“Range: Why Generalists Triumph in a Specialized World”

Why this book?

I have always held the belief that narrow specialization is the way toward achieving any remarkable success in most fields, including science and engineering. That knowing about an area more than anyone does is what sets us apart. I have looked askance at those who know something about many things but not so much about anything! This despise of generalists was a major motivation for me to pursue a graduate degree. I wanted to master ‘something’.

The book at hand has seriously challenged this belief and helped me adopt a more nuanced view. Here are a few highlights, followed by some of my favorite passages.


Experience is overrated

Several social studies have shown that experts are more prone to making mistakes when they encounter a new situation.

A manifestation of this observation is the failure of experts to predict the future. The psychologist Philip Tetlock asked 284 highly educated experts to make specific predictions about specific future events and tracked their predictions for 20 years. The so called “experts” have done horribly. As Tetlock put it, they were not better than dart-throwing chimps.

Among high achievers, early specialization is not the rule

It’s a common belief that high achievers start learning and practicing early, which give them a head start. This contradicts with many observations. 

German scientists published a study in 2014 showing that members of their national team, which had just won the World Cup, were typically late specializers who didn’t play more organized soccer than amateur-league players until age twenty-two or later.

The recommendation: experimentation

In order to contribute something meaningful, a more optimal path than early specialization is experimenting in many fields and then focusing on solving a particular problem, aided with the breadth gained while experimenting.


Everyone needs habits of mind that allow them to dance across disciplines… The goal is not just to transfer knowledge, but to raise fundamental questions and to become familiar with the powerful ideas that shape our society.

Jeannette Wing, a computer science professor at Columbia University and former corporate vice president of Microsoft Research, has pushed broad “computational thinking” as the mental Swiss Army knife. She advocated that it become as fundamental as reading, even for those who will have nothing to do with computer science or programming. “Computational thinking is using abstraction and decomposition when attacking a large complex task,” she wrote. “It is choosing an appropriate representation for a problem.

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.

They were perfectly capable of learning from experience, but failed at learning without experience

For learning that is both durable (it sticks) and flexible (it can be applied broadly), fast and easy is precisely the problem. [A study showed that] being forced to generate answers improves subsequent learning even if the generated answer is wrong. It can even help to be wildly wrong.

Struggling to retrieve information primes the brain for subsequent learning, even when the retrieval itself is unsuccessful. The struggle is real, and really useful. “Like life,” Kornell and team wrote, “retrieval is all about the journey. 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.

How useful is a head start? Closed vs. open skills:

In 2017, Greg Duncan, the education economist, along with psychologist Drew Bailey and colleagues, reviewed sixty-seven early childhood education programs meant to boost academic achievement. Programs like Head Start did give a head start, but academically that was about it. The researchers found a pervasive “fadeout” effect, where a temporary academic advantage quickly diminished and often completely vanished. On a graph, it looks eerily like the kind that show future elite athletes catching up to their peers who got a head start in deliberate practice.

A reason for this, the researchers concluded, is that early childhood education programs teach “closed” skills that can be acquired quickly with repetition of procedures, but that everyone will pick up at some point anyway. 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.

The research team recommended that if programs want to impart lasting academic benefits they should focus instead on “open” skills that scaffold later knowledge. 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.”

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

“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. Malamud’s [an economist at Northwestern University] 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.

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.

Fantasy writer Patrick Rothfuss began studying chemical engineering in college, which “led to a revelation that chemical engineering is boring.” He then spent nine years bouncing between majors “before being kindly asked to graduate already.” After that, according to his official bio, “Patrick went to grad school. He’d rather not talk about it.” Meanwhile, he was slowly working on a novel. That novel, The Name of the Wind (in which chemistry appears repeatedly), sold millions of copies worldwide and is source material for a potential TV successor to Game of Thrones.

As a mathematician, [Freeman] Dyson labeled himself a frog, but contended “It is stupid to claim that birds are better than frogs because they see farther, or that frogs are better than birds because they see deeper.” The world, he wrote, is both broad and deep. “We need birds and frogs working together to explore it.” Dyson’s concern was that science is increasingly overflowing with frogs, trained only in a narrow specialty and unable to change as science itself does. “This is a hazardous situation,” he warned, “for the young people and also for the future of science.”

Fortunately, it is possible, even today, even at the cutting edge, even in the most hyperspecialized specialties, to cultivate land where both birds and frogs can thrive.

Specialization is obvious: keep going straight. Breadth is trickier to grow. A subsidiary of PricewaterhouseCoopers that studied technological innovation over a decade found that there was no statistically significant relationship between R+D spending and performance.* (Save for the bottom 10 percent of spenders, which did perform worse than their peer companies.) Seeding the soil for generalists and polymaths who integrate knowledge takes more than money. It takes opportunity.

[corporate scientist at 3M Jayshree Seth, a chemical engineer said]: 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. It’s mosaic building. I just keep putting those tiles together. Imagine me in a network where I didn’t have the ability to access all these people. That really wouldn’t work well

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.

In wicked domains that lack automatic feedback, experience alone does not improve performance. Effective habits of mind are more important, and they can be developed. In four straight years of forecasting tournaments, Tetlock and Mellers’s research group showed that an hour of basic training in foxy habits improved accuracy. Basically, forecasters can improve by generating a list of separate events with deep structural similarities, rather than focusing only on internal details of the specific event in question. Few events are 100 percent novel—uniqueness is a matter of degree, as Tetlock puts it—and creating the list forces a forecaster implicitly to think like a statistician.

Good judges are good belief updaters