INTRODUCTION: Roger vs. Tiger
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.”
Prominent sports scientist Ross Tucker summed up research in the field simply: “We know that early sampling is key, as is diversity.”
I found a raft of studies that showed how technological inventors increased their creative impact by accumulating experience in different domains, compared to peers who drilled more deeply into one; they actually benefited by proactively sacrificing a modicum of depth for breadth as their careers progressed.
I dove into work showing that highly credentialed experts can become so narrow-minded that they actually get worse with experience, even while becoming more confident—a dangerous combination. And I was stunned when cognitive psychologists I spoke with led me to an enormous and too often ignored body of work demonstrating that 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
CHAPTER 1: The Cult of the Head Start
The powerful lesson is that anything in the world can be conquered in the same way. It relies on one very important, and very unspoken, assumption: that chess and golf are representative examples of all the activities that matter to you.
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.
wide-ranging review of research that rocked psychology because it showed experience simply did not create skill in a wide range of real-world scenarios, from college administrators assessing student potential to psychiatrists predicting patient performance to human resources professionals deciding who will succeed in job training. 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?
Narrow experience made for better chess and poker players and firefighters, but not for better predictors of financial or political trends, or of how employees or patients would perform.
The domains Klein studied, in which instinctive pattern recognition worked powerfully, are what psychologist Robin Hogarth termed “kind” learning environments.
Kahneman was focused on the flip side of kind learning environments; Hogarth called them “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.
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.
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.
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.”
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.”
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.
CHAPTER 2: How the Wicked World Was Made
Professors, he told me, are just too eager to share their favorite facts gleaned from years of acceleratingly narrow study. He has taught for fifty years, from Cornell to Canterbury, and is quick to include himself in that criticism. When he taught intro to moral and political philosophy, he couldn’t resist the urge to impart his favorite minutiae from Plato, Aristotle, Hobbes, Marx, and Nietzsche.
college departments rush to develop students in a narrow specialty area, while failing to sharpen the tools of thinking that can serve them in every area. This must change, he argues, if students are to capitalize on their unprecedented capacity for abstract thought. They must be taught to think before being taught what to think about. Students come prepared with scientific spectacles, but do not leave carrying a scientific-reasoning Swiss Army knife.
Computational thinking is using abstraction and decomposition when attacking a large complex task,” she wrote. “It is choosing an appropriate representation for a problem.”
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.
CHAPTER 3: When Less of the Same Is More
Improv masters learn like babies: dive in and imitate and improvise first, learn the formal rules later. “At the beginning, your mom didn’t give you a book and say, ‘This is a noun, this is a pronoun, this is a dangling participle,’” Cecchini told me. “You acquired the sound first. And then you acquire the grammar later.
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.”
Even the Suzuki Method of music instruction, synonymous in the public consciousness with early drilling, was designed by Shinichi Suzuki to mimic natural language acquisition
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.
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
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. For instance, take the formula for the sum of the interior angles of a polygon (180 × (number of polygon sides − 2)), and apply it to polygons on a worksheet. The other common variety was “making connections” questions, which connected students to a broader concept, rather than just a procedure. That was more like when the teacher asked students why the formula works, or made them try to figure out if it works for absolutely any polygon from a triangle to an octagon. Both types of questions are useful and both were posed by teachers in every classroom in every country studied. But an important difference emerged in what teachers did after they asked a making-connections problem. 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. “We’re very good, humans are, at trying to do the least amount of work that we have to in order to accomplish a task,” Richland told me. Soliciting hints toward a solution is both clever and expedient. The problem is that when it comes to learning concepts that can be broadly wielded, expedience can backfire.
Making-connections problems did not survive the teacher-student interactions.
Just as it is in golf, procedure practice is important in math. But when it comprises the entire math training strategy, it’s a problem. “ Students do not view mathematics as a system,” Richland and her colleagues wrote. They view it as just a set of procedures.
When younger students bring home problems that force them to make connections, Richland told me, “parents are like, ‘Lemme show you, there’s a faster, easier way.’” If the teacher didn’t already turn the work into using-procedures practice, well-meaning parents will. They aren’t comfortable with bewildered kids, and they want understanding to come quickly and easily. But for learning that is both durable (it sticks) and flexible (it can be applied broadly),fast and easy is precisely the problem.
Struggling to generate an answer on your own, even a wrong one, enhances subsequent learning. Socrates was apparently on to something when he forced pupils to generate answers rather than bestowing them. It requires the learner to intentionally sacrifice current performance for future benefit
Being forced to generate answers improves subsequent learning even if the generated answer is wrong. It can even help to be wildly wrong. 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.
Training without hints is slow and error-ridden. It is, essentially, what we normally think of as testing, except for the purpose of learning rather than evaluation—when “test” becomes a dreaded four-letter word.
Used for learning, testing, including self-testing, is a very desirable difficulty. Even testing prior to studying works, at the point when wrong answers are assured
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.” It also made their courses more difficult and frustrating
CHAPTER 5: Thinking Outside Experience
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.
If you need a large force to accomplish some purpose, but are prevented from applying such a force directly, many smaller forces applied simultaneously from different directions may work just as well.”
managers focus on the details of their project and become overly optimistic. Project managers can become like Kahneman’s curriculum-building team, which decided that thanks to its roster of experts it would certainly not encounter the same delays as did other groups.
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.
Using a full “reference class” of analogies—the pillar of the outside view—was immensely more accurate.
Northwestern’s website for the program features an alum’s description: “Think of the Integrated Science Program as a biology minor, chemistry minor, physics minor, and math minor combined into a single major. The primary intent of this program is to expose students to all fields of the natural and mathematical sciences so that they can see commonalities among different fields of the natural sciences. . . . The ISP major allows you to see connections across different disciplines
In one of the most cited studies of expert problem solving ever conducted, an interdisciplinary team of scientists came to a pretty simple conclusion: 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.”
Whether it is the making-connections knowledge Lindsey Richland studied, or the broad concepts that Flynn tested, or the distant, deep structural analogical reasoning that Gentner assessed, there is often no entrenched interest fighting on the side of range, or of knowledge that must be slowly acquired. All forces align to incentivize a head start and early, narrow specialization, even if that is a poor long-term strategy. That is a problem, because another kind of knowledge, perhaps the most important of all, is necessarily slowly acquired—the kind that helps you match yourself to the right challenge in the first place.
CHAPTER 6: The Trouble with Too Much Grit
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?
Malamud analyzed data for thousands of former students, and found that college graduates in England and Wales were consistently more likely to leap entirely out of their career fields than their later-specializing Scottish peers. And despite starting out behind in income because they had fewer specific skills, the Scots quickly caught up. Their counterparts in England and Wales were more often switching fields after college and after beginning a career even though they had more disincentive to switch, having focused on that field.
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
In England and Wales, students were expected to pick a path with knowledge only of the limited menu they had been exposed to early in high school. That is sort of like being forced to choose at sixteen whether you want to marry your high school sweetheart.
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.” Levitt identified one of his own most important skills as “ the willingness to jettison” a project or an entire area of study for a better fit.
Psychologist Angela Duckworth conducted the most famous study of quitting.
She decided to study passion and perseverance, a combination she cleverly formulated as “grit.” She designed a self-assessment that captured the two components of grit. One is essentially work ethic and resilience, and the other is “consistency of interests”—direction, knowing exactly what one wants.
The fact that cadets are selected based on their Whole Candidate Score leads to what statisticians call a “restriction of range.” That is, because cadets were selected precisely for their Whole Candidate Score, a group of people who are very alike on Whole Candidate Score measures were siphoned from the rest of humanity. When that happens, other variables that were not part of the selection process can suddenly look much more important in comparison. To use a sports analogy, it would be like conducting a study of success in basketball that included only NBA players as subjects; the study might show that height is not an important predictor of success, but determination is.
The ones who left earlier were either very homesick or just realized they were not a good fit. Most of the latter seemed to be kids who were pressured into coming to West Point without any real desire themselves.” In other words, of the small number of cadets who left during Beast, rather than a failing of persistence, some of them were simply responding to match quality information—they weren’t a good fit.
Seth Godin wrote a book disparaging the idea that “quitters never win.” 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. “We fail,” he wrote, when we stick with “ tasks we don’t have the guts to quit.” Godin clearly did not advocate quitting simply because a pursuit is difficult. 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 important trick, he said, is staying attuned to whether switching is simply a failure of perseverance, or astute recognition that better matches are available
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. Writer, psychology PhD, and professional poker player Maria Konnikova explained in her book The Confidence Game how the sunk cost mindset is so deeply entrenched that conmen know to begin by asking their marks for several small favors or investments before progressing to large asks. Once a mark has invested energy or money, rather than walking away from sunk costs he will continue investing, more than he ever wanted to, even as, to any rational observer, disaster becomes imminent. “The more we have invested and even lost,” Konnikova wrote, “the longer we will persist in insisting it will all work ou
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. Responding to lived experience with a change of direction, like Van Gogh did habitually, like West Point graduates have been doing since the dawn of the knowledge economy, is less tidy but no less important. It involves a particular behavior that improves your chances of finding the best match, but that at first blush sounds like a terrible life strategy: short-term planning.
CHAPTER 7: Flirting with Your Possible Selves
right away asked what training had prepared her for leadership. Wrong question. “Oh, don’t ask me what my training was,” she replied with a dismissing hand wave. She explained that she just did whatever seemed like it would teach her something and allow her to be of service at each moment, and somehow that added up to training.
Ogas uses the shorthand “standardization covenant” for the cultural notion that it is rational to trade a winding path of self-exploration for a rigid goal with a head start because it ensures stability. “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.”
The precise person you are now is fleeting, just like all the other people you’ve been. That feels like the most unexpected result, but it is also the most well documented.
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;
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. Each “story of me” continues to evolve. We should all heed the wisdom of Alice, who, when asked by the Gryphon in Wonderland to share her story, decided she had to start with the beginning of her adventure that very morning. “It’s no use going back to yesterday,” she said, “because I was a different person then.” Alice captured a grain of truth, one that has profound consequences for the best way to maximize match quality.
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
At first, all career changers fell prey to the cult of the head start and figured it couldn’t possibly make sense to dispense with their long-term plans in favor of rapidly evolving short-term experiments.
Instead of working back from a goal, work forward from promising situations. This is what most successful people actually do anyway.
I propose instead that you don’t commit to anything in the future, but just look at the options available now, and choose those that will give you the most promising range of options afterward.
What Ibarra calls the “plan-and-implement” model—the idea that we should first make a long-term plan and execute without deviation, as opposed to the “test-and-learn” model—is entrenched in depictions of geniuses. 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. The first line of Wallace’s analysis: “Michelangelo did not expound a theory of art.” He tried, then went from there. He was a sculptor, painter, master architect, and made engineering designs for fortifications in Florence. In his late twenties he even pushed visual art aside to spend time writing poems (including one about how much he grew to dislike painting), half of which he left unfinished.
The nonfiction writer and filmmaker Sebastian Junger was twenty-nine and working as an arborist, harnessed in the upper canopy of a pine tree, when he tore open his leg with a chainsaw and got the idea to write about dangerous jobs. He was still limping two months later when a fishing vessel out of Gloucester, Massachusetts, where he lived, was lost at sea. Commercial fishing provided his topic; the result was The Perfect Storm. Junger stuck with the theme of dangerous jobs, and made the Oscar-nominated war documentary Restrepo. “That cut was the best thing that ever could have happened to me,” he told me. “It gave me this template for seeing my career. 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.”
The Van Gogh biography by Steven Naifeh and his late partner and coauthor Gregory White Smith is one of the best books I have ever read in any genre
CHAPTER 9: Lateral Thinking with Withered Technology
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.” As a mathematician, Dyson labeled himself a frog, but contended, “It is stupid to claim that birds are better than frogs because they see farther, or that frogs are better than birds because they see deeper.” The world, he wrote, is both broad and deep. “We need birds and frogs working together to explore it.”
A high-repetition workload negatively impacted performance. Years of experience had no impact at all. If not experience, repetition, or resources, what helped creators make better comics on average and innovate? The answer (in addition to not being overworked) was how many of twenty-two different genres a creator had worked in, from comedy and crime, to fantasy, adult, nonfiction, and sci-fi. Where length of experience did not differentiate creators, breadth of experience did. Broad genre experience made creators better on average and more likely to innovate.
When the National Transportation Safety Board analyzed its database of major flight accidents, it found that 73 percent occurred on a flight crew’s first day working together. Like surgeries and putts, the best flight is one in which everything goes according to routines long understood and optimized by everyone involved, with no surprises.
Darwin was not a university faculty member nor a professional scientist at any institution, but he was networked into the scientific community
He had at least 231 scientific pen pals who can be grouped roughly into thirteen broad themes based on his interests, from worms to human sexual selection
He peppered them with questions. He cut up their letters to paste pieces of information in his own notebooks, in which “ideas tumble over each other in a seemingly chaotic fashion.” When his chaotic notebooks became too unwieldy, he tore pages out and filed them by themes of inquiry. Just for his own experiments with seeds, he corresponded with geologists, botanists, ornithologists, and conchologists in France, South Africa, the United States, the Azores, Jamaica, and Norway, not to mention a number of amateur naturalists and some gardeners he happened to know. As Gruber wrote, the activities of a creator “may appear, from the outside, as a bewildering miscellany,” but he or she can “map” each activity onto one of the ongoing enterprises. “In some respects,” Gruber concluded, “Charles Darwin’s greatest works represent interpretative compilations of facts first gathered by others.” He was a lateral-thinking integrator.
CHAPTER 10: Fooled by Expertise
The aversion to contrary ideas is not a simple artifact of stupidity or ignorance. Yale law and psychology professor Dan Kahan has shown that more scientifically literate adults are actually more likely to become dogmatic about politically polarizing topics in science. Kahan thinks it could be because they are better at finding evidence to confirm their feelings: the more time they spend on the topic, the more hedgehog-like they become.
The most science-curious folk always chose to look at new evidence, whether or not it agreed with their current beliefs. Less science-curious adults were like hedgehogs: they became more resistant to contrary evidence and more politically polarized as they gained subject matter knowledge. Those who were high in science curiosity bucked that trend. Their foxy hunt for information was like a literal fox’s hunt for prey: roam freely, listen carefully, and consume omnivorously. Just as Tetlock says of the best forecasters, it is not what they think, but how they think. 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. “Depth can be inadequate without breadth,” wrote Jonathan Baron, the psychologist who developed measurements of active open-mindedness.
Einstein was a hedgehog. He saw simplicity beneath complexity, and found elegant theories to prove it. But he also spent the last thirty years of his life in a rigid quest for a single theory of everything that would explain away the messy apparent randomness inherent to quantum mechanics, a field spawned in part by his own work
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. There are unknowns, and luck, and even when history apparently repeats, it does not do so precisely. They recognize that they are operating in the very definition of a wicked learning environment, where it can be very hard to learn, from either wins or losses.
In wicked domains that lack automatic feedback, experience alone does not improve performance. Effective habits of mind are more important, and they can be developed. In four straight years of forecasting tournaments, Tetlock and Mellers’s research group showed that an hour of basic training in foxy habits improved accuracy.
Basically, forecasters can improve by generating a list of separate events with deep structural similarities, rather than focusing only on internal details of the specific event in question. Few events are 100 percent novel—uniqueness is a matter of degree, as Tetlock puts it—and creating the list forces a forecaster implicitly to think like a statistician.
Starting with the details—the inside view—is dangerous. Hedgehog experts have more than enough knowledge about the minutiae of an issue in their specialty to do just what Dan Kahan suggested: cherry-pick details that fit their all-encompassing theories. Their deep knowledge works against them. Skillful forecasters depart from the problem at hand to consider completely unrelated events with structural commonalities rather than relying on intuition based on personal experience or a single area of expertise.
When an outcome took them by surprise, however, foxes were much more likely to adjust their ideas. Hedgehogs barely budged. Some hedgehogs made authoritative predictions that turned out wildly wrong, and then updated their theories in the wrong direction. They became even more convinced of the original beliefs that led them astray. “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
But it’s often the case in group meetings where the person who made the PowerPoint slides puts data in front of you, and we often just use the data people put in front of us. I would argue we don’t do a good job of saying, ‘Is this the data that we want to make the decision we need to make?’”
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.” For him, firefighters were an example, and a metaphor for what he learned while studying normally reliable organizations that clung to trusty methods, even when they led to bewildering decisions.
Rather than adapting to unfamiliar situations, whether airline accidents or fire tragedies, Weick saw that experienced groups became rigid under pressure and “regress to what they know best.” They behaved like a collective hedgehog, bending an unfamiliar situation to a familiar comfort zone, as if trying to will it to become something they actually had experienced before.
“When a firefighter is told to drop his firefighting tools, he is told to forget he is a firefighter.” Weick explained that wildland firefighters have a firm “can do” culture, and dropping tools was not part of it, because it meant they had lost control
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. Research on aviation accidents, for example, found that “a common pattern was the crew’s decision to continue with their original plan” even when conditions changed dramatically.
Wildland firefighters and space shuttle engineers do not have the liberty to train for their most challenging moments by trial and error. A team or organization that is both reliable and flexible, according to Weick, is like a jazz group. There are fundamentals—scales and chords—that every member must overlearn, but those are just tools for sensemaking in a dynamic environment. 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. It is, of course, easier said than done. Especially when the tool is the very core of an organization’s culture.
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.” It is no wonder that organizations struggle to cultivate experts who are both proficient with their tools and prepared to drop them.
thinkers who tolerate ambiguity make the best forecasts;
“Consensus is nice to have, but we shouldn’t be optimizing happiness, we should be optimizing our decisions. I just had a feeling all along that there was something wrong with the culture. We didn’t have a healthy tension in the system.”
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. “I warned them, I’m going to communicate with all levels of the organization down to the shop floor, and you can’t feel suspicious or paranoid about that,” he said. “I told them I will not intercept your decisions that belong in your chain of command, but I will give and receive information anywhere in the organization, at any time. I just can’t get enough understanding of the organization from listening to the voices at the top.”
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.
CHAPTER 12: Deliberate Amateurs
The program, known as the R3 Initiative (Rigor, Responsibility, Reproducibility), starts with interdisciplinary classes that include philosophy, history, logic, ethics, statistics, communication, and leadership.
The guild system in Europe arose in the Middle Ages as artisans and merchants sought to maintain and protect specialized skills and trades,” he wrote with a colleague. “Although such guilds often produced highly trained and specialized individuals who perfected their trade through prolonged apprenticeships, they also encouraged conservatism and stifled innovation.” Both training and professional incentives are aligning to accelerate specialization, creating intellectual archipelagos.
specialization had played a critical role in the 2008 global financial crisis. “Insurance regulators regulated insurance, bank regulators regulated banks, securities regulators regulated securities, and consumer regulators regulated consumers,” the official told me. “But the provision of credit goes across all those markets. So we specialized products, we specialized regulation, and the question is, ‘Who looks across those markets?’ The specialized approach to regulation missed systemic issues.”
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. Networks that spawned unsuccessful teams, conversely, were broken into small, isolated clusters in which the same people collaborated over and over. Efficient and comfortable, perhaps, but apparently not a creative engine. “ The entire network looks different when you compare a successful team with an unsuccessful team,” according to Luís A. Nunes Amaral, a Northwestern physicist who studies networks. Amaral’s remark does not compare individual teams, but rather the larger ecosystems that foster the formation of successful teams.
To recap: 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.
CONCLUSION: Expanding Your Range
business writer Michael Simmons put it, “ Baseball has a truncated outcome distribution. When you swing, no matter how well you connect with the ball, the most runs you can get is four.” In the wider world, “every once in a while, when you step up to the plate, you can score 1,000 runs.” It doesn’t mean breakthrough creation is luck, although that helps, but rather that it is hard and inconsistent. Going where no one has is a wicked problem. There is no well-defined formula or perfect system of feedback to follow. It’s like the stock market that way; if you want the sky highs, you have to tolerate a lot of lows. As InnoCentive founder Alph Bingham told me, “breakthrough and fallacy look a lot alike initially.
The question I set out to explore was how to capture and cultivate the power of breadth, diverse experience, and interdisciplinary exploration, within systems that increasingly demand hyperspecialization, and would have you decide what you should be before first figuring out who you are.
So, about that one sentence of advice: Don’t feel behind.
Finally, remember that there is nothing inherently wrong with specialization. We all specialize to one degree or another, at some point or other. My initial spark of interest in this topic came from reading viral articles and watching conference keynotes that offered early hyperspecialization as some sort of life hack, a prescription that will save you the wasted time of diverse experience and experimentation. I hope I have added ideas to that discussion, because research in myriad areas suggests that mental meandering and personal experimentation are sources of power, and head starts are overrated