June 8, 2021

Range: Why Generalists Triumph in a Specialised World by David Epstein | Book Notes

Introduction

  • Tiger was not merely playing golf. He was engaging in “deliberate practice,” the only kind that counts in the now-ubiquitous ten-thousand-hours rule to expertise.
  • The “rule” represents the idea that the number of accumulated hours of highly specialized training is the sole factor in skill development, no matter the domain.
  • Deliberate practice, according to the study of thirty violinists that spawned the rule, occurs when learners are “given explicit instructions about the best method,” individually supervised by an instructor, supplied with “immediate informative feedback and knowledge of the results of their performance,” and “repeatedly perform the same or similar tasks.”
  • Tiger has come to symbolize the idea that the quantity of deliberate practice determines success—and its corollary, that the practice must start as early as possible.
  • We are often taught that the more competitive and complicated the world gets, the more specialized we all must become (and the earlier we must start) to navigate it.
  • Oncologists no longer specialize in cancer, but rather in cancer related to a single organ, and the trend advances each year.
  • In the ten-thousand-hours-themed bestseller Bounce, British journalist Matthew Syed suggested that the British government was failing for a lack of following the Tiger Woods path of unwavering specialization. Moving high-ranking government officials between departments, he wrote, “is no less absurd than rotating Tiger Woods from golf to baseball to football to hockey.”
  • Apparently the idea of an athlete, even one who wants to become elite, following a Roger path and trying different sports is not so absurd.
  • Eventual elites typically devote less time early on to deliberate practice in the activity in which they will eventually become experts. Instead, they undergo what researchers call a “sampling period.” They play a variety of sports, usually in an unstructured or lightly structured environment; they gain a range of physical proficiencies from which they can draw; they learn about their own abilities and proclivities; and only later do they focus in and ramp up technical practice in one area.
  • The title of one study of athletes in individual sports proclaimed “Late Specialization” as “the Key to Success”; another, “Making It to the Top in Team Sports: Start Later, Intensify, and Be Determined.”
  • In reality, the Roger path to sports stardom is far more prevalent than the Tiger path, but those athletes’ stories are much more quietly told, if they are told at all.
  • it takes time—and often forgoing a head start—to develop personal and professional range, but it is worth it.
  • highly credentialed experts can become so narrow-minded that they actually get worse with experience, even while becoming more confident—a dangerous combination.
  • learning itself is best done slowly to accumulate lasting knowledge, even when that means performing poorly on tests of immediate progress. That is, the most effective learning looks inefficient; it looks like falling behind.
  • increasing specialization has created a “system of parallel trenches” in the quest for innovation. Everyone is digging deeper into their own trench and rarely standing up to look in the next trench over, even though the solution to their problem happens to reside there.
  • The challenge we all face is how to maintain the benefits of breadth, diverse experience, interdisciplinary thinking, and delayed concentration in a world that increasingly incentivizes, even demands, hyperspecialization.
  • we also need more Rogers: people who start broad and embrace diverse experiences and perspectives while they progress. People with range.

CHAPTER 1: The Cult of the Head Start

  • Laszlo’s experiment had worked. It worked so well that in the early 1990s he suggested that if his early specialization approach were applied to a thousand children, humanity could tackle problems like cancer and AIDS.
  • The bestseller Talent Is Overrated used the Polgar sisters and Tiger Woods as proof that a head start in deliberate practice is the key to success in “virtually any activity that matters to you.”
  • Psychologist Gary Klein is a pioneer of the “naturalistic decision making” (NDM) model of expertise;
  • NDM researchers observe expert performers in their natural course of work to learn how they make high-stakes decisions under time pressure. Klein has shown that experts in an array of fields are remarkably similar to chess masters in that they instinctively recognize familiar patterns.
  • When I asked Garry Kasparov, perhaps the greatest chess player in history, to explain his decision process for a move, he told me, “I see a move, a combination, almost instantly,” based on patterns he has seen before.
  • Klein studied firefighting commanders and estimated that around 80 percent of their decisions are also made instinctively and in seconds. After years of firefighting, they recognize repeating patterns in the behavior of flames and of burning buildings on the verge of collapse.
  • One of Klein’s colleagues, psychologist Daniel Kahneman, studied human decision making from the “heuristics and biases” model of human judgment. His findings could hardly have been more different from Klein’s. When Kahneman probed the judgments of highly trained experts, he often found that experience had not helped at all. Even worse, it frequently bred confidence but not skill.
  • In those domains, which involved human behavior and where patterns did not clearly repeat, repetition did not cause learning. Chess, golf, and firefighting are exceptions, not the rule.
  • Do specialists get better with experience, or not?
  • Whether or not experience inevitably led to expertise, they agreed, depended entirely on the domain in question.
  • The domains Klein studied, in which instinctive pattern recognition worked powerfully, are what psychologist Robin Hogarth termed “kind” learning environments. Patterns repeat over and over, and feedback is extremely accurate and usually very rapid.
  • The learning environment is kind because a learner improves simply by engaging in the activity and trying to do better.
  • In wicked domains, the rules of the game are often unclear or incomplete, there may or may not be repetitive patterns and they may not be obvious, and feedback is often delayed, inaccurate, or both.
  • Few learning environments are that wicked, but it doesn’t take much to throw experienced pros off course. Expert firefighters, when faced with a new situation, like a fire in a skyscraper, can find themselves suddenly deprived of the intuition formed in years of house fires, and prone to poor decisions. With a change of the status quo, chess masters too can find that the skill they took years to build is suddenly obsolete.
  • Moravec’s paradox: machines and humans frequently have opposite strengths and weaknesses.
  • There is a saying that “chess is 99 percent tactics.” Tactics are short combinations of moves that players use to get an immediate advantage on the board.
  • Bigger-picture planning in chess—how to manage the little battles to win the war—is called strategy.
  • Kasparov did figure out a way to beat the computer: by outsourcing tactics, the part of human expertise that is most easily replaced, the part that he and the Polgar prodigies spent years honing.
  • Through repetitive study of game patterns, they had learned to do what Chase and Simon called “chunking.” Rather than struggling to remember the location of every individual pawn, bishop, and rook, the brains of elite players grouped pieces into a smaller number of meaningful chunks based on familiar patterns.
  • Chunking helps explain instances of apparently miraculous, domain-specific memory, from musicians playing long pieces by heart to quarterbacks recognizing patterns of players in a split second and making a decision to throw.
  • Studying an enormous number of repetitive patterns is so important in chess that early specialization in technical practice is critical.
  • Psychologists Fernand Gobet (an international master) and Guillermo Campitelli (coach to future grandmasters) found that the chances of a competitive chess player reaching international master status (a level down from grandmaster) dropped from one in four to one in fifty-five if rigorous training had not begun by age twelve.
  • Chunking can seem like magic, but it comes from extensive, repetitive practice.
  • the bigger the picture, the more unique the potential human contribution.
  • Our greatest strength is the exact opposite of narrow specialization. It is the ability to integrate broadly.
  • “The difference between winning at Jeopardy! and curing all cancer is that we know the answer to Jeopardy! questions.”
  • “AI systems are like savants.” They need stable structures and narrow worlds.
  • 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.
  • When narrow specialization is combined with an unkind domain, the human tendency to rely on experience of familiar patterns can backfire horribly
  • 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.
  • 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.
  • “cognitive entrenchment.”
  • As psychologist and prominent creativity researcher Dean Keith Simonton observed, “rather than obsessively focusing 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.”
  • “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.”
  • “It just happened that no one else was familiar with both those fields at the same time,”
  • 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.
  • Martian tennis,

CHAPTER 2: How the Wicked World Was Made

  • Raven’s Progressive Matrices
  • 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.
  • 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.
  • “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.
  • In Flynn’s terms, we now see the world through “scientific spectacles.” He means that rather than relying on our own direct experiences, we make sense of reality through classification schemes, using layers of abstract concepts to understand how pieces of information relate to one another.
  • In the progress bar on your computer screen that fills up to indicate a download, abstractions are legion, from the fundamental—the programming language that created it is a representation of binary code, the raw 1s and 0s the computer uses—to the psychological: the bar is a visual projection of time that provides peace of mind by estimating the progress of an immense number of underlying activities.
  • Conceptual schemes are flexible, able to arrange information and ideas for a wide variety of uses, and to transfer knowledge between domains.
  • Modern work demands knowledge transfer: the ability to apply knowledge to new situations and different domains.
  • Exposure to the modern world has made us better adapted for complexity, and that has manifested as flexibility, with profound implications for the breadth of our intellectual world.
  • As Arab historiographer Ibn Khaldun, considered a founder of sociology, pointed out centuries ago, a city dweller traveling through the desert will be completely dependent on a nomad to keep him alive. So long as they remain in the desert, the nomad is a genius.
  • But it is certainly true that modern life requires range, making connections across far-flung domains and ideas.
  • The ability to move freely, to shift from one category to another, is one of the chief characteristics of ‘abstract thinking.’”
  • Flynn’s great disappointment is the degree to which society, and particularly higher education, has responded to the broadening of the mind by pushing specialization, rather than focusing early training on conceptual, transferable knowledge.
  • In Flynn’s words, “the traits that earn good grades at the university do not include critical ability of any broad significance.”
  • Flynn’s conclusion: “There is no sign that any department attempts to develop anything other than narrow critical competence.”
  • everyone needs habits of mind that allow them to dance across disciplines.
  • Chicago has long prided itself on a core curriculum dedicated to interdisciplinary critical thinking. The two-year core, according to the university, “is intended as an introduction to the tools of inquiry used in every discipline—science, mathematics, humanities, and social sciences.
  • scientific-reasoning Swiss Army knife.
  • Three-quarters of American college graduates go on to a career unrelated to their major—a trend that includes math and science majors—after having become competent only with the tools of a single discipline.
  • One good tool is rarely enough in a complex, interconnected, rapidly changing world.
  • “No tool is omnicompetent.”
  • As statistician Doug Altman put it, “Everyone is so busy doing research they don’t have time to stop and think about the way they’re doing it.”
  • “How many piano tuners are there in New York City?”
  • The professor later explained that these were “Fermi problems,”
  • detailed prior knowledge was less important than a way of thinking.
  • Fermi thinking regularly, breaking down a problem so I can leverage what little I know to start investigating what I don’t, a “similarities” problem of sorts.
  • “how Fermi estimation can cut through bullshit like a hot knife through butter.”
  • They were perfectly capable of learning from experience, but failed at learning without experience.
  • And that is what a rapidly changing, wicked world demands—conceptual reasoning skills that can connect new ideas and work across contexts.
  • The more constrained and repetitive a challenge, the more likely it will be automated, while great rewards will accrue to those who can take conceptual knowledge from one problem or domain and apply it in an entirely new one.

CHAPTER 3: When Less of the Same Is More

  • Virtuosos, the original musical celebrities,
  • The concerto was born—in which a virtuoso soloist plays back and forth against an orchestra—and Venetian composer Antonio Vivaldi (known as il Prete Rosso, the Red Priest, for his flame-red hair) became the form’s undisputed champion.
  • Vivaldi’s creativity was facilitated by a particular group of musicians who could learn new music quickly on a staggering array of instruments.
  • cast known as the figlie del coro, literally, “daughters of the choir.”
  • The ospedali commissioned composers for original works. Over one six-year period, Vivaldi wrote 140 concertos exclusively for the Pietà musicians.
  • It all raises the question: Just what magical training mechanism was deployed to transform the orphan foundlings of the Venetian sex industry, who but for the grace of charity would have died in the city’s canals, into the world’s original international rock stars?
  • The Pieta’s musicians loved to show off their versatility.
  • Audience members commonly remarked on the wide range of instruments the figlie could play, or on their surprise at seeing a virtuosa singer come out during intermission to improvise an instrumental solo.
  • According to musicologist Marc Pincherle, in the multiskilled figlie and their menagerie of instruments, “Vivaldi had at his disposal a musical laboratory of unlimited resources.”
  • The figlie’s skills on a vast array of instruments enabled musical experimentation so profound that it laid a foundation for the modern orchestra.
  • Today, the massively multi-instrument approach seems to go against everything we know about how to get good at a skill like playing music. It certainly goes against the deliberate practice framework, which only counts highly focused attempts at exactly the skill to be performed.
  • litany
  • Parents in online forums agonize over what instrument to pick for their child, because the child is too young to pick for herself and will fall irredeemably behind if she waits.
  • In response to such concerns, the director of a private music school wrote a “how to choose” advice column with tips for picking an instrument for a child who can’t yet stick with the same favorite color from one week to the next.
  • sampling period
  • The sampling period is not incidental to the development of great performers—something to be excised in the interest of a head start—it is integral.
  • The students who would go on to be most successful only started practicing much more once they identified an instrument they wanted to focus on, whether because they were better at it or just liked it more.
  • “It seems very clear,” the psychologists wrote, “that sheer amount of lesson or practice time is not a good indicator of exceptionality.”
  • “The strong implication,” the researchers wrote, is “that that too many lessons at a young age may not be helpful.”
  • Those children identified as exceptional by the school turn out to be those children who distributed their effort more evenly across three instruments.”
  • The Cambridge Handbook of Expertise and Expert Performance, published in 2006, is a sort of bible for popular writers, speakers, and researchers in the ten-thousand-hours school.
  • The strict deliberate practice school describes useful training as focused consciously on error correction.
  • Charles Limb, a musician, hearing specialist, and auditory surgeon at the University of California, San Francisco, designed an iron-free keyboard so that jazz musicians could improvise while inside an MRI scanner. Limb saw that brain areas associated with focused attention, inhibition, and self-censoring turned down when the musicians were creating. “It’s almost as if the brain turned off its own ability to criticize itself,” he told National Geographic. While improvising, musicians do pretty much the opposite of consciously identifying errors and stopping to correct them.
  • “It’s easier for a jazz musician to learn to play classical literature than for a classical player to learn how to play jazz,” he said. “The jazz musician is a creative artist, the classical musician is a re-creative artist.”
  • In totality, the picture is in line with a classic research finding that is not specific to music: breadth of training predicts breadth of transfer. That is, the more contexts in which something is learned, the more the learner creates abstract models, and the less they rely on any particular example.
  • Learners become better at applying their knowledge to a situation they’ve never seen before, which is the essence of creativity.
  • In offering advice to parents, psychologist Adam Grant noted that creativity may be difficult to nurture, but it is easy to thwart.
  • I think when you’re self-taught you experiment more, trying to find the same sound in different places, you learn how to solve problems.”

CHAPTER 4: Learning, Fast and Slow

  • That was one American class period out of hundreds in the United States, Asia, and Europe that were filmed and analyzed in an effort to understand effective math teaching.
  • In every classroom in every country, teachers relied on two main types of questions.
  • The more common were “using procedures” questions: basically, practice at something that was just learned.
  • The other common variety was “making connections” questions, which connected students to a broader concept, rather than just a procedure.
  • Rather than letting students grapple with some confusion, teachers often responded to their solicitations with hint-giving that morphed a making-connections problem into a using-procedures one.
  • When the students were playing multiple choice with the teacher, “what they’re actually doing is seeking rules.” They were trying to turn a conceptual problem they didn’t understand into a procedural one they could just execute.
  • Making-connections problems did not survive the teacher-student interactions.
  • In Japan, a little more than half of all problems were making-connections problems, and half of those stayed that way through the solving.
  • When a student offered an idea for how to approach a problem, rather than engaging in multiple choice, the teacher had them come to the board and put a magnet with their name on it next to the idea.
  • (There is a specific Japanese word to describe chalkboard writing that tracks conceptual connections over the course of collective problem solving: bansho.)
  • “Students do not view mathematics as a system,” Richland and her colleagues wrote. They view it as just a set of procedures.
  • Some of the college students seemed to have unlearned number sense that most children have, like that adding two numbers gives you a third comprised of the first two. A student who was asked to verify that 462 + 253 = 715, subtracted 253 from 715, and got 462. When he was asked for another strategy, he could not come up with subtracting 462 from 715 to see that it equals 253, because the rule he learned was to subtract the number to the right of the plus sign to check the answer.
  • But for learning that is both durable (it sticks) and flexible (it can be applied broadly), fast and easy is precisely the problem.
  • Kornell was explaining the concept of “desirable difficulties,” obstacles that make learning more challenging, slower, and more frustrating in the short term, but better in the long term.
  • One of those desirable difficulties is known as the “generation effect.”
  • Struggling to generate an answer on your own, even a wrong one, enhances subsequent learning.
  • Metcalfe and colleagues have repeatedly demonstrated a “hypercorrection effect.” The more confident a learner is of their wrong answer, the better the information sticks when they subsequently learn the right answer. Tolerating big mistakes can create the best learning opportunities.
  • The overall experiment results went like this: the more hints that were available during training, the better the monkeys performed during early practice, and the worse they performed on test day.
  • The study conclusion was simple: “training with hints did not produce any lasting learning.”
  • Struggling to retrieve information primes the brain for subsequent learning, even when the retrieval itself is unsuccessful. The struggle is real, and really useful. “Like life,” Kornell and team wrote, “retrieval is all about the journey.”
  • Like a lot of professional development efforts, each particular concept or skill gets a short period of intense focus, and then on to the next thing, never to return.
  • That structure makes intuitive sense, but it forgoes another important desirable difficulty: “spacing,” or distributed practice.
  • It is what it sounds like—leaving time between practice sessions for the same material. You might call it deliberate not-practicing between bouts of deliberate practice.
  • Space between practice sessions creates the hardness that enhances learning.
  • For a given amount of Spanish study, spacing made learning more productive by making it easy to make it hard.
  • Repetition, it turned out, was less important than struggle.
  • As with excessive hint-giving, it will, as a group of psychologists put it, “produce misleadingly high levels of immediate mastery that will not survive the passage of substantial periods of time.”
  • In 2007, the U.S. Department of Education published a report by six scientists and an accomplished teacher who were asked to identify learning strategies that truly have scientific backing. Spacing, testing, and using making-connections questions were on the extremely short list. All three impair performance in the short term.
  • “Professors who excel at promoting contemporaneous student achievement,” the economists wrote, “on average, harm the subsequent performance of their students in more advanced classes.” What looked like a head start evaporated.
  • The economists suggested that the professors who caused short-term struggle but long-term gains were facilitating “deep learning” by making connections. They “broaden the curriculum and produce students with a deeper understanding of the material.”
  • Tellingly, Calculus I students whose teachers had fewer qualifications and less experience did better in that class, while the students of more experienced and qualified teachers struggled in Calculus I but did better in subsequent courses.
  • A similar study was conducted at Italy’s Bocconi University, on twelve hundred first-year students who were randomized into introductory course sections in management, economics, or law, and then the courses that followed them in a prescribed sequence over four years. It showed precisely the same pattern. Teachers who guided students to overachievement in their own course were rated highly, and undermined student performance in the long run.
  • Psychologist Robert Bjork first used the phrase “desirable difficulties” in 1994.
  • “Above all, the most basic message is that teachers and students must avoid interpreting current performance as learning.
  • Focusing on “using procedures” problems worked well forty years ago when the world was flush with jobs that paid middle-class salaries for procedural tasks, like typing, filing, and working on an assembly line.
  • “jobs that pay well require employees to be able to solve unexpected problems, often while working in groups. . . . These shifts in labor force demands have in turn put new and increasingly stringent demands on schools.”
  • Knowledge increasingly needs not merely to be durable, but also flexible—both sticky and capable of broad application.
  • Toward the end of the eighth-grade math class that I watched with Lindsey Richland, the students settled into a worksheet for what psychologists call “blocked” practice. That is, practicing the same thing repeatedly, each problem employing the same procedure.
  • for knowledge to be flexible, it should be learned under varied conditions, an approach called varied or mixed practice, or, to researchers, “interleaving.”
  • Interleaving has been shown to improve inductive reasoning. When presented with different examples mixed together, students learn to create abstract generalizations that allow them to apply what they learned to material they have never encountered before.
  • The blocked-practice students learned procedures for each type of problem through repetition. The mixed-practice (interleaving) students learned how to differentiate types of problems.
  • The feeling of learning, it turns out, is based on before-your-eyes progress, while deep learning is not. “When your intuition says block,” Kornell told me, “you should probably interleave.”
  • Interleaving is a desirable difficulty that frequently holds for both physical and mental skills.
  • Whether the task is mental or physical, interleaving improves the ability to match the right strategy to a problem. That happens to be a hallmark of expert problem solving.
  • Whether chemists, physicists, or political scientists, the most successful problem solvers spend mental energy figuring out what type of problem they are facing before matching a strategy to it, rather than jumping in with memorized procedures.
  • Desirable difficulties like testing and spacing make knowledge stick. It becomes durable.
  • Desirable difficulties like making connections and interleaving make knowledge flexible, useful for problems that never appeared in training.
  • As with all desirable difficulties, the trouble is that a head start comes fast, but deep learning is slow. “The slowest growth,” the researchers wrote, occurs “for the most complex skills.”
  • When a knowledge structure is so flexible that it can be applied effectively even in new domains or extremely novel situations, it is called “far transfer.”

CHAPTER 5: Thinking Outside Experience

  • More important, Kepler invented astrophysics.
  • It is a truism to say that Kepler thought outside the box. But what he really did, whenever he was stuck, was to think entirely outside the domain.
  • “I especially love analogies,” he wrote, “my most faithful masters, acquainted with all the secrets of nature. . . . One should make great use of them.”

....

Dedre Gentner is a Northwestern University psychologist. She is probably world's foremost authority on analogical thinking.

  • Deep analogical thinking is the practice of recognizing conceptual similarities in multiple domains or scenarios that may seem to have little in common on the surface.
  • “In my opinion,” Gentner told me, “our ability to think relationally is one of the reasons we’re running the planet. Relations are really hard for other species.”
  • Analogical thinking takes the new and makes it familiar, or takes the familiar and puts it in a new light, and allows humans to reason through problems they have never seen in unfamiliar contexts.
  • Students might learn about the motion of molecules by analogy to billiard-ball collisions; principles of electricity can be understood with analogies to water flow through plumbing. Concepts from biology serve as analogies to inform the cutting edge of artificial intelligence: “neural networks” that learn how to identify images from examples (when you search cat pictures, for instance) were conceived as akin to the neurons of the brain, and “genetic algorithms” are conceptually based on evolution by natural selection—solutions are tried, evaluated, and the more successful solutions pass on properties to the next round of solutions, ad infinitum.
  • Most problems, of course, are not new, so we can rely on what Gentner calls “surface” analogies from our own experience. “Most of the time, if you’re reminded of things that are similar on the surface, they’re going to be relationally similar as well,”
  • The current world is not so kind; it requires thinking that cannot fall back on previous experience.
  • “In the life we lead today,” Gentner told me, “we need to be reminded of things that are only abstractly or relationally similar. And the more creative you want to be, the more important that is.”
  • In the course of studying problem solving in the 1930s, Karl Duncker posed one of the most famous hypothetical problems in all of cognitive psychology. It goes like this:
  • Suppose you are a doctor faced with a patient who has a malignant stomach tumor. It is impossible to operate on this patient, but unless the tumor is destroyed the patient will die. There is a kind of ray that can be used to destroy the tumor. If the rays reach the tumor all at once at a sufficiently high intensity, the tumor will be destroyed. Unfortunately, at this intensity the healthy tissue that the rays pass through on the way to the tumor will also be destroyed. At lower intensities the rays are harmless to healthy tissue, but they will not affect the tumor either. What type of procedure might be used to destroy the tumor with the rays, and at the same time avoid destroying the healthy tissue?
  • There are two analogies that complement this question:
  • Only about 10 percent of people solve “Duncker’s radiation problem” initially. Presented with both the radiation problem and the fortress story, about 30 percent solve it and save the patient. Given both of those plus the fire chief story, half solve it. Given the fortress and the fire chief stories and then told to use them to help solve the radiation problem, 80 percent save the patient.
  • The answer is that you (the doctor) could direct multiple low-intensity rays at the tumor from different directions, leaving healthy tissue intact, but converging at the tumor site with enough collective intensity to destroy it.
  • A gift of a single analogy from a different domain tripled the proportion of solvers who got the radiation problem. Two analogies from disparate domains gave an even bigger boost.
  • Human intuition, it appears, is not very well engineered to make use of the best tools when faced with what the researchers called “ ill-defined” problems.
  • In a wicked world, relying upon experience from a single domain is not only limiting, it can be disastrous.
  • The trouble with using no more than a single analogy, particularly one from a very similar situation, is that it does not help battle the natural impulse to employ the “inside view,” a term coined by psychologists Daniel Kahneman and Amos Tversky.
  • Our natural inclination to take the inside view can be defeated by following analogies to the “outside view.”
  • The outside view probes for deep structural similarities to the current problem in different ones. The outside view is deeply counterintuitive because it requires a decision maker to ignore unique surface features of the current project, on which they are the expert, and instead look outside for structurally similar analogies.
  • For a unique 2012 experiment, University of Sydney business strategy professor Dan Lovallo—who had conducted inside-view research with Kahneman—and a pair of economists theorized that starting out by making loads of diverse analogies, Kepler style, would naturally lead to the outside view and improve decisions.
  • The investors initially judged their own projects, where they knew all the details, completely differently from similar projects to which they were outsiders.
  • If you’re asked to predict whether a particular horse will win a race or a particular politician will win an election, the more internal details you learn about any particular scenario—physical qualities of the specific horse, the background and strategy of the particular politician—the more likely you are to say that the scenario you are investigating will occur.
  • Focusing narrowly on many fine details specific to a problem at hand feels like the exact right thing to do, when it is often exactly wrong.
  • In an example, students rated a university a lot better it were told about a few specific science departments that were ranked in the top ten nationally than if there were simply told that every science department at the university was ranked among the top ten.

....

In another experiment, they wondered if forcing analogical thinking on moviegoers could lead to accurate forecasts of film success. They gave a few hundred moviegoers some basic info about some upcoming movies (at the time, Wedding Crashers, Fantastic Four, Deuce Bigalow: European Gigolo, and others). The moviegoers scored these movies as to how well they were similar to movies on another list. The researchers used those similarities to predict the revenues of the upcoming releases. Using the moviegoers’ analogies gave revenue projections that were less than 4 percent off for War of the Worlds, Bewitched, and Red Eye, and 1.7 percent off for Deuce Bigalow: European Gigolo.

  • Netflix came to a similar conclusion for improving its recommendation algorithm. Decoding movies’ traits to figure out what you like was very complex and less accurate than simply analogizing you to many other customers with similar viewing histories. Instead of predicting what you might like, they examine who you are like, and the complexity is captured therein.
  • Interestingly, if the researchers used only the single film that the movie fans ranked as most analogous to the new release, predictive power collapsed. What seemed like the single best analogy did not do well on its own. Using a full “reference class” of analogies—the pillar of the outside view—was immensely more accurate.
  • Dedre Gentner wanted to find out if everyone can be a bit more like Kepler, capable of wielding distant analogies to understand problems. So she helped create the “Ambiguous Sorting Task.”
  • It consists of twenty-five cards, each one describing a real-world phenomenon, like how internet routers or economic bubbles work. Each card falls into two main categories, one for its domain (economics, biology, and so on) and one for its deep structure. Participants are asked to sort the cards into like categories.
  • They would rather rush them to specialization than equip them with ideas from what Gentner referred to as a “variety of base domains,” which foster analogical thinking and conceptual connections that can help students categorize the type of problem they are facing. That is precisely a skill that sets the most adept problem solvers apart.
  • Successful problem solvers are more able to determine the deep structure of a problem before they proceed to match a strategy to it. Less successful problem solvers are more like most students in the Ambiguous Sorting Task: they mentally classify problems only by superficial, overtly stated features, like the domain context. For the best performers, they wrote, problem solving “begins with the typing of the problem.”
  • As education pioneer John Dewey put it in Logic, The Theory of Inquiry, “a problem well put is half-solved.”
  • Every once in a while, Mars appears to reverse course in the sky, do a little loop, and then carry on in the original direction, a feat known as retrograde motion.

....

Psychologist Kevin Dunbar began documenting how productive labs work in the 1990s. He set out to document the process of discovery in real time, focussing on molecular biology labs. He spent a year with 4 labs in the United States.

  • The labs in which scientists had more diverse professional backgrounds were the ones where more and more varied analogies were offered, and where breakthroughs were more reliably produced when the unexpected arose.
  • When the moment came to either dismiss or embrace and grapple with information that puzzled them, they drew on their range to make analogies.
  • In some lab meetings a new analogy entered the conversation every four minutes on average, some of them from outside of biology entirely.
  • In the face of the unexpected, the range of available analogies helped determine who learned something new.
  • “When all the members of the laboratory have the same knowledge at their disposal, then when a problem arises, a group of similar minded individuals will not provide more information to make analogies than a single individual,” Dunbar concluded.

CHAPTER 6: The Trouble with Too Much Grit

  • Vincent van Gogh, Paul Gauguin, J. K. Rowling – they all appear to have excelled in spite of their late starts. It would be easy enough to cherry-pick stories of exceptional late developers overcoming the odds. But they aren’t exceptions by virtue of their late starts, and those late starts did not stack the odds against them. Their late starts were integral to their eventual success.
  • “Match quality” is a term economists use to describe the degree of fit between the work someone does and who they are—their abilities and proclivities.
  • If students focused earlier, they compiled more skills that prepared them for gainful employment. If they sampled and focused later, they entered the job market with fewer domain-specific skills, but a greater sense of the type of work that fit their abilities and inclinations. Malamud’s question was: Who usually won the trade-off, early or late specializers?
  • With less sampling opportunity, more students headed down a narrow path before figuring out if it was a good one. The English and Welsh students were specializing so early that they were making more mistakes.
  • Malamud’s conclusion: “The benefits to increased match quality . . . outweigh the greater loss in skills.” Learning stuff was less important than learning about oneself. Exploration is not just a whimsical luxury of education; it is a central benefit.
  • For professionals who did switch, whether they specialized early or late, switching was a good idea. “You lose a good fraction of your skills, so there’s a hit,” Malamud said, “but you do actually have higher growth rates after switching.” Regardless of when specialization occurred, switchers capitalized on experience to identify better matches.
  • According to Levitt, the study suggested that “admonitions such as ‘winners never quit and quitters never win,’ while well-meaning, may actually be extremely poor advice.”
  • Winston Churchill’s “never give in, never, never, never, never” is an oft-quoted trope. The end of the sentence is always left out: “except to convictions of honor and good sense.”
  • Switchers are winners. It seems to fly in the face of hoary adages about quitting, and of far newer concepts in modern psychology.
  • Carnegie Mellon economics and statistics professor Robert A. Miller modeled career matching—and a decision to attend a military academy is a major career choice—as a “multi-armed bandit process.”
  • A multi-armed bandit process refers to a hypothetical scenario: a single gambler is sitting in front of an entire row of slot machines; each machine has its own unique probability of reward with each pull; the gambler’s challenge is to test the different machines and try to figure out the best way to allocate their lever pulls to maximize rewards.
  • Godin argued that “winners”—he generally meant individuals who reach the apex of their domain—quit fast and often when they detect that a plan is not the best fit, and do not feel bad about it.
  • Persevering through difficulty is a competitive advantage for any traveler of a long road, but he suggested that knowing when to quit is such a big strategic advantage that every single person, before undertaking an endeavor, should enumerate conditions under which they should quit.
  • The more skilled the Army thought a prospective officer could become, the more likely it was to offer a scholarship. And as those hard-working and talented scholarship recipients blossomed into young professionals, they tended to realize that they had a lot of career options outside the military. Eventually, they decided to go try something else. In other words, they learned things about themselves in their twenties and responded by making match quality decisions.
  • The Army learned a hard lesson: the problem was not a financial one; it was a matching one.
  • A few years later, with more knowledge of their skills and preferences, choosing to pursue a different goal was no longer the gritless route; it was the smart one.
  • In the wider world of work, finding a goal with high match quality in the first place is the greater challenge, and persistence for the sake of persistence can get in the way.
  • A recent international Gallup survey of more than two hundred thousand workers in 150 countries reported that 85 percent were either “not engaged” with their work or “actively disengaged.”
  • The trouble, Godin noted, is that humans are bedeviled by the “sunk cost fallacy.” Having invested time or money in something, we are loath to leave it, because that would mean we had wasted our time or money, even though it is already gone.
  • “The more we have invested and even lost,” Konnikova wrote, “the longer we will persist in insisting it will all work out.”
  • “I have been obsessed with a certain idea or project for a short time but later lost interest” is Van Gogh in a nutshell, at least up until the final few years of his life when he settled on his unique style and creatively erupted.
  • Van Gogh was an example of match quality optimization, Robert Miller’s multi-armed bandit process come to life. He tested options with maniacal intensity and got the maximum information signal about his fit as quickly as possible, and then moved to something else and repeated, until he had zigzagged his way to a place no one else had ever been, and where he alone excelled.
  • No one in their right mind would argue that passion and perseverance are unimportant, or that a bad day is a cue to quit. But the idea that a change of interest, or a recalibration of focus, is an imperfection and competitive disadvantage leads to a simple, one-size-fits-all Tiger story: pick and stick, as soon as possible.

CHAPTER 7: Flirting with Your Possible Selves

  • Todd Rose, director of Harvard’s Mind, Brain, and Education program, and computational neuroscientist Ogi Ogas cast a broad net when they set out to study unusually winding career paths.
  • They wanted to find people who are fulfilled and successful, and who arrived there circuitously.
  • It turned out virtually every person had followed what seemed like an unusual path.
  • Thus the research found a name, the Dark Horse Project, because even as more subjects were added, most perceived themselves as dark horses who followed what seemed like an unlikely path.
  • “They focused on, ‘Here’s who I am at the moment, here are my motivations, here’s what I’ve found I like to do, here’s what I’d like to learn, and here are the opportunities. Which of these is the best match right now? And maybe a year from now I’ll switch because I’ll find something better.’”
  • Each dark horse had a novel journey, but a common strategy. “ Short-term planning,” Ogas told me. “They all practice it, not long-term planning.”
  • “I feel sorry for the people who know exactly what they’re going to do from the time they’re sophomores in high school,” he said.
  • “The people we study who are fulfilled do pursue a long-term goal, but they only formulate it after a period of discovery,” he told me.
  • “Obviously, there’s nothing wrong with getting a law or medical degree or PhD. But it’s actually riskier to make that commitment before you know how it fits you. And don’t consider the path fixed. People realize things about themselves halfway through medical school.” Charles Darwin, for example.
  • Career goals that once felt safe and certain can appear ludicrous, to use Darwin’s adjective, when examined in the light of more self-knowledge.
  • Our work preferences and our life preferences do not stay the same, because we do not stay the same.

....

  • Gilbert and colleagues measured the preferences, values, and personalities of more than nineteen thousand adults aged eighteen to sixty-eight. Some were asked to predict how much they would change over the next decade, others to reflect about how much they had changed in the previous one.
  • Predictors expected that they would change very little in the next decade, while reflectors reported having changed a lot in the previous one.
  • Hilariously, predictors were willing to pay an average of $129 a ticket for a show ten years away by their current favorite band, while reflectors would only pay $80 to see a show today by their favorite band from ten years ago.
  • University of Illinois psychologist Brent W. Roberts specializes in studying personality development. He and another psychologist aggregated the results of ninety-two studies and revealed that some personality traits change over time in fairly predictable ways.
  • Adults tend to become more agreeable, more conscientious, more emotionally stable, and less neurotic with age, but less open to experience.
  • In middle age, adults grow more consistent and cautious and less curious, open-minded, and inventive.

....

  • “marshmallow test”
  • The original premise was simple: An experimenter places a marshmallow (or a cookie, or a pretzel) in front of a nursery school child; before leaving, the experimenter tells the child that if she can wait until the experimenter returns, she’ll get that marshmallow plus a second one. If the child can’t wait, she can eat the marshmallow. The children were not told how long the wait would be (it was fifteen to twenty minutes, depending on age), so they just had to hold out if they wanted the maximum reward.
  • At a given point in life, an individual’s nature influences how they respond to a particular situation, but their nature can appear surprisingly different in some other situation.
  • “if-then signatures.”
  • If David is at a giant party, then he seems introverted, but if David is with his team at work, then he seems extroverted. (True.) So is David introverted or extroverted? Well, both, and consistently so.
  • Ogas and Rose call this the “context principle.”
  • In 2007, Mischel wrote, “The gist of such findings is that the child who is aggressive at home may be less aggressive than most when in school; the man exceptionally hostile when rejected in love may be unusually tolerant about criticism of his work; the one who melts with anxiety in the doctor’s office may be a calm mountain climber; the risk-taking entrepreneur may take few social risks.”
  • conscientious
  • Instead of asking whether someone is gritty, we should ask when they are. “If you get someone into a context that suits them,” Ogas said, “they’ll more likely work hard and it will look like grit from the outside.”
  • Because personality changes more than we expect with time, experience, and different contexts, we are ill-equipped to make ironclad long-term goals when our past consists of little time, few experiences, and a narrow range of contexts.

....

  • When she compiled her findings, the central premise was at once simple and profound: we learn who we are only by living, and not before.
  • Ibarra concluded that we maximize match quality throughout life by sampling activities, social groups, contexts, jobs, careers, and then reflecting and adjusting our personal narratives. And repeat.
  • As she put it, “We discover the possibilities by doing, by trying new activities, building new networks, finding new role models.” We learn who we are in practice, not in theory.
  • Think of Frances Hesselbein, who assumed over and over she was just dipping her toe into something new, until she was near the age when her peers were retiring and finally realized she had short-term-planned her way to a vocation. Or Van Gogh, who was certain he found the perfect calling again and again, only to learn in practice that he was mistaken, until he wasn’t.
  • quotidian
  • Themes emerged in the transitions. The protagonists had begun to feel unfulfilled by their work, and then a chance encounter with some world previously invisible to them led to a series of short-term explorations.
  • Some career changers got richer, others poorer; all felt temporarily behind, but as in the Freakonomics coin-flip study, they were happier with a change.
  • Most of the work I’ve done in the last ten years didn’t exist when I was in high school. . . . In such a world it’s not a good idea to have fixed plans.
  • Popular lore holds that the sculptor Michelangelo would see a full figure in a block of marble before he ever touched it, and simply chip away the excess stone to free the figure inside. It is an exquisitely beautiful image. It just isn’t true. Art historian William Wallace showed that Michelangelo was actually a test-and-learn all-star. He constantly changed his mind and altered his sculptural plans as he worked. He left three-fifths of his sculptures unfinished, each time moving on to something more promising.
  • Like anyone eager to raise their match quality prospects, Michelangelo learned who he was—and whom he was carving—in practice, not in theory. Michelangelo started with an idea, tested it, changed it, and readily abandoned it for a better project fit.
  • Michelangelo might have fit well in Silicon Valley; he was a relentless iterator. He worked according to Ibarra’s new aphorism: “I know who I am when I see what I do.”

....

  • Virtually every good thing in my life I can trace back to a misfortune, so my feeling is you don’t know what’s good and what’s bad when things happen. You do not know. You have to wait to find out.”
  • oeuvre
  • A person don’t know what he can do unless he tryes. Trying things is the answer to find your talent.”

CHAPTER 8: The Outsider Advantage

  • The most clever solution always came from a piece of knowledge that was not a part of the normal curriculum.
  • stymied
  • “outside-in” thinking: finding solutions in experiences far outside of focused training for the problem itself.
  • Einstellung effect, a psychology term for the tendency of problem solvers to employ only familiar methods even if better ones are available.
  • “the further the problem was from the solver’s expertise, the more likely they were to solve it.”
  • “Big innovation most often happens when an outsider who may be far away from the surface of the problem reframes the problem in a way that unlocks the solution.”
  • Kaggle is like InnoCentive but specifically for posting challenges in the area of machine learning—artificial intelligence designed to teach itself without human intervention.
  • “Knowledge is a double-edged sword. It allows you to do some things, but it also makes you blind to other things that you could do.”
  • “Undiscovered public knowledge,”
  • The more information specialists create, the more opportunity exists for curious dilettantes to contribute by merging strands of widely available but disparate information—undiscovered public knowledge,

CHAPTER 9: Lateral Thinking with Withered Technology

  • Lateral thinking is a term coined in the 1960s for the reimagining of information in new contexts, including the drawing together of seemingly disparate concepts or domains that can give old ideas new uses.
  • By “withered technology,” Yokoi meant tech that was old enough to be extremely well understood and easily available, so it didn’t require a specialist’s knowledge.
  • There is, to be sure, no comprehensive theory of creativity. But there is a well-documented tendency people have to consider only familiar uses for objects, an instinct known as functional fixedness.
  • He advised young employees not just to play with technology for its own sake, but to play with ideas. Do not be an engineer, he said, be a producer.
  • “Once a young person starts saying things like, ‘Well, it’s not really my place to say . . .’ then it’s all over,” he said.
  • Eminent physicist and mathematician Freeman Dyson styled it this way: we need both focused frogs and visionary birds. “Birds fly high in the air and survey broad vistas of mathematics out to the far horizon,” Dyson wrote in 2009. “They delight in concepts that unify our thinking and bring together diverse problems from different parts of the landscape. Frogs live in the mud below and see only the flowers that grow nearby. They delight in the details of particular objects, and they solve problems one at a time.”
  • The world, he wrote, is both broad and deep.
  • The specialists were adept at working for a long time on difficult technical problems, and for anticipating development obstacles. The generalists tended to get bored working in one area for too long.
  • “polymaths,” broad with at least one area of depth.
  • The polymaths had depth in a core area—so they had numerous patents in that area—but they were not as deep as the specialists.
  • They also had breadth, even more than the generalists, having worked across dozens of technology classes.
  • Over the course of their careers, the polymaths’ breadth increased markedly as they learned about “the adjacent stuff,” while they actually lost a modicum of depth.
  • “Specialists specifically peaked about 1985,” Ouderkirk told me. “And then declined pretty dramatically, leveled off about 2007, and the most recent data show it’s declining again, which I’m trying to understand.”
  • “When information became more widely disseminated,” Ouderkirk told me, “it became a lot easier to be broader than a specialist, to start combining things in new ways.”
  • She is a “T-shaped person,” she said, one who has breadth, compared to an “I-shaped person,” who only goes deep, an analog to Dyson’s birds and frogs.
  • “If you’re working on well-defined and well-understood problems, specialists work very, very well,” he told me. “As ambiguity and uncertainty increases, which is the norm with systems problems, breadth becomes increasingly important.”
  • Research by Spanish business professors Eduardo Melero and Neus Palomeras backed up Ouderkirk’s idea. They analyzed fifteen years of tech patents from 32,000 teams at 880 different organizations, tracking each individual inventor as he or she moved among teams, and then tracking the impact of each invention.
  • In low-uncertainty domains, teams of specialists were more likely to author useful patents.
  • In high-uncertainty domains—where the fruitful questions themselves were less obvious—teams that included individuals who had worked on a wide variety of technologies were more likely to make a splash.
  • The higher the domain uncertainty, the more important it was to have a high-breadth team member.
  • Taylor and Greve suggested that “individuals are capable of more creative integration of diverse experiences than teams are.” They titled their study Superman or the Fantastic Four? “When seeking innovation in knowledge-based industries,” they wrote, “it is best to find one ‘super’ individual. If no individual with the necessary combination of diverse knowledge is available, one should form a ‘fantastic’ team.”
  • “In product development,” Taylor and Greve concluded, “specialization can be costly.”
  • In kind environments, where the goal is to re-create prior performance with as little deviation as possible, teams of specialists work superbly.

CHAPTER 10: Fooled by Expertise

  • On one side was Stanford biologist Paul Ehrlich. In congressional testimony, on The Tonight Show (twenty times), and in his 1968 bestseller The Population Bomb, Ehrlich insisted that it was too late to prevent a doomsday apocalypse from overpopulation.
  • impervious
  • “It is difficult to make predictions, especially about the future,”
  • “There is often a curiously inverse relationship,” Tetlock concluded, “between how well forecasters thought they were doing and how well they did.”
  • There was also a “perverse inverse relationship” between fame and accuracy. The more likely an expert was to have his or her predictions featured on op-ed pages and television, the more likely they were always wrong.
  • the narrow-view hedgehogs, who “know one big thing,” and the integrator foxes, who “know many little things.”
  • Where hedgehogs represented narrowness, foxes ranged outside a single discipline or theory and embodied breadth.
  • Agreement is not what they are after; they are after aggregating perspectives, lots of them.
  • In an impressively unsightly image, Tetlock described the very best forecasters as foxes with dragonfly eyes. Dragonfly eyes are composed of tens of thousands of lenses, each with a different perspective, which are then synthesized in the dragonfly’s brain.
  • A hallmark of interactions on the best teams is what psychologist Jonathan Baron termed “active open-mindedness.” The best forecasters view their own ideas as hypotheses in need of testing. Their aim is not to convince their teammates of their own expertise, but to encourage their teammates to help them falsify their own notions.
  • The best forecasters are high in active open-mindedness. They are also extremely curious, and don’t merely consider contrary ideas, they proactively cross disciplines looking for them.
  • Beneath complexity, hedgehogs tend to see simple, deterministic rules of cause and effect framed by their area of expertise, like repeating patterns on a chessboard. Foxes see complexity in what others mistake for simple cause and effect. They understand that most cause-and-effect relationships are probabilistic, not deterministic.
  • In wicked domains that lack automatic feedback, experience alone does not improve performance.
  • When an outcome took them by surprise, however, foxes were much more likely to adjust their ideas. Hedgehogs barely budged.
  • “Good judges are good belief updaters,” according to Tetlock. If they make a bet and lose, they embrace the logic of a loss just as they would the reinforcement of a win. That is called, in a word: learning. Sometimes, it involves putting experience aside entirely.

CHAPTER 11: Learning to Drop Your Familiar Tools

  • Business professors around the world have been teaching Carter Racing for thirty years because it provides a stark lesson in the danger of reaching conclusions from incomplete data, and the folly of relying only on what is in front of you.
  • “Dropping one’s tools is a proxy for unlearning, for adaptation, for flexibility,” Weick wrote. “It is the very unwillingness of people to drop their tools that turns some of these dramas into tragedies.”
  • “If I feel like I don’t have data to back me up, the boss’s opinion is better than mine.”
  • Dropping familiar tools is particularly difficult for experienced professionals who rely on what Weick called overlearned behavior. That is, they have done the same thing in response to the same challenges over and over until the behavior has become so automatic that they no longer even recognize it as a situation-specific tool.
  • He employed what Weick called “hunches held lightly.” Gleason gave decisive directions to his crew, but with transparent rationale and the addendum that the plan was ripe for revision as the team collectively made sense of a fire.
  • “When you don’t have any data,” Feynman said, “you have to use reason.”
  • There are no tools that cannot be dropped, reimagined, or repurposed in order to navigate an unfamiliar challenge. Even the most sacred tools. Even the tools so taken for granted they become invisible.
  • As NASA engineer Mary Shafer once articulated, “Insisting on perfect safety is for people who don’t have the balls to live in the real world.”
  • “Congruence” is a social science term for cultural “fit” among an institution’s components—values, goals, vision, self-concepts, and leadership styles.
  • She found that the most effective leaders and organizations had range; they were, in effect, paradoxical. They could be demanding and nurturing, orderly and entrepreneurial, even hierarchical and individualistic all at once. A level of ambiguity, it seemed, was not harmful. In decision making, it can broaden an organization’s toolbox in a way that is uniquely valuable.
  • thinkers who tolerate ambiguity make the best forecasts;
  • cultures can build in a form of ambiguity that forces decision makers to use more than one tool, and to become more flexible and learn more readily.
  • He wanted a culture where everyone had the responsibility to protest if something didn’t feel right. He decided to go prospecting for doubts.
  • So when Geveden became CEO, he wrote a short memo on his expectations for teamwork. “I told them I expect disagreement with my decisions at the time we’re trying to make decisions, and that’s a sign of organizational health,” he told me. “After the decisions are made, we want compliance and support, but we have permission to fight a little bit about those things in a professional way.”
  • He emphasized that there is a difference between the chain of command and the chain of communication, and that the difference represents a healthy cross-pressure.
  • a differentiated chain of command and chain of communication that produced incongruence, and thus a healthy tension.
  • A trio of psychology and management professors who analyzed a century of Himalayan mountain climbers—5,104 expedition groups in all—found that teams from countries that strongly valued hierarchical culture got more climbers to the summit, but also had more climbers die along the way. The trend did not hold for solo climbers, only teams, and the researchers argued that hierarchical teams benefitted from a clear chain of command, but suffered from a one-way chain of communication that obscured problems. The teams needed elements of both hierarchy and individualism to both excel and survive.
  • Incongruence, as the experimental research testified, helps people to discover useful cues, and to drop the traditional tools when it makes sense.
  • When all you have is a volcanologist, I learned, every extinction looks like a volcano.
  • Seeing small pieces of a larger jigsaw puzzle in isolation, no matter how hi-def the picture, is insufficient to grapple with humanity’s greatest challenges.
  • Individuals who live by historian Arnold Toynbee’s words that “no tool is omnicompetent. There is no such thing as a master-key that will unlock all doors.”
  • Rather than wielding a single tool, they have managed to collect and protect an entire toolshed, and they show the power of range in a hyperspecialized world.

CHAPTER 12: Deliberate Amateurs

  • One needs to let the brain think about something different from its daily work, he would say. “On Saturday,” as Smithies put it, “you don’t have to be completely rational.”
  • “I try to teach people, ‘Don’t end up a clone of your thesis adviser,’” he told me. “Take your skills to a place that’s not doing the same sort of thing. Take your skills and apply them to a new problem, or take your problem and try completely new skills.”
  • “deliberate amateur.”
  • The word “amateur,” she pointed out, did not originate as an insult, but comes from the Latin word for a person who adores a particular endeavor.
  • “A paradox of innovation and mastery is that breakthroughs often occur when you start down a road, but wander off for a ways and pretend as if you have just begun,”
  • Arturo Casadevall
  • His “h-index,” a measure of a scientist’s productivity and how often they are cited, recently surpassed Albert Einstein’s.
  • young scientists are rushed to specialize before they learn how to think; they end up unable to produce good work themselves and unequipped to spot bad (or fraudulent) work by their colleagues.
  • The interface between specialties, and between creators with disparate backgrounds, has been studied, and it is worth defending.
  • In professional networks that acted as fertile soil for successful groups, individuals moved easily among teams, crossing organizational and disciplinary boundaries and finding new collaborators.
  • New collaborations allow creators “to take ideas that are conventions in one area and bring them into a new area, where they’re suddenly seen as invention,” said sociologist Brian Uzzi, Amaral’s collaborator. Human creativity, he said, is basically an “import/ export business of ideas.”
  • Uzzi documented an import/ export trend that began in both the physical and social sciences in the 1970s, pre-internet: more successful teams tended to have more far-flung members. Teams that included members from different institutions were more likely to be successful than those that did not, and teams that included members based in different countries had an advantage as well.
  • It echoes Oliver Smithies’s advice to bring new skills to an old problem, or a new problem to old skills.
  • work that builds bridges between disparate pieces of knowledge is less likely to be funded, less likely to appear in famous journals, more likely to be ignored upon publication, and then more likely in the long run to be a smash hit in the library of human knowledge.
  • The further basic science moves from meandering exploration toward efficiency, he believes, the less chance it will have of solving humanity’s greatest challenges.
  • Casadevall’s overarching point is that the innovation ecosystem should intentionally preserve range and inefficiency.
  • “Scientific progress on a broad front results from the free play of free intellects, working on subjects of their own choice,” Bush wrote, “in the manner dictated by their curiosity for exploration of the unknown.”
  • At its core, all hyperspecialization is a well-meaning drive for efficiency—the most efficient way to develop a sports skill, assemble a product, learn to play an instrument, or work on a new technology. But inefficiency needs cultivating too. The wisdom of a Polgar-like method of laser-focused, efficient development is limited to narrowly constructed, kind learning environments.
  • “When you push the boundaries, a lot of it is just probing. It has to be inefficient,” Casadevall told me. “What’s gone totally is that time to talk and synthesize. People grab lunch and bring it into their offices. They feel lunch is inefficient, but often that’s the best time to bounce ideas and make connections.”

CONCLUSION: Expanding Your Range

  • Creativity researcher Dean Keith Simonton has shown that the more work eminent creators produced, the more duds they churned out, and the higher their chances of a supernova success.
  • As InnoCentive founder Alph Bingham told me, “breakthrough and fallacy look a lot alike initially.”
  • Compare yourself to yourself yesterday, not to younger people who aren’t you. Everyone progresses at a different rate, so don’t let anyone else make you feel behind. You probably don’t even know where exactly you’re going, so feeling behind doesn’t help.

Featured Image Source

Share your thoughts via Twitter DM. Let's have a chat.