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  When we know the rules and answers, and they don’t change over time—chess, golf, playing classical music—an argument can be made for savant-like hyperspecialized practice from day one. But those are poor models of most things humans want to learn.

  When narrow specialization is combined with an unkind domain, the human tendency to rely on experience of familiar patterns can backfire horribly—like the expert firefighters who suddenly make poor choices when faced with a fire in an unfamiliar structure. Chris Argyris, who helped create the Yale School of Management, noted the danger of treating the wicked world as if it is kind. He studied high-powered consultants from top business schools for fifteen years, and saw that they did really well on business school problems that were well defined and quickly assessed. But they employed what Argyris called single-loop learning, the kind that favors the first familiar solution that comes to mind. Whenever those solutions went wrong, the consultant usually got defensive. Argyris found their “brittle personalities” particularly surprising given that “the essence of their job is to teach others how to do things differently.”

  Psychologist Barry Schwartz demonstrated a similar, learned inflexibility among experienced practitioners when he gave college students a logic puzzle that involved hitting switches to turn light bulbs on and off in sequence, and that they could play over and over. It could be solved in seventy different ways, with a tiny money reward for each success. The students were not given any rules, and so had to proceed by trial and error.* If a student found a solution, they repeated it over and over to get more money, even if they had no idea why it worked. Later on, new students were added, and all were now asked to discover the general rule of all solutions. Incredibly, every student who was brand-new to the puzzle discovered the rule for all seventy solutions, while only one of the students who had been getting rewarded for a single solution did. The subtitle of Schwartz’s paper: “How Not to Teach People to Discover Rules”—that is, by providing rewards for repetitive short-term success with a narrow range of solutions.

  All this is bad news for some of the business world’s favorite successful-learning analogies—the Polgars, Tiger, and to some degree analogies based in any sport or game. Compared to golf, a sport like tennis is much more dynamic, with players adjusting to opponents every second, to surfaces, and sometimes to their own teammates. (Federer was a 2008 Olympic gold medalist in doubles.) But tennis is still very much on the kind end of the spectrum compared to, say, a hospital emergency room, where doctors and nurses do not automatically find out what happens to a patient after their encounter. They have to find ways to learn beyond practice, and to assimilate lessons that might even contradict their direct experience.

  The world is not golf, and most of it isn’t even tennis. As Robin Hogarth put it, much of the world is “Martian tennis.” You can see the players on a court with balls and rackets, but nobody has shared the rules. It is up to you to derive them, and they are subject to change without notice.

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  • • •

  We have been using the wrong stories. Tiger’s story and the Polgar story give the false impression that human skill is always developed in an extremely kind learning environment. If that were the case, specialization that is both narrow and technical and that begins as soon as possible would usually work. But it doesn’t even work in most sports.

  If the amount of early, specialized practice in a narrow area were the key to innovative performance, savants would dominate every domain they touched, and child prodigies would always go on to adult eminence. As psychologist Ellen Winner, one of the foremost authorities on gifted children, noted, no savant has ever been known to become a “Big-C creator,” who changed their field.

  There are domains beyond chess in which massive amounts of narrow practice make for grandmaster-like intuition. Like golfers, surgeons improve with repetition of the same procedure. Accountants and bridge and poker players develop accurate intuition through repetitive experience. Kahneman pointed to those domains’ “robust statistical regularities.” But when the rules are altered just slightly, it makes experts appear to have traded flexibility for narrow skill. In research in the game of bridge where the order of play was altered, experts had a more difficult time adapting to new rules than did nonexperts. When experienced accountants were asked in a study to use a new tax law for deductions that replaced a previous one, they did worse than novices. Erik Dane, a Rice University professor who studies organizational behavior, calls this phenomenon “cognitive entrenchment.” His suggestions for avoiding it are about the polar opposite of the strict version of the ten-thousand-hours school of thought: vary challenges within a domain drastically, and, as a fellow researcher put it, insist on “having one foot outside your world.”

  Scientists and members of the general public are about equally likely to have artistic hobbies, but scientists inducted into the highest national academies are much more likely to have avocations outside of their vocation. And those who have won the Nobel Prize are more likely still. Compared to other scientists, Nobel laureates are at least twenty-two times more likely to partake as an amateur actor, dancer, magician, or other type of performer. Nationally recognized scientists are much more likely than other scientists to be musicians, sculptors, painters, printmakers, woodworkers, mechanics, electronics tinkerers, glassblowers, poets, or writers, of both fiction and nonfiction. And, again, Nobel laureates are far more likely still. The most successful experts also belong to the wider world. “To him who observes them from afar,” said Spanish Nobel laureate Santiago Ramón y Cajal, the father of modern neuroscience, “it appears as though they are scattering and dissipating their energies, while in reality they are channeling and strengthening them.” The main conclusion of work that took years of studying scientists and engineers, all of whom were regarded by peers as true technical experts, was that those who did not make a creative contribution to their field lacked aesthetic interests outside their narrow area. As psychologist and prominent creativity researcher Dean Keith Simonton observed, “rather than obsessively focus[ing] on a narrow topic,” creative achievers tend to have broad interests. “This breadth often supports insights that cannot be attributed to domain-specific expertise alone.”

  Those findings are reminiscent of a speech Steve Jobs gave, in which he famously recounted the importance of a calligraphy class to his design aesthetics. “When we were designing the first Macintosh computer, it all came back to me,” he said. “If I had never dropped in on that single course in college, the Mac would have never had multiple typefaces or proportionally spaced fonts.” Or electrical engineer Claude Shannon, who launched the Information Age thanks to a philosophy course he took to fulfill a requirement at the University of Michigan. In it, he was exposed to the work of self-taught nineteenth-century English logician George Boole, who assigned a value of 1 to true statements and 0 to false statements and showed that logic problems could be solved like math equations. It resulted in absolutely nothing of practical importance until seventy years after Boole passed away, when Shannon did a summer internship at AT&T’s Bell Labs research facility. There he recognized that he could combine telephone call-routing technology with Boole’s logic system to encode and transmit any type of information electronically. It was the fundamental insight on which computers rely. “It just happened that no one else was familiar with both those fields at the same time,” Shannon said.

  In 1979, Christopher Connolly cofounded a psychology consultancy in the United Kingdom to help high achievers (initially athletes, but then others) perform at their best. Over the years, Connolly became curious about why some professionals floundered outside a narrow expertise, while others were remarkably adept at expanding their careers—moving from playing in a world-class orchestra, for example, to running one. Thirty years after he started, Connolly returned to school to do a PhD investigating that very question, under Fernand Gobet, the psychologist and chess international ma
ster. Connolly’s primary finding was that early in their careers, those who later made successful transitions had broader training and kept multiple “career streams” open even as they pursued a primary specialty. They “traveled on an eight-lane highway,” he wrote, rather than down a single-lane one-way street. They had range. The successful adapters were excellent at taking knowledge from one pursuit and applying it creatively to another, and at avoiding cognitive entrenchment. They employed what Hogarth called a “circuit breaker.” They drew on outside experiences and analogies to interrupt their inclination toward a previous solution that may no longer work. Their skill was in avoiding the same old patterns. In the wicked world, with ill-defined challenges and few rigid rules, range can be a life hack.

  Pretending the world is like golf and chess is comforting. It makes for a tidy kind-world message, and some very compelling books. The rest of this one will begin where those end—in a place where the popular sport is Martian tennis, with a view into how the modern world became so wicked in the first place.

  CHAPTER 2

  How the Wicked World Was Made

  THE TOWN OF DUNEDIN sits at the base of a hilly peninsula that juts off of New Zealand’s South Island into the South Pacific. The peninsula is famous for yellow-eyed penguins, and Dunedin boasts, demurely, the world’s steepest residential street. It also features the University of Otago, the oldest university in New Zealand, and home to James Flynn, a professor of political studies who changed how psychologists think about thinking.

  He started in 1981, intrigued by a thirty-year-old paper that reported IQ test scores of American soldiers in World Wars I and II. The World War II soldiers had performed better, by a lot. A World War I soldier who scored smack in the middle of his peers—the 50th percentile—would have made only the 22nd percentile compared to soldiers in World War II. Flynn wondered if perhaps civilians had experienced a similar improvement. “I thought, if IQ gains had occurred anywhere,” he told me, “maybe they had occurred everywhere.” If he was right, psychologists had been missing something big right before their eyes.

  Flynn wrote to researchers in other countries asking for data, and on a dull November Saturday in 1984, he found a letter in his university mailbox. It was from a Dutch researcher, and it contained years of raw data from IQ tests given to young men in the Netherlands. The data were from a test known as Raven’s Progressive Matrices, designed to gauge the test taker’s ability to make sense of complexity. Each question of the test shows a set of abstract designs with one design missing. The test taker must try to fill in the missing design to complete a pattern. Raven’s was conceived to be the epitome of a “culturally reduced” test; performance should be unaffected by material learned in life, inside or outside of school. Should Martians alight on Earth, Raven’s should be the test capable of determining how bright they are. And yet Flynn could immediately see that young Dutchmen had made enormous gains from one generation to the next.

  Flynn found more clues in test reference manuals. IQ tests are all standardized so that the average score is always 100 points. (They are graded based on a curve, with 100 in the middle.) Flynn noticed that the tests had to be restandardized from time to time to keep the average at 100, because test takers were giving more correct answers than they had in the past. In the twelve months after he received the Dutch letter, Flynn collected data from fourteen countries. Every single one showed huge gains for both children and adults. “Our advantage over our ancestors,” as he put it, is “from the cradle to the grave.”

  Flynn had asked the right question. Score gains had occurred everywhere. Other academics had stumbled upon pieces of the same data earlier, but none had investigated whether it was part of a global pattern, even those who were having to tweak the test scoring system to keep the average at 100. “As an outsider,” Flynn told me, “things strike me as surprising that I think people trained in psychometrics just accepted.”

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  • • •

  The Flynn effect—the increase in correct IQ test answers with each new generation in the twentieth century—has now been documented in more than thirty countries. The gains are startling: three points every ten years. To put that in perspective, if an adult who scored average today were compared to adults a century ago, she would be in the 98th percentile.

  When Flynn published his revelation in 1987, it hit the community of researchers who study cognitive ability like a firebomb. The American Psychological Association convened an entire meeting on the issue, and psychologists invested in the immutable nature of IQ test scores offered an array of explanations to usher the effect away, from more education and better nutrition—which presumably contributed—to test-taking experience, but none fit the unusual pattern of score improvements. On tests that gauged material picked up in school or with independent reading or study—general knowledge, arithmetic, vocabulary—scores hardly budged. Meanwhile, performance on more abstract tasks that are never formally taught, like the Raven’s matrices, or “similarities” tests, which require a description of how two things are alike, skyrocketed.

  A young person today asked to give similarities between “dusk” and “dawn” might immediately realize that both connote times of day. But they would be far more likely than their grandmothers to produce a higher-level similarity: both separate day from night. A child today who scores average on similarities would be in the 94th percentile of her grandparents’ generation. When a group of Estonian researchers used national test scores to compare word understandings of schoolkids in the 1930s to those in 2006, they saw that improvement came very specifically on the most abstract words. The more abstract the word, the bigger the improvement. The kids barely bested their grandparents on words for directly observable objects or phenomena (“hen,” “eating,” “illness”), but they improved massively on imperceptible concepts (“law,” “pledge,” “citizen”).

  The gains around the world on Raven’s Progressive Matrices—where change was least expected—were the biggest of all. “The huge Raven’s gains show that today’s children are far better at solving problems on the spot without a previously learned method for doing so,” Flynn concluded. They are more able to extract rules and patterns where none are given. Even in countries that have recently had a decrease in verbal and math IQ test scores, Raven’s scores went up. The cause, it seemed, was some ineffable thing in modern air. Not only that, but the mystery air additive somehow supercharged modern brains specifically for the most abstract tests. What manner of change, Flynn wondered, could be at once so large and yet so particular?

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  • • •

  Through the late 1920s and early 1930s, remote reaches of the Soviet Union were forced through social and economic changes that would normally take generations. Individual farmers in isolated areas of what is now Uzbekistan had long survived by cultivating small gardens for food, and cotton for everything else. Nearby in the mountain pasturelands of present-day Kyrgyzstan, herders kept animals. The population was entirely illiterate, and a hierarchical social structure was enforced by strict religious rules. The socialist revolution dismantled that way of life almost overnight.

  The Soviet government forced all that agricultural land to become large collective farms and began industrial development. The economy quickly became interconnected and complex. Farmers had to form collective work strategies, plan ahead for production, divvy up functions, and assess work along the way. Remote villages began communicating with distant cities. A network of schools opened in regions with 100 percent illiteracy, and adults began learning a system of matching symbols to sounds. Villagers had used numbers before, but only in practical transactions. Now they were taught the concept of a number as an abstraction that existed even without reference to counting animals or apportioning food. Some village women remained fully illiterate but took short courses on how to teach kindergartners. Other women were admitted for longer study at a teachers’ school. Classes
in preschool education and the science and technology of agriculture were offered to students who had no formal education of any kind. Secondary schools and technical institutes soon followed. In 1931, amid that incredible transformation, a brilliant young Russian psychologist named Alexander Luria recognized a fleeting “natural experiment,” unique in the history of the world. He wondered if changing citizens’ work might also change their minds.

  When Luria arrived, the most remote villages had not yet been touched by the warp-speed restructuring of traditional society. Those villages gave him a control group. He learned the local language and brought fellow psychologists to engage villagers in relaxed social situations—teahouses or pastures—and discuss questions or tasks designed to discern their habits of mind.

  Some were very simple: present skeins of wool or silk in an array of hues and ask participants to describe them. The collective farmers and farm leaders, as well as the female students, easily picked out blue, red, and yellow, sometimes with variations, like dark blue or light yellow. The most remote villagers, who were still “premodern,” gave more diversified descriptions: cotton in bloom, decayed teeth, a lot of water, sky, pistachio. Then they were asked to sort the skeins into groups. The collective farmers, and young people with even a little formal education, did so easily, naturally forming color groups. Even when they did not know the name of a particular color, they had little trouble putting together darker and lighter shades of the same one. The remote villagers, on the other hand, refused, even those whose work was embroidery. “It can’t be done,” they said, or, “None of them are the same, you can’t put them together.” When prodded vigorously, and only if they were allowed to make many small groups, some relented and created sets that were apparently random. A few others appeared to sort the skeins according to color saturation, without regard to the color.