Range David Epstein 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 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.

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

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.*

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.

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.

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

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.

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.

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.

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.

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,

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.

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 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.

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

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.

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.

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

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

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

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

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.

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,

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.

Struggling to retrieve information primes the brain for subsequent learning,

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.

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.

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.

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

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.

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

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.

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.

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.

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.

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

...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.

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.

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.

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.

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.

cognitive entrenchment.

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

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

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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. •

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.

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 "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.

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.” •

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.

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 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.

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.

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.

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.

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.

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.

Ukrainian boxer Vasyl Lomachenko set a record for the fewest fights needed to win world titles in three different weight classes. Lomachenko, who took four years off boxing as a kid to learn traditional Ukrainian dance, reflected, “I was doing so many different sports as a young boy—gymnastics, basketball, football, tennis—and I think, ultimately, everything came together with all those different kinds of sports to enhance my footwork.

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.

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.

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,

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.

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.

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.

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.

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.

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.

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.

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.

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.