The Undoing Project

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The Undoing Project Page 1

by Michael Lewis




  For Dacher Keltner

  My Chief Jungle Guide

  Doubt is not a pleasant condition, but certainty is an absurd one.

  —Voltaire

  CONTENTS

  Introduction:

  THE PROBLEM THAT NEVER GOES AWAY

  1

  MAN BOOBS

  2

  THE OUTSIDER

  3

  THE INSIDER

  4

  ERRORS

  5

  THE COLLISION

  6

  THE MIND’S RULES

  7

  THE RULES OF PREDICTION

  8

  GOING VIRAL

  9

  BIRTH OF THE WARRIOR PSYCHOLOGIST

  10

  THE ISOLATION EFFECT

  11

  THE RULES OF UNDOING

  12

  THIS CLOUD OF POSSIBILITY

  Coda:

  BORA-BORA

  A Note on Sources

  Acknowledgments

  The

  UNDOING

  PROJECT

  Introduction

  THE PROBLEM THAT NEVER GOES AWAY

  Back in 2003 I published a book, called Moneyball, about the Oakland Athletics’ quest to find new and better ways to value baseball players and evaluate baseball strategies. The team had less money to spend on players than other teams, and so its management, out of necessity, set about rethinking the game. In both new and old baseball data—and in the work of people outside the game who had analyzed that data—the Oakland front office discovered what amounted to new baseball knowledge. That knowledge allowed them to run circles around the managements of other baseball teams. They found value in players who had been discarded or overlooked, and folly in much of what passed for baseball wisdom. When the book appeared, some baseball experts—entrenched management, talent scouts, journalists—were upset and dismissive, but a lot of readers found the story as interesting as I had. A lot of people saw in Oakland’s approach to building a baseball team a more general lesson: If the highly paid, publicly scrutinized employees of a business that had existed since the 1860s could be misunderstood by their market, who couldn’t be? If the market for baseball players was inefficient, what market couldn’t be? If a fresh analytical approach had led to the discovery of new knowledge in baseball, was there any sphere of human activity in which it might not do the same?

  In the past decade or so, a lot of people have taken the Oakland A’s as their role model and set out to use better data, and better analysis of that data, to find market inefficiencies. I’ve read articles about Moneyball for Education, Moneyball for Movie Studios, Moneyball for Medicare, Moneyball for Golf, Moneyball for Farming, Moneyball for Book Publishing(!), Moneyball for Presidential Campaigns, Moneyball for Government, Moneyball for Bankers, and so on. “All of a sudden we’re ‘Moneyballing’ offensive linemen?” an offensive line coach for the New York Jets complained in 2012. After seeing the diabolically clever data-based approach taken by the North Carolina legislature in writing laws to make it more difficult for African Americans to vote, the comedian John Oliver congratulated the legislators for having “Money-balled racism.”

  But the enthusiasm for replacing old-school expertise with new-school data analysis was often shallow. When the data-driven approach to high-stakes decision making did not lead to immediate success—and, occasionally, even when it did—it was open to attack in a way that the old approach to decision making was not. In 2004, after aping Oakland’s approach to baseball decision making, the Boston Red Sox won their first World Series in nearly a century. Using the same methods, they won it again in 2007 and 2013. But in 2016, after three disappointing seasons, they announced that they were moving away from the data-based approach and back to one where they relied upon the judgment of baseball experts. (“We have perhaps overly relied on numbers . . . ,” said owner John Henry.) The writer Nate Silver for several years enjoyed breathtaking success predicting U.S. presidential election outcomes for the New York Times, using an approach to statistics he learned writing about baseball. For the first time in memory, a newspaper seemed to have an edge in calling elections. But then Silver left the Times, and failed to predict the rise of Donald Trump—and his data-driven approach to predicting elections was called into question . . . by the New York Times! “Nothing exceeds the value of shoe-leather reporting, given that politics is an essentially human endeavor and therefore can defy prediction and reason,” wrote a Times columnist, late in the spring of 2016. (Never mind that few shoe-leather reporters saw Trump coming, either, or that Silver later admitted that, because Trump seemed sui generis, he’d allowed an unusual amount of subjectivity to creep into his forecasts.)

  I’m sure some of the criticism of people who claim to be using data to find knowledge, and to exploit inefficiencies in their industries, has some truth to it. But whatever it is in the human psyche that the Oakland A’s exploited for profit—this hunger for an expert who knows things with certainty, even when certainty is not possible—has a talent for hanging around. It’s like a movie monster that’s meant to have been killed but is somehow always alive for the final act.

  And so, once the dust had settled on the responses to my book, one of them remained more alive and relevant than the others: a review by a pair of academics, then both at the University of Chicago—an economist named Richard Thaler and a law professor named Cass Sunstein. Thaler and Sunstein’s piece, which appeared on August 31, 2003, in the New Republic, managed to be at once both generous and damning. The reviewers agreed that it was interesting that any market for professional athletes might be so screwed-up that a poor team like the Oakland A’s could beat most rich teams simply by exploiting the inefficiencies. But—they went on to say—the author of Moneyball did not seem to realize the deeper reason for the inefficiencies in the market for baseball players: They sprang directly from the inner workings of the human mind. The ways in which some baseball expert might misjudge baseball players—the ways in which any expert’s judgments might be warped by the expert’s own mind—had been described, years ago, by a pair of Israeli psychologists, Daniel Kahneman and Amos Tversky. My book wasn’t original. It was simply an illustration of ideas that had been floating around for decades and had yet to be fully appreciated by, among others, me.

  That was an understatement. Until that moment I don’t believe I’d ever heard of either Kahneman or Tversky, even though one of them had somehow managed to win a Nobel Prize in economics. And I hadn’t actually thought much about the psychological aspects of the Moneyball story. The market for baseball players was rife with inefficiencies: why? The Oakland front office had talked about “biases” in the marketplace: Foot speed was overrated because it was so easy to see, for instance, and a hitter’s ability to draw walks was undervalued in part because walks were so forgettable—they seemed to require the hitter mainly to do nothing at all. Fat or misshapen players were more likely to be undervalued; handsome, fit players were more likely to be overvalued. All of these biases that the Oakland front office talked about I’d found interesting, but I hadn’t really pushed further and asked: Where do the biases come from? Why do people have them? I’d set out to tell a story about the way markets worked, or failed to work, especially when they were valuing people. But buried somewhere inside it was another story, one that I’d left unexplored and untold, about the way the human mind worked, or failed to work, when it was forming judgments and making decisions. When faced with uncertainty—about investments or people or anything else—how did it arrive at its conclusions? How did it process evidence—from a baseball game, an earnings report, a trial, a medical examination, or a speed date? What were people’s minds doing—even the minds of supposed experts—
that led them to the misjudgments that could be exploited for profit by others, who ignored the experts and relied on data?

  And how did a pair of Israeli psychologists come to have so much to say about these matters that they more or less anticipated a book about American baseball written decades in the future? What possessed two guys in the Middle East to sit down and figure out what the mind was doing when it tried to judge a baseball player, or an investment, or a presidential candidate? And how on earth does a psychologist win a Nobel Prize in economics? In the answers to those questions, it emerged, there was another story to tell. Here it is.

  1

  MAN BOOBS

  You never knew what a kid in the interview room might say to jolt you out of your slumber and back to your senses and force you to pay attention. And once you were paying attention, you naturally placed far greater weight on whatever he had just said than you probably should: The most memorable moments in job interviews for the National Basketball Association were hard to consign to some appropriately sized compartment in the brain. In certain cases it was as if the players were trying to screw up your ability to judge them. For instance, when the Houston Rockets interviewer asked one player if he could pass a drug test, the guy had gone wide-eyed and grabbed the table and said, “You mean today!!!???” There was the college player who’d been arrested on charges (subsequently dropped) of domestic violence, and whose agent claimed it had been a simple misunderstanding. When they’d asked the player about it he’d explained, chillingly, that he’d grown weary of his girlfriend’s “bitching, so I just put my hands around her neck and I squeezed. ’Cause I needed her to shut up.” There was Kenneth Faried, the power forward out of Morehead State. When he showed up for his interview they’d asked him, “Do you prefer to be called Kenneth or Kenny?” “Manimal,” Faried said. He wanted to be called Manimal. What did you do with that? Roughly three out of every four of the black American players who came for NBA interviews—or at least came for interviews with the NBA’s Houston Rockets—had never really known their father. “It’s not uncommon, when you ask these guys who their biggest male influence was, for them to say, ‘My mom,’” said the Rockets’ director of player personnel, Jimmy Paulis. “One said, ‘Obama.’”

  Then there was Sean Williams. Back in 2007 Sean Williams, six foot ten, was an off-the-charts player who had been suspended from his Boston College team the first two of his three seasons after being arrested for possession of marijuana (a charge that was later dropped). He’d played only fifteen games his sophomore year and still blocked 75 shots; the fans referred to his college games as The Sean Williams Block Party. Sean Williams looked like a big-time NBA player and was expected to be a first-round pick—in part because everyone assumed that his ability to get through his junior year without being suspended meant that he’d gotten his marijuana use under control. Before the 2007 NBA draft, he’d flown to Houston, at his agent’s request, to practice his interviewing skills. The agent cut the Rockets a deal: Williams would talk to the Rockets and the Rockets alone, and the Rockets would offer the agent tips about how to make Sean Williams more persuasive in a job interview. It actually went pretty well, until they got onto the topic of marijuana. “So you got caught smoking weed your freshman and sophomore years,” said the Rockets interviewer. “What happened your junior year?” Williams just shook his head and said, “They stopped testing me. And if you’re not going to test me, I’m gonna smoke!”

  After that, Williams’s agent decided it was best for Sean Williams not to grant any more interviews. He still got himself drafted in the first round by the New Jersey Nets, and made brief appearances in 137 NBA games before leaving to play in Turkey.

  Millions of dollars were at stake—NBA players were, on average, by far the highest-paid athletes in all of team sports. The future success of the Houston Rockets was on the line. These young people were hurling information about themselves at you that was meant to help you to make an employment decision. But a lot of times it was hard to know what to do with it.

  Rockets interviewer: What do you know about the Houston Rockets?

  Player: I know you are in Houston.

  Rockets interviewer: Which foot did you hurt?

  Player: I have been telling people my right foot.

  Player: Coach and I did not see eye to eye.

  Rockets interviewer: On what?

  Player: Playing time.

  Rockets interviewer: What else?

  Player: He was shorter.

  Ten years of grilling extremely tall people had reinforced in Daryl Morey, the general manager of the Houston Rockets, the sense that he should resist the power of any face-to-face interaction with some other person to influence his judgment. Job interviews were magic shows. He needed to fight whatever he felt during them—especially if he and everyone else in the room felt charmed. Extremely tall people had an unusual capacity to charm. “There’s a lot of charming bigs,” said Morey. “I don’t know if it’s like the fat kid on the playground or what.” The trouble wasn’t the charm but what the charm might mask: addictions, personality disorders, injuries, a deep disinterest in hard work. The bigs could bring you to tears with their story about their love of the game and the hardship they had overcome to play it. “They all have a story,” said Morey. “I could tell you a story about every guy.” And when the story was about perseverance in the face of incredible adversity, as it often was, it was hard not to grow attached to it. It was hard not to use it to create in your mind a clear picture of future NBA success.

  But Daryl Morey believed—if he believed in anything—in taking a statistically based approach to decision making. And the most important decision he made was whom to allow onto his basketball team. “Your mind needs to be in a constant state of defense against all this crap that is trying to mislead you,” he said. “We’re always trying to figure out what’s a trick and what’s real. Are we seeing a hologram? Is this an illusion?” These interviews belonged on the list of the crap trying to mislead you. “Here’s the biggest reason I want to be in every interview,” said Morey. “If we pick him, and he has some horrible problem and the owner asks, ‘What did he say in the interview when you asked him that question?’ and I go, ‘I never actually spoke to him before we gave him one point five million dollars,’ I get fired.”

  And so, in the winter of 2015, Morey, along with five members of his staff, sat in a conference room in Houston, Texas, waiting for another giant. The interview room contained nothing worth seeing. A conference table, some chairs, windows obscured by blinds. On the table rested a lone coffee mug, left by mistake, with a logo—National Sarcasm Society: Like We Need Your Support. The giant was . . . well, none of the men knew all that much about him except that he was still only nineteen years old, and that he was huge even by the standards of professional basketball. He’d been discovered five years earlier in a village in Punjab by some agent or talent scout—or so they’d been told. He was then fourteen years old, seven feet tall, and barefoot—or, at any rate, wearing shoes so tattered they revealed his feet.

  They’d wondered about that. The kid’s family must have been so poor that they couldn’t afford to buy him shoes. Or maybe they’d decided it was pointless to buy shoes for feet that grew so rapidly. Or maybe the whole thing was a fiction invented by an agent. Either way, what lingered in the mind was the image: a seven-foot-tall, fourteen-year-old-boy, barefoot in the streets of India. They didn’t know how the boy had found his way out of the Indian village. Somebody, probably an agent, had arranged for him to travel to the United States to learn how to speak English and play basketball.

  To the NBA he was a complete unknown. There was no video of the guy playing organized basketball. He hadn’t played, so far as the Rockets could determine. He hadn’t participated in the NBA Draft Combine, the formal audition for amateur players. It was only just that morning that the Rockets had been permitted to take his measurements. His feet were size
22, and his hands, from fingertip to wrist, were eleven and a half inches, the biggest hands the staff had ever measured. Shoeless, he stood seven foot two and weighed three hundred pounds, and his agent claimed he was still growing. He’d spent the past five years in southwest Florida learning basketball—most recently at IMG, a sports academy built to turn amateurs into professionals. Although no one they knew had seen him play, the few people who had laid eyes on him were still talking about it. Robert Upshaw, for instance. Upshaw was a thick seven-foot center who had been dismissed from his team at the University of Washington and was now auditioning for NBA teams. A few days earlier, in the Dallas Mavericks gym, he’d worked out with the Indian giant. Hearing from the Rockets scouts that he might be about to do it again, Upshaw’s eyes went wide and his face lit up and he said, “The dude is the biggest human being I’ve ever seen. And he can shoot the three-ball! It’s crazy.”

  * * *

  Back in 2006, when he was hired to run the Houston Rockets and figure out who should play pro basketball and who should not, Daryl Morey had been the first of his kind: the basketball nerd king. His job was to replace one form of decision making, which relied upon the intuition of basketball experts, with another, which relied mainly on the analysis of data. He had no serious basketball-playing experience and no interest in passing himself off as a jock or a basketball insider. He’d always been just the way he was, a person who was happier counting than feeling his way through life. As a kid he’d cultivated an interest in using data to make predictions until it became a ruling obsession. “That always seemed the coolest thing to me,” he said. “How do you use numbers to predict things? It was like a cool way to use numbers to be better than other people. And I really liked being better than other people.” He built forecasting models the way other kids built model airplanes. “It was always sports I was trying to predict. I didn’t know what else to apply it to—what, am I going to forecast my grades?”

 

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