Epstein Range Quotes

We learn who we are in practice, not in theory.

You have people walking around with all the knowledge of humanity on their phone, but they have no idea how to integrate it. We don’t train people in thinking or reasoning.

If we treated careers more like dating, nobody would settle down so quickly.

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

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.*

Our work preferences and our life preferences do not stay the same, because we do not stay the same.

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.

everyone needs habits of mind that allow them to dance across disciplines.

Learning stuff was less important than learning about oneself. Exploration is not just a whimsical luxury of education; it is a central benefit.

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.

In a wicked world, relying upon experience from a single domain is not only limiting, it can be disastrous.

Modern work demands knowledge transfer: the ability to apply knowledge to new situations and different domains. Our most fundamental thought processes have changed to accommodate increasing complexity and the need to derive new patterns rather than rely only on familiar ones. Our conceptual classification schemes provide a scaffolding for connecting knowledge, making it accessible and flexible.

First act and then think...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.

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.

Overspecialization can lead to collective tragedy even when every individual separately takes the most reasonable course of action.

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.

it is difficult to accept that the best learning road is slow, and that doing poorly now is essential for better performance later. It is so deeply counterintuitive that it fools the learners themselves,

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.

Almost none of the students in any major showed a consistent understanding of how to apply methods of evaluating truth they had learned in their own discipline to other areas.

We learn who we are only by living, and not before.

mental meandering and personal experimentation are sources of power, and head starts are overrated

We fail...tasks we don't have the guts to quit."...knowing when to quit is such a strategic advantage that every single person, before undertaking an endeavor should enumerate conditions under which they should quit.

Seeding the soil for generalists and polymaths who integrate knowledge takes more than money. It takes opportunity.

Who do I really want to become?,” their work indicated that it is better to be a scientist of yourself, asking smaller questions that can actually be tested—“Which among my various possible selves should I start to explore now? How can I do that?” Be a flirt with your possible selves.* Rather than a grand plan, find experiments that can be undertaken quickly. “Test-and-learn,” Ibarra told me, “not plan-and-implement.

As each man amassed more information for his own view, each became more dogmatic, and the inadequacies in their models of the world more stark.

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.

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.

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.

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.

My inclination is to attack a problem by building a narrative. I figure out the fundamental questions to ask, and if you ask those questions of the people who actually do know their stuff, you are still exactly where you would be if you had all this other knowledge inherently.

The precise person you are now is fleeting, just like all the other people you’ve been.

Struggling to retrieve information primes the brain for subsequent learning,

...problem solving "begins with the typing of the problem."..."a problem well put is half-solved.

All of the strengths-finder stuff, it gives people license to pigeonhole themselves or others in ways that just don’t take into account how much we grow and evolve and blossom and discover new things,

The jazz musician is a creative artist, the classical musician is a re-creative artist.

AI systems are like savants.” They need stable structures and narrow worlds.

Specialization is obvious: keep going straight. Breadth is trickier to grow.

Instead of working back from a goal, work forward from promising situations. This is what most successful people actually do anyway.

the foxiest forecasters—just bright people with wide-ranging interests and reading habits but no particular relevant background

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.” Labor

Like chess masters and firefighters, premodern villagers relied on things being the same tomorrow as they were yesterday. They were extremely well prepared for what they had experienced before, and extremely poorly equipped for everything else. Their very thinking was highly specialized in a manner that the modern world has been telling us is increasingly obsolete. 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. Faced with any problem they had not directly experienced before, the remote villagers were completely lost. That is not an option for us. 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.

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.

Their findings about who these people are should sound familiar by now: "high tolerance for ambiguity"; "systems thinkers"; "additional technical knowledge from peripheral domains"; "repurposing what is already available"; "adept at using analogous domains for finding inputs to the invention process"; "ability to connect disparate pieces of information in new ways"; "synthesizing information from many different sources"; "they appear to flit among ideas"; "broad range of interests"; "they read more (and more broadly) than other technologists and have a wider range of outside interests"; "need to learn significantly across domains"; "Serial innovators also need to communicate with various individuals with technical expertise outside of their own domain.

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.

Don’t end up a clone of your thesis adviser,’” he [Oliver Smithies] 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.

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.

Whether or not experience inevitably led to expertise, they agreed, depended entirely on the domain in question. 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.

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. All slow down learning and make performance suffer, in the short term.

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.

As the company grew, he worried that young engineers would be too concerned about looking stupid to share ideas for novel uses of old technology, so he began intentionally blurting out crazy ideas at meetings to set the tone.

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.

Repetition, it turned out, was less important than struggle.

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.

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.

The ultimate lesson of the question was that detailed prior knowledge was less important than a way of thinking.

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.

highly credentialed experts can become so narrow-minded that they actually get worse with experience, even while becoming more confident—a dangerous combination.

And yet a tech founder who is fifty years old is nearly twice as likely to start a blockbuster company as one who is thirty, and the thirty-year-old has a better shot than a twenty-year-old.

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.

Our greatest strength is the exact opposite of narrow specialization. It is the ability to integrate broadly. According to Gary Marcus, a psychology and neural science professor who sold his machine learning company to Uber, “In narrow enough worlds, humans may not have much to contribute much longer. In more open-ended games, I think they certainly will. Not just games, in open ended real-world problems we’re still crushing the machines.

While it is undoubtedly true that there are areas that require individuals with Tiger’s precocity and clarity of purpose, as complexity increases—as technology spins the world into vaster webs of interconnected systems in which each individual only sees a small part—we also need more Rogers: people who start broad and embrace diverse experiences and perspectives while they progress. People with range.

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.

InnoCentive solvers rate problems on how relevant they were to their own field of specialization, and found that “the further the problem was from the solver’s expertise, the more likely they were to solve it.

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.

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 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.

...he preferred to view his crew leadership not as decision making, but as sensemaking. "If I make a decision, it is a possession, I take pride in it. I tend to defend it and not listen to those who question it...If I make sense, then this is more dynamic and I listen and I can change it.

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.

cognitive entrenchment.

the study suggested that “admonitions such as ‘winners never quit and quitters never win,’ while well-meaning, may actually be extremely poor advice.

desirable difficulties

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.

Exposure to the modern world has made us better adapted to complexity, and that has manifested in flexibility, with profound implications for the breadth of our intellectual world. In every cognitive direction, the minds of premodern citizens were severely constrained by the concrete world before them.

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.

Instead, she told me, in a clever inversion of a hallowed axiom, “First act and then think.” Ibarra marshaled social psychology to argue persuasively that we are each made up of numerous possibilities. 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.

Above all, the most basic message is that teachers and students must avoid interpreting current performance as learning. Good performance on a test during the learning process can indicate mastery, but learners and teachers need to be aware that such performance will often index, instead, fast but fleeting progress.

The average expert was a horrific forecaster. Their areas of specialty, years of experience, academic degrees, and even (for some) access to classified information made no difference. They were bad at short-term forecasting, bad at long-term forecasting, and bad at forecasting in every domain. When experts declared that some future event was impossible or nearly impossible, it nonetheless occurred 15 percent of the time. When they declared a sure thing, it failed to transpire more than one-quarter of the time.

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.

Compared to other scientists, Nobel laureates are at least twenty-two times more likely to partake as an amateur actor, dancer, magician, or other type of performer. Nationally recognized scientists are much more likely than other scientists to be musicians, sculptors, painters, printmakers, woodworkers, mechanics, electronics tinkerers, glassblowers, poets, or writers, of both fiction and nonfiction. And, again, Nobel laureates are far more likely still.

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.” Even people who look like consummate long-term visionaries from afar usually looked like short-term planners up close.

The most momentous personality changes occur between age eighteen and one’s late twenties, so specializing early is a task of predicting match quality for a person who does not yet exist. It could work, but it makes for worse odds. Plus, while personality change slows, it does not stop at any age. Sometimes it can actually happen instantly.

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.

Teaching kids to read a little early is not a lasting advantage. Teaching them how to hunt for and connect contextual clues to understand what they read can be. 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.

And he refused to specialize in anything, preferring to keep an eye on the overall estate rather than any of its parts. . . . And Nikolay’s management produced the most brilliant results. —Leo Tolstoy, War and Peace

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.

Modern work demands knowledge transfer: the ability to apply knowledge to new situations and different domains. Our most fundamental thought processes have changed to accommodate increasing complexity and the need to derive new patterns rather than rely only on familiar ones. Our conceptual classification schemes provide a scaffolding for connecting knowledge, making

Especially now, when all the information is on your phone. You have people walking around with all the knowledge of humanity on their phone, but they have no idea how to integrate it. We don’t train people in thinking or reasoning.

Mostly, though, students get what economist Bryan Caplan called narrow vocational training for jobs few of them will ever have. 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. As the historian and philosopher Arnold Toynbee said when he described analyzing the world in an age of technological and social change, “No tool is omnicompetent.” •

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.

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.

Tetlock conferred nicknames (borrowed from philosopher Isaiah Berlin) that became famous throughout the psychology and intelligence-gathering communities: the narrow-view hedgehogs, who “know one big thing,” and the integrator foxes, who “know many little things.

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.

the best forecasters, it is not what they think, but how they think.

Computational thinking is using abstraction and decomposition when attacking a large complex task,” she wrote. “It is choosing an appropriate representation for a problem.

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.

„Be careful not to be too careful“, Delbrück warned, „or you will unconsciously limit your exploration.

In Gilbert’s terms, we are works in progress claiming to be finished.

T-people like myself can happily go to the I-people with questions to create the trunk for the T,

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.

As education pioneer John Dewey put it in Logic, The Theory of Inquiry, “a problem well put is half-solved.

Susan Polgar has written, “you can get a lot further by being very good in tactics”—that is, knowing a lot of patterns—“and have only a basic understanding of strategy.

In the most devilishly wicked learning environments, experience will reinforce the exact wrong lessons.

She found that the most effective leaders and organizations had range;

It is no wonder that organizations struggle to cultivate experts who are both proficient with their tools and prepared to drop them.

Where length of experience did not differentiate creators, breadth of experience did.

Exploration is not just a whimsical luxury of education; it is a central benefit.

In the wicked world, with ill-defined challenges and few rigid rules, range can be a life hack.

Short-term rehearsal gave purely short-term benefits. Struggling to hold on to information and then recall it had helped the group distracted by math problems transfer the information from short-term to long-term memory. The group with more and immediate rehearsal opportunity recalled nearly nothing on the pop quiz. Repetition, it turned out, was less important than struggle. It isn’t bad to get an answer right while studying. Progress just should not happen too quickly,

I was not the type of person who wanted to spend my entire life learning one or two things new to the world, but rather the type who wanted constantly to learn things new to me and share them.

Dark horses were on the hunt for match quality. “They never look around and say, ‘Oh, I’m going to fall behind, these people started earlier and have more than me at a younger age,’” Ogas told me. “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.

Yokoi was the first to admit it. “I don’t have any particular specialist skills,” he once said. “I have a sort of vague knowledge of everything.” 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. “The producer knows that there’s such a thing as a semiconductor, but doesn’t need to know its inner workings. . . . That can be left to the experts.” He argued, “Everyone takes the approach of learning detailed, complex skills. If no one did this then there wouldn’t be people who shine as engineers. . . . Looking at me, from the engineer’s perspective, it’s like, ‘Look at this idiot,’ but once you’ve got a couple hit products under your belt, this word ‘idiot’ seems to slip away somewhere.

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.

A separate, international team analyzed more than a half million research articles, and classified a paper as “novel” if it cited two other journals that had never before appeared together. Just one in ten papers made a new combination, and only one in twenty made multiple new combinations. The group tracked the impact of research papers over time. They saw that papers with new knowledge combinations were more likely to be published in less prestigious journals, and also much more likely to be ignored upon publication. They got off to a slow start in the world, but after three years, the papers with new knowledge combos surpassed the conventional papers, and began accumulating more citations from other scientists. Fifteen years after publication, studies that made multiple new knowledge combinations were way more likely to be in the top 1 percent of most-cited papers. 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. •

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.

Sometimes you just slap your head and go, ‘Well why didn’t I think of that?’ If it was easily solved by people within the industry, it would have been solved by people within the industry,” Pegau said. “I think it happens more often than we’d love to admit, because we tend to view things with all the information we’ve gathered in our industry, and sometimes that puts us down a path that goes into a wall. It’s hard to back up and find another path.

In 2009, Kahneman and Klein took the unusual step of coauthoring a paper in which they laid out their views and sought common ground. And they found it. Whether or not experience inevitably led to expertise, they agreed, depended entirely on the domain in question. 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.

it is better to be a scientist of yourself, asking smaller questions that can actually be tested...Be a flirt with your possible selves. Rather than a grand plan, find experiments that can be undertaken quickly. "Test and learn...

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.

Scientists and members of the general public are about equally likely to have artistic hobbies, but scientists inducted into the highest national academies are much more likely to have avocations outside of their vocation. And those who have won the Nobel Prize are more likely still. Compared to other scientists, Nobel laureates are at least twenty-two times more likely to partake as an amateur actor, dancer, magician, or other type of performer. Nationally recognized scientists are much more likely than other scientists to be musicians, sculptors, painters, printmakers, woodworkers, mechanics, electronics tinkerers, glassblowers, poets, or writers, of both fiction and nonfiction. And, again, Nobel laureates are far more likely still.

It is no wonder that organizations struggle to cultivate experts who are both proficient with their tools and prepared to drop them. But there is an organizational strategy that can help. The strategy, strange as it sounds, is to send a mixed message.

Compared to the Tiger Mother’s tome, a parenting manual oriented toward creative achievement would have to open with a much shorter list of rules. In offering advice to parents, psychologist Adam Grant noted that creativity may be difficult to nurture, but it is easy to thwart. He pointed to a study that found an average of six household rules for typical children, compared to one in households with extremely creative children. The parents with creative children made their opinions known after their kids did something they didn’t like, they just did not proscribe it beforehand. Their households were low on prior restraint.

Twenty thousand volunteers responded, agonizing over everything from whether they should get a tattoo, try online dating, or have a child, to the 2,186 people who were pondering a job change.* But could they really trust a momentous decision to chance? The answer for the potential job changers who flipped heads was: only if they wanted to be happier. Six months later, those who flipped heads and switched jobs were substantially happier than the stayers.* 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.

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.

At the first ever Girl Scout training event Hesselbein attended, she heard another new troop leader complain that she was getting nothing from the session. Hesselbein mentioned it to a dress-factory worker who was also volunteering, and the woman told her, “You have to carry a big basket to bring something home.” She repeats that phrase today, to mean that a mind kept wide open will take something from every new experience. It is a natural philosophy for someone who was sixty when she attempted to turn down an interview for the job that became her calling. She had no long-term plan, only a plan to do what was interesting or needed at the moment. “I never envisioned” is her most popular preamble. Hesselbein’s professional career, which started in her midfifties, was extraordinary. The meandering path, however, was not.

The "deliberate amateur"... "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," ...Be careful not to be too careful, or you will unconsciously limit your exploration.

It isn’t just the increase in new knowledge that generates opportunities for nonspecialists, though. In a race to the forefront, a lot of useful knowledge is simply left behind to molder. That presents another kind of opportunity for those who want to create and invent but who cannot or simply do not want to work at the cutting edge. They can push forward by looking back; they can excavate old knowledge but wield it in a new way.

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. It is a powerful tool for solving wicked problems, and Kepler was an analogy addict, so Gentner is naturally very fond of him.

The fadeout was not a disappearance of skill so much as the rest of the world catching up. The motor-skill equivalent would be teaching a kid to walk a little early. Everyone is going to learn it anyway, and while it might be temporarily impressive, there is no evidence that rushing it matters.

I always advise my people to read outside your field, everyday something. And most people say, ‘Well, I don’t have time to read outside my field.’ I say, ‘No, you do have time, it’s far more important.’ Your world becomes a bigger world, and maybe there’s a moment in which you make connections.

Individual creators started out with lower innovativeness than teams—they were less likely to produce a smash hit—but as their experience broadened they actually surpassed teams: an individual creator who had worked in four or more genres was more innovative than a team whose members had collective experience across the same number of genres. Taylor and Greve suggested that “individuals are capable of more creative integration of diverse experiences than teams are.

a system that leads people to downplay previous experiences, as if they were entirely wasted, is a counterproductive one. We shouldn’t be ashamed of broad experience, or of needing time to find match quality. Take it from Angela Duckworth, the researcher whose work popularized the psychological construct of “grit.

In that way, the students had something in common with Luria’s remote villagers—even the science majors were typically unable to generalize research methods from their own field to other fields. Flynn’s conclusion: “There is no sign that any department attempts to develop [anything] other than narrow critical competence.

The Columbia Accident Investigation Board concluded that NASA’s culture “emphasized chain of command, procedure, following the rules, and going by the book. While rules and procedures were essential for coordination, they had an unintended negative effect.” Once again, “allegiance to hierarchy and procedure” had ended in disaster. Again, lower ranking engineers had concerns they could not quantify; they stayed silent because “the requirement for data was stringent and inhibiting.

Yokoi had no desire (or capability) to compete with electronics companies that were racing one another to invent some entirely new sliver of dazzling technology. Nor could Nintendo compete with Japan’s titans of traditional toys—Bandai, Epoch, and Takara—on their familiar turf. With that, and Drive Game, in mind, Yokoi embarked on an approach he called “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. The heart of his philosophy was putting cheap, simple technology to use in ways no one else considered.

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.” Diverse experience was impactful when created by platoon in teams, and even more impactful when contained within an individual.

Interventional cardiologists have gotten so used to treating chest pain with stents—metal tubes that pry open blood vessels—that they do so reflexively even in cases where voluminous research has proven that they are inappropriate or dangerous. A recent study found that cardiac patients were actually less likely to die if they were admitted during a national cardiology meeting, when thousands of cardiologists were away; the researchers suggested it could be because common treatments of dubious effect were less likely to be performed.

There are no tools that cannot be dropped, reimagined, or repurposed in order to navigate an unfamiliar challenge. Even the most sacred tools

the students of more experienced and qualified

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.

difference between the chain of command and the chain of communication, and that the difference represents a healthy cross-pressure.

No tool is omnicompetent. There is no such thing as a master-key that will unlock all doors. —Arnold Toynbee, A Study of History

Struggling to hold on to information and then recall it had helped the group distracted by math problems transfer the information from short-term to long-term memory.

Fifteen years after publication, studies that made multiple new knowledge combinations were way more likely to be in the top 1 percent of most-cited papers.

recognized what artificial intelligence scholars call Moravec’s paradox: machines and humans frequently have opposite strengths and weaknesses.

humans empowered to do what they do best without the prerequisite of years of specialized pattern recognition.

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.

today’s children are far better at solving problems on the spot without a previously learned method for doing so,” Flynn concluded.

Chunking can seem like magic, but it comes from extensive, repetitive practice.

It is not that we are unable to come up with contrary ideas, it is just that our strong instinct is not to.

This is a widespread phenomenon. 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. Psychologists have shown repeatedly that the more internal details an individual can be made to consider, the more extreme their judgment becomes.

Professors who excel at promoting contemporaneous student achievement,” the economists wrote, “on average, harm the subsequent performance of their students in more advanced classes.

The very tool that had helped make NASA so consistently successful, what Diane Vaughan called “the original technical culture” in the agency’s DNA, suddenly worked perversely in a situation where the familiar brand of data did not exist. Reason without numbers was not accepted. In the face of an unfamiliar challenge, NASA managers failed to drop their familiar tools.

When I was a college runner, I had teammates whose drive and determination seemed almost boundless on the track, and nearly absent in the classroom, and vice versa. 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.

The expression “young and foolish,” he wrote, describes the tendency of young adults to gravitate to risky jobs, but it is not foolish at all. It is ideal. They have less experience than older workers, and so the first avenues they should try are those with high risk and reward, and that have high informational value. Attempting to be a professional athlete or actor or to found a lucrative start-up is unlikely to succeed, but the potential reward is extremely high. Thanks to constant feedback and an unforgiving weed-out process, those who try will learn quickly if they might be a match, at least compared to jobs with less constant feedback. If they aren’t, they go test something else, and continue to gain information about their options and themselves.

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.

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. In that way, they are just about the precise opposite of experts who develop in kind learning environments, like chess masters, who rely heavily on intuition.

an official with the U.S. Securities and Exchange Commission learned I was writing about specialization and contacted me to make sure I knew that 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.

Experimentation is not a tidy prescription, but it is common, and it has advantages, and it requires more than the typical motivational-poster lip service to a tolerance for failure. Breakthroughs are high variance.

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

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.

Duckworth learned that the Whole Candidate Score—an agglomeration of standardized test scores, high school rank, physical fitness tests, and demonstrated leadership—is the single most important factor for admission, but that it is useless for predicting who will drop out before completing Beast. She had been talking to high performers across domains, and decided to study passion and perseverance, a combination she cleverly formulated as “grit.

At one point they morphed into standardized forms that had to be filled out. Monday Notes became one more rigid formality in a process culture. “Immediately, the quality of the notes fell,” wrote another official NASA historian.

companies do their most impactful creative work in a crisis, because the disciplinary boundaries fly out the window. “Communication really happens in the carpool,” he once said. He made sure that “dabble time” was a cultural staple.

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.

In an age when alchemy was still a common approach to natural phenomena, Kepler filled the universe with invisible forces acting all around us, and helped usher in the Scientific Revolution. His fastidious documentation of every meandering path his brain blazed is one of the great records of a mind undergoing creative transformation. 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.

It may very well be that if you were to take all the research funding in the country and you put it in Alzheimer's disease, you would never get to the solution. But the answer to Alzheimer's disease may come from a misfolding protein in a cucumber. But how are you going to write a grant on a cucumber? And who are you going to send it to? If somebody gets interested in a folding protein in a cucumber and it's a good scientific question, leave them alone. Let them torture the cucumber.

The reason that elite athletes seem to have superhuman reflexes is that they recognize patterns of ball or body movements that tell them what’s coming before it happens. When tested outside of their sport context, their superhuman reactions disappear.

Dropping familiar tools is particularly difficult for experienced professionals who rely on what Weick called over learned 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.

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. At the time it might seem like a great idea, but the more you experience, the less great that idea looks in hindsight. In England and Wales, adults were more likely to get divorced from the careers they had invested in because they settled down too early.

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, as Don Swanson called it. The larger and more easily accessible the library of human knowledge, the more chances for inquisitive patrons to make connections at the cutting edge. An operation like InnoCentive, which at first blush seems totally counterintuitive, should become even more fruitful as specialization accelerates.

Other feelings too can be philosophical—pain, grief, tedium, delight, exultation—if they are experienced on behalf of humankind. “I looked around me, and my soul became wounded by the suffering of mankind” is the opening of Alexander Radishchev’s “Journey from St. Petersburg to Moscow” (1790), which laid the foundation of all subsequent Russian philosophy. It is a philosophy shaped by feelings of suffering and compassion, by the Karamazovian question of how to justify a child’s tears. The range of philosophical feelings is wide.

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.

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.

Uzzi and a team analyzed eighteen million papers from a variety of scientific domains to see whether atypical knowledge combinations mattered. If a particular paper cited other areas of research that rarely, if ever, appeared together, then it was classified as having used an atypical combination of knowledge.

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.

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.

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.

including thousands of paintings in his unique, semi-cartoonish style, often densely packed with animals and figures—Elvis, George Washington, angels—and set fancifully in apocalyptic landscapes. In short order, he was appearing on Johnny Carson’s Tonight Show and creating album covers for R.E.M. and Talking Heads. Upon entry to the garden, I was greeted by a giant self-portrait of a smirking Finster in a burgundy suit, affixed to a cinderblock wall. At the bottom are the words “I began painting pictures in Jan-1976—without any training. This is my painting. A person don’t know what he can do unless he tryes. Trying things is the answer to find your talent.

If you write an interdisciplinary grant proposal, it goes to people who are really, really specialized in A or B, and maybe if you’re lucky they have the capacity to see the connections at the interface of A and B,” he told me. “Everyone acknowledges that great progress is made at the interface, but who is there to defend the interface?

Ideally, intellectual sparring partners “hone each other’s arguments so that they are sharper and better,” Yale historian Paul Sabin wrote. “The opposite happened with Paul Ehrlich and Julian Simon.” As each man amassed more information for his own view, each became more dogmatic, and the inadequacies in their models of the world more stark.

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.

Olympic athletes need to understand that the rules for life are different from the rules for sports,” she wrote. “Yes, striving to accomplish a single overarching goal every day means you have grit, determination and resilience. But the ability to pull yourself together mentally and physically in competition is different from the new challenges that await you. So after you retire, travel, write a poem, try to start your own business, stay out a little too late, devote time to something that doesn’t have a clear end goal.” 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.

Facing uncertain environments and wicked problems, breadth of experience is invaluable. Facing kind problems, narrow specialization can be remarkably efficient. The problem is that we often expect the hyperspecialist, because of their expertise in a narrow area, to magically be able to extend their skill to wicked problems. The results can be disastrous.

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.

As Alph Bingham noticed, for difficult challenges organizations tend toward local search. They rely on specialists in a single knowledge domain, and methods that have worked before. (Think about the lab with only E. coli specialists from chapter 5.) If those fail, they’re stuck. For the most intractable problems, “our research shows that a domain-based solution is often inferior,

around 90 percent of major infrastructure projects worldwide go over budget (by an average of 28 percent) in part because 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.

There is a particular kind of thinker, one who becomes more entrenched in their single big idea about how the world works even in the face of contrary facts, whose predictions become worse, not better, as they amass information for their mental representation of the world. They are on television and in the news every day, making worse and worse predictions while claiming victory, and they have been rigorously studied.

Paul Graham, computer scientist and cofounder of Y Combinator—the start-up funder of Airbnb, Dropbox, Stripe, and Twitch—encapsulated Ibarra’s tenets in a high school graduation speech he wrote, but never delivered: It might seem that nothing would be easier than deciding what you like, but it turns out to be hard, partly because it’s hard to get an accurate picture of most jobs. . . . 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. And yet every May, speakers all over the country fire up the Standard Graduation Speech, the theme of which is: don’t give up on your dreams. I know what they mean, but this is a bad way to put it, because it implies you’re supposed to be bound by some plan you made early on. The computer world has a name for this: premature optimization. . . . . . . Instead of working back from a goal, work forward from promising situations. This is what most successful people actually do anyway. In the graduation-speech approach, you decide where you want to be in twenty years, and then ask: what should I do now to get there? 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.

In four separate fires in the 1990s, twenty-three elite wildland firefighters refused orders to drop their tools and perished beside them. Even when Rhoades eventually dropped his chainsaw, he felt like he was doing something unnatural. Weick found similar phenomena in Navy seamen who ignored orders to remove steel-toed shoes when abandoning a ship, and drowned or punched holes in life rafts; fighter pilots in disabled planes refusing orders to eject; and Karl Wallenda, the world-famous high-wire performer, who fell 120 feet to his death when he teetered and grabbed first at his balance pole rather than the wire beneath him. He momentarily lost the pole while falling, and grabbed it again in the air. “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.

What its withered technology lacked, the Game Boy made up in user experience. It was cheap. It could fit in a large pocket. It was all but indestructible. If a drop cracked the screen—and it had to be a horrific drop—it kept on ticking. If it were left in a backpack that went in the washing machine, once it dried out it was ready to roll a few days later. Unlike its power-guzzling color competitors, it played for days (or weeks) on AA batteries. Old hardware was extremely familiar to developers inside and outside Nintendo, and with their creativity and speed unencumbered by learning new technology, they pumped out games as if they were early ancestors of iPhone app designers—Tetris, Super Mario Land, The Final Fantasy Legend, and a slew of sports games released in the first year were all smash hits. With simple technology, Yokoi’s team sidestepped the hardware arms race and drew the game programming community onto its team.

In 2016, Japanese biologist Yoshinori Ohsumi closed his Nobel lecture ominously: “Truly original discoveries in science are often triggered by unpredictable and unforeseen small findings. . . . Scientists are increasingly required to provide evidence of immediate and tangible applications of their work.” That is head start fervor come full circle; explorers have to pursue such narrowly specialized goals with such hyperefficiency that they can say what they will find before they look for it.

A nice idea, but here’s how it worked out in practice: a bank arm that specialized in mortgage lending started the homeowner on lower payments; an arm of the same bank that specialized in foreclosures then noticed that the homeowner was suddenly paying less, declared them in default, and seized the home. “No one imagined silos like that inside banks,” a government adviser said later. Overspecialization can lead to collective tragedy even when every individual separately takes the most reasonable course of action.

Only years later—as an investigative journalist writing about poor scientific research—did I realize that I had committed statistical malpractice in one section of the thesis that earned me a master’s degree from Columbia University. Like many a grad student, I had a big database and hit a computer button to run a common statistical analysis, never having been taught to think deeply (or at all) about how that statistical analysis even worked. The stat program spit out a number summarily deemed “statistically significant.” Unfortunately, it was almost certainly a false positive, because I did not understand the limitations of the statistical test in the context in which I applied it. Nor did the scientists who reviewed the work. 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.” I rushed into extremely specialized scientific research without having learned scientific reasoning. (And then I was rewarded for it, with a master’s degree, which made for a very wicked learning environment.) As backward as it sounds, I only began to think broadly about how science should work years after I left it.

repeated the De Groot exercise, but added a wrinkle. This time, the chess players were also given boards with the pieces in an arrangement that would never actually occur in a game. Suddenly, the experts performed just like the lesser players. The grandmasters never had photographic memories after all. 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.

You can do your entire career on one cell type and it’s more likely you keep your job by getting grants,” Casadevall told me. “There is not even pressure to integrate. In fact, if you write a grant proposal about how the B cell is integrating with the macrophage [a basic interaction of the immune system],* there may be no one to review it. If it goes to the macrophage people, they say, ‘Well, I don’t know anything about it. Why B cells?’ The system maintains you in a trench. You basically have all these parallel trenches, and it’s very rare that anybody stands up and actually looks at the next trench to see what they are doing, and often it’s related.

And the more distant the analogy, the better it was for idea generation. Students who were pointed to Nike and McDonald’s generated more strategic options than their peers who were reminded of computer companies Apple and Dell. Just being reminded to analogize widely made the business students more creative. Unfortunately, students also said that if they were to use analogy companies at all, they believed the best way to generate strategic options would be to focus on a single example in the same field. Like the venture capitalists, their intuition was to use too few analogies, and to rely on those that were the most superficially similar. “That’s usually exactly the wrong way to go about it regardless of what you’re using analogy for,” Lovallo told me.

In 1998, he helped organize the first “advanced chess” tournament, in which each human player, including Kasparov himself, paired with a computer. Years of pattern study were obviated. The machine partner could handle tactics so the human could focus on strategy. It was like Tiger Woods facing off in a golf video game against the best gamers. His years of repetition would be neutralized, and the contest would shift to one of strategy rather than tactical execution. In chess, it changed the pecking order instantly. “Human creativity was even more paramount under these conditions, not less,” according to Kasparov. Kasparov settled for a 3–3 draw with a player he had trounced four games to zero just a month earlier in a traditional match. “My advantage in calculating tactics had been nullified by the machine.” The primary benefit of years of experience with specialized training was outsourced, and in a contest where humans focused on strategy, he suddenly had peers. A few years later, the first “freestyle chess” tournament was held. Teams could be made up of multiple humans and computers. The lifetime-of-specialized-practice advantage that had been diluted in advanced chess was obliterated in freestyle. A duo of amateur players with three normal computers not only destroyed Hydra, the best chess supercomputer, they also crushed teams of grandmasters using computers. Kasparov concluded that the humans on the winning team were the best at “coaching” multiple computers on what to examine, and then synthesizing that information for an overall strategy. Human/Computer combo teams—known as “centaurs”—were playing the highest level of chess ever seen. If Deep Blue’s victory over Kasparov signaled the transfer of chess power from humans to computers, the victory of centaurs over Hydra symbolized something more interesting still: humans empowered to do what they do best without the prerequisite of years of specialized pattern recognition.

So, about that one sentence of advice: Don’t feel behind. Two Roman historians recorded that when Julius Caesar was a young man he saw a statue of Alexander the Great in Spain and broke down in tears. “Alexander at my age had conquered so many nations, and I have all this time done nothing that is memorable,” he supposedly said. Pretty soon, that concern was a distant memory and Caesar was in charge of the Roman Republic—which he turned into a dictatorship before he was murdered by his own pals. It’s fair to say that like most youth athletes with highlight reels, he peaked early. 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. Instead, as Herminia Ibarra suggested for the proactive pursuit of match quality, start planning experiments. Your personal version of Friday night or Saturday morning experiments, perhaps.

In 1931, amid that incredible transformation, a brilliant young Russian psychologist named Alexander Luria recognized a fleeting “natural experiment,” unique in the history of the world. He wondered if changing citizens’ work might also change their minds. When Luria arrived, the most remote villages had not yet been touched by the warp-speed restructuring of traditional society. Those villages gave him a control group. He learned the local language and brought fellow psychologists to engage villagers in relaxed social situations—teahouses or pastures—and discuss questions or tasks designed to discern their habits of mind. Some were very simple: present skeins of wool or silk in an array of hues and ask participants to describe them. The collective farmers and farm leaders, as well as the female students, easily picked out blue, red, and yellow, sometimes with variations, like dark blue or light yellow. The most remote villagers, who were still “premodern,” gave more diversified descriptions: cotton in bloom, decayed teeth, a lot of water, sky, pistachio. Then they were asked to sort the skeins into groups. The collective farmers, and young people with even a little formal education, did so easily, naturally forming color groups. Even when they did not know the name of a particular color, they had little trouble putting together darker and lighter shades of the same one. The remote villagers, on the other hand, refused, even those whose work was embroidery. “It can’t be done,” they said, or, “None of them are the same, you can’t put them together.” When prodded vigorously, and only if they were allowed to make many small groups, some relented and created sets that were apparently random. A few others appeared to sort the skeins according to color saturation, without regard to the color. Geometric shapes followed suit. The greater the dose of modernity, the more likely an individual grasped the abstract concept of “shapes” and made groups of triangles, rectangles, and circles, even if they had no formal education and did not know the shapes’ names. The remote villagers, meanwhile, saw nothing alike in a square drawn with solid lines and the same exact square drawn with dotted lines. To Alieva, a twenty-six-year-old remote villager, the solid-line square was obviously a map, and the dotted-line square was a watch. “How can a map and a watch be put together?” she asked, incredulous. Khamid, a twenty-four-year-old remote villager, insisted that filled and unfilled circles could not go together because one was a coin and the other a moon.

When players study all those patterns, they are mastering tactics. Bigger-picture planning in chess—how to manage the little battles to win the war—is called strategy. As Susan Polgar has written, “you can get a lot further by being very good in tactics”—that is, knowing a lot of patterns—“and have only a basic understanding of strategy.” Thanks to their calculation power, computers are tactically flawless compared to humans. Grandmasters predict the near future, but computers do it better. What if, Kasparov wondered, computer tactical prowess were combined with human big-picture, strategic thinking? In 1998, he helped organize the first “advanced chess” tournament, in which each human player, including Kasparov himself, paired with a computer. Years of pattern study were obviated. The machine partner could handle tactics so the human could focus on strategy. It was like Tiger Woods facing off in a golf video game against the best gamers. His years of repetition would be neutralized, and the contest would shift to one of strategy rather than tactical execution. In chess, it changed the pecking order instantly. “Human creativity was even more paramount under these conditions, not less,” according to Kasparov. Kasparov settled for a 3–3 draw with a player he had trounced four games to zero just a month earlier in a traditional match. “My advantage in calculating tactics had been nullified by the machine.” The primary benefit of years of experience with specialized training was outsourced, and in a contest where humans focused on strategy, he suddenly had peers. A few years later, the first “freestyle chess” tournament was held. Teams could be made up of multiple humans and computers. The lifetime-of-specialized-practice advantage that had been diluted in advanced chess was obliterated in freestyle. A duo of amateur players with three normal computers not only destroyed Hydra, the best chess supercomputer, they also crushed teams of grandmasters using computers. Kasparov concluded that the humans on the winning team were the best at “coaching” multiple computers on what to examine, and then synthesizing that information for an overall strategy. Human/Computer combo teams—known as “centaurs”—were playing the highest level of chess ever seen. If Deep Blue’s victory over Kasparov signaled the transfer of chess power from humans to computers, the victory of centaurs over Hydra symbolized something more interesting still: humans empowered to do what they do best without the prerequisite of years of specialized pattern recognition.