Range: Why Generalists Triumph in a Specialized World

by David Epstein

Eventual elites typically devote less time early on to deliberate practice in the activity in which they will eventually become experts. Instead, they undergo what researchers call a “sampling period.” They play a variety of sports, usually in an unstructured or lightly structured environment; they gain a range of physical proficiencies from which they can draw; they learn about their own abilities and proclivities; and only later do they focus in and ramp up technical practice in one area.

I dove into work showing that highly credentialed experts can become so narrow-minded that they actually get worse with experience, even while becoming more confident—a dangerous combination. And I was stunned when cognitive psychologists I spoke with led me to an enormous and too often ignored body of work demonstrating that learning itself is best done slowly to accumulate lasting knowledge, even when that means performing poorly on tests of immediate progress. That is, the most effective learning looks inefficient; it looks like falling behind.

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.

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.

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.”

Tiger parents are trying to skip that phase entirely. It reminds me of a conversation I had with Ian Yates, a British sports scientist and coach who helped develop future professional athletes in a range of sports. Parents, Yates told me, increasingly come to him and “want their kids doing what the Olympians are doing right now, not what the Olympians were doing when they were twelve or thirteen,” which included a wider variety of activities that developed their general athleticism and allowed them to probe their talents and interests before they focused narrowly on technical skills. The sampling period is not incidental to the development of great performers—something to be excised in the interest of a head start—it is integral.

Charles Limb, a musician, hearing specialist, and auditory surgeon at the University of California, San Francisco, designed an iron-free keyboard so that jazz musicians could improvise while inside an MRI scanner. Limb saw that brain areas associated with focused attention, inhibition, and self-censoring turned down when the musicians were creating. “It’s almost as if the brain turned off its own ability to criticize itself,” he told National Geographic. While improvising, musicians do pretty much the opposite of consciously identifying errors and stopping to correct them.

In totality, the picture is in line with a classic research finding that is not specific to music: breadth of training predicts breadth of transfer. That is, the more contexts in which something is learned, the more the learner creates abstract models, and the less they rely on any particular example. Learners become better at applying their knowledge to a situation they’ve never seen before, which is the essence of creativity.

In offering advice to parents, psychologist Adam Grant noted that creativity may be difficult to nurture, but it is easy to thwart. 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.

Being forced to generate answers improves subsequent learning even if the generated answer is wrong. It can even help to be wildly wrong. Metcalfe and colleagues have repeatedly demonstrated a “hypercorrection effect.” The more confident a learner is of their wrong answer, the better the information sticks when they subsequently learn the right answer. Tolerating big mistakes can create the best learning opportunities.*

Psychologist Kevin Dunbar began documenting how productive labs work in the 1990s, and stumbled upon a modern version of Keplerian thinking. Faced with an unexpected finding, rather than assuming the current theory is correct and that an observation must be off, the unexpected became an opportunity to venture somewhere new—and analogies served as the wilderness guide.

Dunbar witnessed important breakthroughs live, and saw that the labs most likely to turn unexpected findings into new knowledge for humanity made a lot of analogies, and made them from a variety of base domains. 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.

Seth Godin, author of some of the most popular career writing in the world, wrote a book disparaging the idea that “quitters never win.” Godin argued that “winners”—he generally meant individuals who reach the apex of their domain—quit fast and often when they detect that a plan is not the best fit, and do not feel bad about it. “We fail,” he wrote, when we stick with “tasks we don’t have the guts to quit.”

Ogas and Rose call this the “context principle.” In 2007, Mischel wrote, “The gist of such findings is that the child who is aggressive at home may be less aggressive than most when in school; the man exceptionally hostile when rejected in love may be unusually tolerant about criticism of his work; the one who melts with anxiety in the doctor’s office may be a calm mountain climber; the risk-taking entrepreneur may take few social risks.” Rose framed it more colloquially: “If you are conscientious and neurotic while driving today, it’s a pretty safe bet you will be conscientious and neurotic while driving tomorrow. At the same time . . . you may not be conscientious and neurotic when you are playing Beatles cover songs with your band in the context of the local pub.” Perhaps that is one reason Daniel Kahneman and his colleagues in the military (chapter 1) failed to predict who would be a leader in battle based on who had been a leader in an obstacle course exercise. 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 central premise was at once simple and profound: we learn who we are only by living, and not before.

“It gave me this template for seeing my career. Virtually every good thing in my life I can trace back to a misfortune, so my feeling is you don’t know what’s good and what’s bad when things happen. You do not know. You have to wait to find out.”

somehow someone’s solution was always cleverer than the others. I was paying attention, and I noticed that the most clever solution always came from a piece of knowledge that was not a part of the normal curriculum.”

group of optics specialists he consulted assured him it could not be done, which was exactly what he wanted to hear. “If they say, ‘It’s a great idea, go for it, makes sense,’ what is the chance you’re the first person to come up with it? Precisely zero,” he told me.

Incredibly, the hedgehogs performed especially poorly on long-term predictions within their domain of expertise. They actually got worse as they accumulated credentials and experience in their field. The more information they had to work with, the more they could fit any story to their worldview.

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. In the sweep of humanity, that is not normal.

Skillful forecasters depart from the problem at hand to consider completely unrelated events with structural commonalities rather than relying on intuition based on personal experience or a single area of expertise.

The experiments showed that an effective problem-solving culture was one that balanced standard practice—whatever it happened to be—with forces that pushed in the opposite direction. If managers were used to process conformity, encouraging individualism helped them to employ “ambidextrous thought,” and learn what worked in each situation. If they were used to improvising, encouraging a sense of loyalty and cohesion did the job. The trick was expanding the organization’s range by identifying the dominant culture and then diversifying it by pushing in the opposite direction.

Human creativity, he said, is basically an “import/export business of ideas.”

“A jack-of-all-trades is a master of none, but oftentimes better than a master of one.”

“Listening to @DavidEpstein ‘Range’ in the car with 12 year old daughter. ‘Mom, why do we make “What I want to be when I grow up” signs on the first day of school? We should make “Top 5 things I want to learn about this year” signs.’ Smart cookie. :-)” I think I’ll borrow the twelve-year-old’s idea.