decision-making under uncertainty could lead even a confident reader to view his or her own decisions warily. Kahneman doesn’t exclude himself. After discussing Bernoulli’s errors and the Kahneman-Tversky breakthrough paper, “Prospect Theory: An Analysis of Decision Under Risk,” he notes that “theory-induced blindness” has led to scholars overlooking “some absurd consequences” in certain Prospect Theory assumptions. He suggests that Prospect Theory gives too little weight to the gambler’s anticipation of regret in explaining the rejection of statistically sound risks.
Thinking, Fast and Slow pays its due to the partnership with Tversky. If Amos had survived, Kahneman says more than once, he would clearly have shared the Nobel. But Thinking, Fast and Slow also encompasses work Kahneman has done subsequently, and with different research partners. And it plays with a metaphor, that we operate with two mental systems. System One is fast and uses information at hand, which is quite often adequate but sometimes isn’t. System Two is slow and methodical, far more critical and less apt to jump to conclusions, and it comes to work only when we demand its attention. The body of the Kahneman-Tversky partnership’s work demonstrates the value of this plodding and reluctant worker.
February 5 2017
November 27, 2021