In recent years, we’ve come to assume that the formula for success is to start practicing early and refuse to quit until you’re the best in the world. We see parents hire violin teachers for kids who can barely walk, high schoolers expected to have the next decade or more of their lives planned by the time they graduate, and successful doctors who spend their entire lives studying a single gland in the human body. We view changing course, whether it be switching majors, switching jobs, or switching careers, as wasting years of past experience.
However, according to journalist David Epstein, this school of thought couldn’t be more wrong. In Range, Epstein argues that in today’s modern world, generalism—a broad competence in many professional fields—is the key to living a fulfilling and productive life. Epstein cites a robust collection of scientific evidence and recounts powerful real-life case studies to prove that there’s more than one way to become a world-class success.
You never need to despair that you’re “too late” to pursue something you’re interested in. Late bloomers and those seeking a fresh start are just as likely to become one of the greats—and, as we’ll see, may even have an advantage over those who have trained from birth to do just one thing.
To explain why, we’ll start by further defining the traditional path to excellence and explaining why it isn’t the most reliable path to success in today’s world. Then, we’ll guide you through the new generalist’s path to excellence, a style of personal growth that embraces the world as it is instead of how it should be. Lastly, we’ll show why generalists’ nontraditional background gives them an invaluable creative edge over specialists.
According to Epstein, the traditional path to excellence has been more or less treated as common sense for years. Obviously, if you want to get good at something, you have to practice a lot. By this logic, the path to success is to start training as early as possible.
If you believe in a purely linear relationship between practice time and success, specializing at a young age and never deviating from a given path would allow humans to accomplish maximum levels of greatness.
(Shortform note: This “traditional path to excellence” rose to prominence in recent years due in large part to Malcolm Gladwell’s 2008 book Outliers. Gladwell’s famed “10,000-hour rule” states that the way to become a master in any field is to spend 10,000 hours practicing. He attributes the success of virtuosos such as Mozart, the Beatles, and Bill Gates not to inherent talent, but to the sheer volume of time they spent practicing.)
However, Epstein argues that in the real world, specialization is a far less reliable life strategy than we would expect, especially in modern times. This is true for a number of reasons.
The main reason specialization isn’t ideal is that the world is far more unpredictable than we’d like to believe. Epstein distinguishes between “kind” and “wicked domains”—what we’ll call Stable and Unstable Environments.
Stable Environments are settings in which the ways to achieve success are easily understood and unchanging. Games with clearly defined rules such as basketball or billiards are Stable Environments, as are simple procedural jobs, like installing circuit boards on an assembly line. Unstable Environments are settings in which the ways to achieve success are unclear and constantly changing. As a result, training in an Unstable Environment isn’t guaranteed to make you better. The worlds of business and science are examples of Unstable Environments—in fact, almost every environment in the “real world” is unstable to a certain degree.
Epstein argues that, because they assume that the world is a largely Stable Environment, specialists strive for efficiency above all else. They assume that to reach the top of your field, all you need to do is accumulate skill as quickly as possible. Generalists, on the other hand, recognize that we live in an unstable world—it’s impossible to perfectly predict what experience will be valuable to you—“efficient” narrow training won’t necessarily pay off. Likewise, experience that feels like a waste of time often pays off in ways you could never have imagined, as we’ll see throughout this guide.
The Ludic Fallacy
Coined by Nassim Nicholas Taleb in his book The Black Swan, the “Ludic Fallacy” refers to the misapplication of Stable Environment rules to an Unstable Environment. The word “Ludic” comes from the Latin word ludus, meaning “game,” as people falsely assume that the same strategies used to calculate probability within a game can be used in the real world.
For example, Taleb explains that casinos calculate their real-world risk using the same strategies they use to calculate risk within a game like blackjack. They spend millions of dollars on high-tech security systems designed to prevent people from cheating, which, according to their calculations, profitably mitigates their risk.
However, in the Unstable Environment of the real world, the largest losses never come from the places you’d expect, making the goal of accurately calculating risk impossible. Taleb visited a casino that lost $100 million dollars after one of its entertainers was mauled by his own tiger, had to pay a gargantuan fine to the IRS after an otherwise reliable employee forgot to send in certain tax forms for years, and had to pay the ransom for the kidnapping of the casino owner’s daughter. These losses cost 1,000 times more than the cheating losses predicted by their risk analysts. Statistical models like the one the casino used to calculate risk fail in Unstable Environments.
Specialists’ path to success fails in much the same way—as we’ll see, they fail to realize that their narrow, inflexible plans keep them from taking advantage of the unpredictable.
According to Epstein, another reason specialization isn’t ideal is that it’s becoming more obsolete as time goes on. We’ve entered the knowledge economy, in which innovation and creative problem-solving are far more valuable than specialized procedures.
Generally speaking, specialization helps you do things you’ve done before, while generalism helps you solve problems you’ve never seen before. Epstein notes that specialization works well for something like chess—chess players recognize game states and board positions, then instinctively utilize the appropriate counterplay.
However, in the mid-20th century, computers rendered many specialized procedural jobs obsolete. The qualities of tasks that make them suitable for specialization—repeated recognizable patterns, unchanging rules—also make them suitable for automation.
In the modern world, knowing how to perform specialized procedures isn’t enough to ensure job security. Epstein notes that modern problems aren’t like chess games—they’re one-of-a-kind, and you need to be able to draw on what you’ve learned in unrelated situations in order to solve them. As we’ll see later in this guide, these are skills developed through generalism.
The Knowledge Economy Requires Us to Solve New Problems
In his book Linchpin, author Seth Godin elaborates on Epstein’s argument that today’s knowledge economy requires us to solve new problems in order to thrive.
Since the Industrial Revolution, people have flocked to safe corporate jobs where they’re told exactly what to do because they provide a comfortable certainty. These jobs weren’t always fun, but they were low-risk. However, as technology has advanced and labor markets have developed, specialized jobs that simply consist of “following the rules” have become more and more scarce, driving down wages and killing job security. In Godin’s words, “There are no longer any great jobs where someone else tells you precisely what to do.”
Attaining a highly specialized skill seems like a safe bet. But you can earn far more by doing things no one has done before.
Godin asserts that in order to succeed in this new economy, you need to do things differently than anyone else. If all you do is fill your expected role, you’ll need to put in a massive amount of work to create even marginally more value than your peers. However, if you start executing on original ideas within your organization, you could deliver something worth hundreds or thousands of times more than someone else doing the same job. As he put it on an episode of The Tim Ferriss Show podcast, “We can’t out-obedience the competition.” Your most valuable contributions will be what your organization isn’t already asking for.
You’ve seen why the traditional path to excellence—early specialization—is misguided and outdated. Luckily, Epstein has outlined a new path to excellence—a formula to help us thrive in the modern world.
Instead of picking one skill and trying to stick with it for your whole life, Epstein suggests that you:
We’ll examine each of these life stages in turn.
Epstein asserts that the first step to mastery is an era of exploration and experimentation with different activities—a “sampling period,” as he calls it. Musicians, entrepreneurs, and athletes alike benefit from a period of early exploration, for a couple of reasons.
First, Epstein establishes the principle that broad learning teaches transferable skills. Basic training in a wide range of activities teaches a unique kind of skillset—one founded on instincts and principles that apply across disciplines rather than habits that apply in only one context.
A study conducted at a high-level music boarding school found that the highest-performing students didn’t practice more than others, took fewer formal lessons, didn’t start playing at a younger age, and didn’t even come from musical families. Instead, what set them apart was the number of instruments they knew how to play. The most exceptional students typically spread their practice time across three instruments.
(Shortform note: Science shows that there are limits to how far skills can transfer. Psychologists first distinguished between “near transfer” and “far transfer” of learning in 1923. You can use your experience with one musical instrument to help learn another, but it doesn’t make you better at math. The former is near transfer while the latter is far transfer. Experience can transfer proportionally to the number of similar elements shared by two activities—near transfer is a valuable learning tool, but far transfer has been largely debunked. Despite arguments to the contrary, teaching kids chess or piano doesn’t somehow make them smarter in school.)
Second, a period of exploration increases your chances of discovering a pursuit that’s a good fit for you—something that suits your inherent talents and that you’re excited about pursuing.
Extending this idea, Epstein suggests that parents should nurture exploration in their children, allowing them to discover their own likes and dislikes. Eager parents try to get their kids to skip the era of exploration by choosing lifelong pursuits for them as early as possible—often a particular musical instrument or sport. However, an externally-imposed specialization is far less likely to be a good fit than one you choose for yourself. A study of 1,200 musicians showed that kids who had their destinies chosen for them were far more likely to quit later down the road.
Exploring Employment: What Season Are You In?
Before you start putting in the work to become a master at something, you need to explore long enough to find out what’s motivating you. If you skip the exploratory period and begin specializing in something you’re not personally driven to pursue, you won’t care enough to push through the difficulties required to succeed. Finding a job that’s a good fit for you requires identifying what you want to get from that job.
Financial guru Ramit Sethi has organized the most common career motivations into three categories he calls “Career Seasons.” You’re in the season of “Growth” if you’re primarily motivated to jumpstart your career and rise as quickly as possible. You’re in “Lifestyle” if your primary goals lie outside your career, for example, spending more time with family. You’re in “Reinvention” if you feel unfulfilled on your current life path and want to start totally fresh on something new.
Sethi calls these stages “Career Seasons” because over the course of your lifetime, your priorities will change, and you’re likely to cycle through these stages more than once. It’s important to be conscientious of your shifting priorities. If you feel you’ve outgrown your current job, it may be time to go exploring again.
After an era of exploration in which they’ve built up a broad base of experience and found an activity that’s a good fit for them, generalists do engage in specialized practice, but they do so differently than traditional specialists.
Epstein argues that, unlike the rigorous drills practiced by specialists—for example, a piano player practicing her scales—we shouldn’t optimize learning for efficiency, as the most effective learning is slow and difficult.
Epstein cites a study observing undergraduate-level calculus classes at the Air Force Academy. Over the course of a decade, researchers studied the performance of more than ten thousand students and a hundred different professors, who all taught the exact same curriculum. Some professors emphasized broad, interdisciplinary understanding, while others emphasized the efficient mastery of specific procedures that would be on the test.
The latter group of professors, who prioritized efficient memorization, yielded students with higher test scores and earned more positive student evaluations than the professors who emphasized general knowledge. However, once the students advanced to Calculus II and more complex math classes, students of deep learning vastly outperformed their procedurally-minded peers. Lasting, useful knowledge takes time to learn.
This holds true even for narrow skills like playing a musical instrument. Epstein finds that many jazz legends taught themselves how to play, without formal lessons, through an excruciatingly inefficient process of trial and error. By teaching themselves, these musicians not only mastered their instruments forward and backward, they discovered the unique skill of effortless improvisation, developing a creative instinct that classically trained musicians could never match. The slow struggle of experimentation provides its own unique, lasting skills in any pursuit.
The Strengths and Weaknesses of “Overlearning”
Countering Epstein’s argument that efficient specialists miss out on the depth of inefficient practice, recent research has identified the benefits of “overlearning”: practicing a skill after you’ve already achieved proficiency. If specialists can continue to train their existing skills indefinitely, the efficient path to mastery doesn’t seem to miss much. However, research shows that overlearning in narrow specialized domains may limit these specialists in a different way.
In one study on overlearning, two groups of subjects were trained to identify subtle striped patterns embedded in static on a screen. One group was assigned to overlearn, practicing for twenty minutes after both groups had already learned to pick out the correct pattern. The next day, the overlearners were able to complete their task far better than those who didn’t overlearn. However, when asked to perform a new task—identifying a slightly different pattern in the static—the overlearners actually performed worse than the control group.
What does this tell us? The researchers concluded that the overlearners’ weakened performance was a side effect of their “resilient” experience with the first task. They had learned the first skill so well that they found it difficult to stray from the procedure. In other words, overlearning narrow skills hinders the application of those skills in new contexts.
When specialists attempt to learn adjacent skills, like classical musicians attempting to improvise or Air Force Academy students advancing to Calculus II, their overlearning of narrow procedures may do more harm than good.
Even after they’ve specialized enough to become a master in their field, generalists approach life differently than specialists. We live in a constantly changing world, and you need to be prepared to pivot—that is, to start chasing an entirely new specialization, if need be.
Often, we see pivoting as a sign of weakness, giving up on what we’ve promised to do—a deficiency of “grit.” Epstein disagrees, arguing that too much commitment can be just as harmful as not enough. He cites a Gallup survey showing that 85% of workers around the world are either “not engaged” at work or “actively disengaged.” This shows that many people are far too committed to the jobs they currently have and suffering for it.
Contrary to accepted wisdom, Epstein argues that it’s better to chase whatever opportunities you’re passionate about in the short term rather than committing to a single long-term goal or vision for your future. This is because people change, and it’s impossible for you to know how much you’ll change. A job that was a good fit for you ten years ago may not be anymore, and you’ll need to pivot. Additionally, it’s impossible to predict what opportunities will or won’t be available in the future, so planning your life out ahead of time and refusing to quit will unnecessarily limit your options.
The Pitfalls of Passion
In his book So Good They Can’t Ignore You, Cal Newport warns against making passion the primary guide of your career decisions. You shouldn’t be afraid to pivot if you’re stuck in a job you hate, but you shouldn’t expect your career to be transcendently fulfilling and refuse to specialize at all, either.
In Newport’s eyes, it’s alright to start a career in something you’re not passionate about. The idea that everyone has a single life purpose that they need to discover in order to be happy is a myth. In fact, studies have found that most people aren’t passionate about their dream jobs until after they’ve been working there for several years.
This is because the elements of motivation that get you excited to go to work in the morning are extremely different than most people expect. Psychologists have developed a framework called self-determination theory, identifying the primary contributors to motivation as autonomy, competence, and relatedness—that is, how much you feel you’re in control over your responsibilities, how skilled and capable you feel, and how connected you feel to those around you. None of these require a deeply emotional divine calling—you can acquire them as you work.
Epstein asserts that generalists are better at coming up with new ideas and solving problems in creative ways, making them far more valuable in the professional world than specialists.
Firstly, their diverse background experience makes it easier for them to think analogically—that is, using analogies to discover commonalities between dissimilar situations. For example, a start-up CEO struggling to decide whether to sell her rapidly growing company could inform her decision by studying 20th-century farmers who discovered massive wealths of oil underneath their land. Analogical thinking is effective because seemingly unrelated problems often have the same underlying structure, enabling similar solutions.
Secondly, generalists are better at lateral thinking, the use of pre-existing knowledge in a new context. Epstein writes extensively about cases in which outsiders with less expertise and less information about a given situation solve problems that have stumped teams of experts for years. They’re able to come up with ideas specialists never would because they’re drawing from a different background.
Lastly, the fact that creativity is all about bringing together ideas in new ways reveals the practical value of diversity in the workplace. Epstein notes that team members with diverse backgrounds bring together diverse ideas, making it more likely that they’ll come up with something new. For this reason, scientists who have worked abroad at some point in their lives, on average, make more impactful discoveries.
Creativity Requires Inefficiency
These three generalist strategies show that it’s impossible to efficiently specialize in creativity. Likewise, the management strategies that yield the most creative ideas are often the opposite of those required for efficient procedural work. Robert Sutton, author of Weird Ideas That Work, concludes that the most innovative organizations are “inefficient (and often annoying) places to work.”
Sutton offers another piece of counterintuitive advice: Managers of creative teams should reward employees for success and failure and only punish employees for inaction. Quantity, not quality, is the path to creative success.
Here’s another: Companies that want innovation should hire employees that often refuse to listen to bosses or coworkers. The Xerox employee who invented the laser printer was someone like this. He was working at a research and development lab, an organization whose sole purpose is innovation, yet when he suggested they look into the blossoming new potential of laser technology, he was dismissed by his coworkers and ordered to stop looking into it by his boss. Fortunately, he complained to someone higher up, got transferred to a new lab, and revolutionized the printing industry.
Range is a bold challenge to widely-held assumptions about success and human potential. Whether you want to become an Olympic sprinter, a neuroscientist, or a virtuoso musician, the traditional advice is the same: Start practicing as soon as you can and don’t stop until you’re the best in the world.
However, David Epstein argues that this narrow, highly specialized path is not as reliable as it’s been made out to be. Instead, broad competence in a wide range of skills is the best way to get ahead of the competition. Counter to what you’d expect, learning to do several things well makes you better at each one. Being a jack of all trades is often the way to become master of all.
In reality, very few world-class professionals attain success in the way you’d expect. Rarely have entrepreneurs, scientists, or even athletes trained from birth to do what they’re doing. In this book, Epstein makes the case that starting late or switching fields is nothing to be ashamed of. No matter where you are in life, you have as good a chance as anyone to become one of the greats—your unique history may even give you the upper hand.
David Epstein first gained public recognition as a senior writer for Sports Illustrated, investigating current events in the world of sports and frequently making use of his scientific background (an MS in environmental science).
After leaving Sports Illustrated, Epstein worked as an investigative journalist for the Pulitzer-winning online news source ProPublica, delivered TED Talks such as “Are athletes really getting faster, better, stronger?” that have collectively racked up more than 10 million views, and hosted a podcast called How To! for online magazine Slate.
Connect with David Epstein:
Publisher: Penguin Random House
Imprint: Riverhead Books
Range was published in 2019, becoming a New York Times bestseller. This is his second book, preceded in 2013 by the best-selling The Sports Gene, a deep dive into the various ways both genetics and life experience impact an athlete’s potential for success. Range is a broader application of many of the ideas in The Sports Gene (where Epstein first challenged the 10,000-hour rule) and is more directly argumentative.
Since Range’s publication, Epstein has started the Range Widely newsletter, intended to help readers “expand their range” and learn about interesting connections between seemingly unrelated fields.
Range’s thesis directly challenges many popular books on the subject of learning and human performance, especially those that emphasize “deliberate practice” such as Peak by Anders Ericsson and Outliers by Malcolm Gladwell. One chapter, “The Trouble with Too Much Grit,” is a direct critique of Grit by Angela Duckworth, which Epstein argues underestimates the value of quitting in some situations.
Additionally, Range is significantly influenced by previous books that have challenged the role that pure quantity of experience plays in human success, directly utilizing ideas from Make It Stick by Peter Brown, The Dip by Seth Godin, and Superforecasting by Philip Tetlock. Most of the knowledge in Range is aggregated from other sources rather than fully original, but Epstein weaves these ideas together into a single cohesive argument.
Range received glowing reviews from The New York Times, The Wall Street Journal, Forbes, and NPR. It was one of six books on the McKinsey and Financial Times shortlist for Business Book of the Year.
Critics praised Range for its convincing argument against commonly accepted wisdom, as well as the life-affirming conclusion of that argument. Critics and readers also appreciated Epstein’s engaging writing style. The true stories he uses in support of his thesis are consistently fascinating. Despite the fact that Range was intended to disprove the main idea of his book Outliers, Malcolm Gladwell has expressed admiration for Range and provides the blurb on the book’s front cover.
Critics of Range have claimed that Epstein is a little too optimistic about the average person’s chances to succeed without much deliberate practice. “Those who are richly endowed with talent may find it easy to excel in multiple domains,” writes the New York Times. “The rest of us, however, must lean heavily on the practice part of the equation.” They argue that Epstein could get away with downplaying talent or practice, but not necessarily both.
Additionally, some readers find Range’s one-note argument to become tedious when stretched across several chapters. They also criticize Epstein for lacking the evidence necessary to support his argument, saying he relies too heavily on anecdotes.
Range is an intentionally fluffy, accessible collection of scientific evidence in support of a thesis with strong mass appeal. Epstein strikes a tone between inspirational optimism and even-handed science-based realism. Some readers may feel that Epstein’s empowering argument leans too far toward wishful thinking, but his consistent return to statistics and concrete studies urges the reader to seriously consider his ideas.
Each chapter in Range tackles a single idea, beginning with an extended anecdote that lays the foundation for its argument. However, Epstein doesn’t explicitly connect each chapter to the others in any overarching structure, instead alluding to previously discussed concepts whenever the opportunity arises organically. The book tends to rely on narrow segues from one topic to another instead of zooming out to make the big picture easy to see.
We’ve split this guide into three parts. We’ve reorganized Epstein’s ideas to make it as easy as possible for you to apply them to your own life. The new outline is as follows:
In Part 1, we’ll lay the groundwork by exploring the specialist point of view in detail and explaining what specific features of today’s world make it much more favorable to generalists.
Part 2 is a chronological guide through the life of a generalist. We’ve broken up a few chapters and sorted their ideas into life stages to make it easier to pinpoint which ideas apply to your current situation in life and what you should be aiming to do next.
In Part 3, we’ll conclude by exploring the various advantages available to generalist professionals that narrow specialists lack.
Throughout the guide, we’ll provide additional relevant arguments from books that inspired Range, such as Seth Godin’s The Dip and Peter Brown’s Make It Stick. We’ll also take a closer look at the scientific studies that Epstein cites in the book and include intriguing relevant details that he chose to leave out.
David Epstein argues that in today’s modern world, generalism—a broad competence in many professional fields—is the key to living a fulfilling and productive life. However, for much of history, accepted wisdom has painted early specialization in one narrow skillset as the ideal way to get ahead.
This is still a common mindset today. We see parents hire violin teachers for kids who can barely walk, high schoolers expected to have the next decade or more of their lives planned by the time they graduate, and successful doctors who spend their entire lives studying a single gland in the human body. We view changing course, whether it be switching majors, switching jobs, or switching careers as wasting years of past experience.
According to Epstein, this school of thought couldn’t be more wrong. In Part 1 of this guide, we’ll show why the specialized path to excellence is no longer the wisest strategy.
First, we’ll define the commonly accepted traditional path to excellence. Next, we’ll show why this old path to excellence is increasingly obsolete in today’s world. Finally, we’ll take a look at the flaws of an education system that’s still built around the traditional path to excellence.
Malcolm Gladwell’s Traditional Path to Excellence
Recently, this traditional path to excellence was formalized and popularized by Malcolm Gladwell in his 2008 book Outliers. His famed “10,000-hour rule” states that the way to become a master in any field is to spend 10,000 hours practicing. Gladwell attributes the success of virtuosos such as Mozart, the Beatles, and Bill Gates not to inherent talent, but to the sheer volume of time they spent practicing.
The other key element of the traditional path to excellence is the specific kind of practice that best facilitates success, an idea Gladwell doesn’t cover in Outliers. Researchers often refer to this type of practice as “deliberate practice.”
The term “deliberate practice” was first defined by Anders Ericsson, a Swedish psychologist and expert on human expertise, whom Gladwell cites extensively in Outliers. Deliberate practice is a uniquely intense form of training intended to endow mastery in the most efficient way possible. It involves breaking down a skill into its component parts and rigorously repeating each part until it becomes effortless. Often, coaches or mentors provide guidance and feedback. You can read more about deliberate practice in our guide to Ericsson’s book Peak.
According to Epstein, the traditional path to excellence has been more or less treated as common sense for years. Obviously, if you want to get good at something, you have to practice a lot. By this logic, the path to success is to start deliberately practicing as early as possible.
If you believe in a purely linear relationship between practice time and success, specializing at a young age and never deviating from a given path would allow humans to accomplish never-before-seen levels of greatness. Extreme devotees of the 10,000-hour rule apply this logic to everything.
For example, Epstein describes Laszlo Polgar, who deliberately raised three of his daughters to be world-class chess masters and proclaimed to the world that if more children were brought up deliberately practicing from birth, they could become skilled enough to easily cure diseases like cancer and AIDS. In Bounce, Matthew Syed attributes the failure of the British government to the fact that its officials rotate from department to department without the opportunity to specialize.
Even if you don’t believe quite this deeply in the role of deliberate practice, it’s likely that you’re giving it more credit than it deserves.
Nature Versus Nurture
Epstein isn’t the first person to critique the traditional path to excellence championed by Polgar and Syed. Studies have shown that genetics still play a significant role in skill acquisition. Experiments testing twins on fundamental musical skills showed that some skills, such as the instinct to match melodies with the same rhythm, are entirely gene-dependent—discrepancies in hours spent practicing had no impact. A broader study found that identical twins are far more likely to have similar levels of drawing ability than fraternal twins.
However, a disproportionate reliance on genetic contributions to success has its own problems. If you become convinced that your ineffective genes prevent you from succeeding, you’ll give up before you’ve even begun. Studies have confirmed that high self-esteem leads to increased initiative, as well as greater ability to set and achieve goals. In this way, unrealistic beliefs like Laszlo Polgar’s faith that scientific prowess can be taught from birth can be beneficial, even if (as we’ll see later) they’re not true.
Epstein argues that specialization is a far less reliable life strategy than we would expect, especially in recent years. This is true for a number of reasons.
The main reason specialization isn’t ideal is that the world is far more unpredictable than we’d like to believe. Epstein distinguishes between “kind” and “wicked domains”—what we’ll call Stable and Unstable Environments.
Stable Environments are settings in which the ways to achieve success are easily understood and unchanging. Games with clearly defined rules such as basketball or billiards are Stable Environments, as are simple procedural jobs, like installing circuit boards on an assembly line. Unstable Environments are settings in which the ways to achieve success are unclear and constantly changing. Almost every environment in the “real world” is unstable to a certain degree.
Experience in Stable Environments will provide you with permanent value. For this reason, Epstein argues that specialization and deliberate practice are the most valuable in Stable Environments. Practicing your free throw a hundred times a day will make you better at basketball because the rules aren’t going to change.
Epstein warns that experience in Unstable Environments, on the other hand, may be worthless—or worse, it may harm your future performance. Dating, for instance, is an example of an Unstable Environment. Failed relationships often teach lessons that are inaccurate and/or unhelpful—someone who gets cheated on may come to the conclusion that no one will ever love them, when in reality they just weren’t with the right person. The rules of the environment are hidden and ill-defined, and as a result, experience doesn’t always result in improvement.
The Ludic Fallacy
Coined by author Nassim Nicholas Taleb in his book The Black Swan, the “Ludic Fallacy” refers to the misapplication of Stable Environment rules to an Unstable Environment. The word “Ludic” comes from the Latin word ludus, meaning “game,” as people falsely assume that the same strategies used to calculate probability within a game can be used in the real world.
For example, Taleb explains that casinos calculate their real-world risk using the same strategies they use to calculate risk within a game like blackjack. They spend millions of dollars on high-tech security systems designed to prevent people from cheating, which, according to their calculations, profitably mitigates their risk.
However, in the Unstable Environment of the real world, the largest losses never come from the places you’d expect, making the goal of accurately calculating risk impossible. Taleb visited a casino that lost $100 million dollars after one of its entertainers was mauled by his own tiger, had to pay a gargantuan fine to the IRS after an otherwise reliable employee forgot to send in certain tax forms for years, and had to pay the ransom for the kidnapping of the casino owner’s daughter. These losses cost 1,000 times more than the cheating losses predicted by their risk analysts. Statistical models like the one the casino used to calculate risk fail in Unstable Environments.
Specialists’ path to success fails in much the same way—they fail to realize that their narrow, inflexible plans keep them from taking advantage of the unpredictable, as we’ll see in Part 2 of this guide.
Epstein argues that, because they assume that the world is a largely Stable Environment, followers of the traditional path to excellence strive for efficiency above all else. Specialists see skills and knowledge as a simple commodity—the more you practice, the more you “collect.” As a result, they assume that to reach the top of your field, all you need to do is accumulate skill as quickly as possible.
Generalists, on the other hand, recognize that we live in an unstable world—it’s impossible to perfectly predict what experience will be valuable to you. As we’ll see throughout this guide, experience that feels like a waste of time often pays off in ways you could never have imagined. Additionally, some inefficiency is necessary to perform at a world-class level. This leads us to one of Range’s main ideas—efficiency is a bad metric with which to judge your life. We’ll explore this in great detail in Part 2 of this guide.
Stop Trying So Hard
Optimizing your life around efficiency is not just ineffective—it can take a toll on your life satisfaction. On an episode of The Tim Ferriss Show podcast, entrepreneur Derek Sivers recounts the story of how he learned to be happier by not trying as hard.
When he lived in Los Angeles, Sivers would bike down a long beachside path every day, pushing himself non-stop until he made it back home. Every day, he challenged himself to beat his record, as if he were training for a race, but he eventually got stuck at 43 minutes. He began to dread going on his daily bike ride, so one day he decided to take it easy and enjoy the sights and sounds of the beachside path. When he got home, he was dumbstruck to discover that the relaxed trip only took him 45 minutes. What had felt like Olympic-level training only shaved two minutes off his time.
The moral Sivers gleaned from this experience was this: Trying to squeeze the most out of every possible second of your life often causes more stress than benefits. It’s possible to accomplish great things without making yourself miserable in the process.
Epstein argues that specialization is becoming more obsolete as time goes on. To help explain why, he distinguishes between two modes of decision-making: tactics and strategy.
Tactics are instinctual procedural responses to certain repeated patterns. You recognize a situation and immediately know what to do in response. For example, Epstein notes that chess experts primarily use tactics. They recognize game states and board positions, then utilize the appropriate memorized counterplay. Tactics are all about instinctively doing things you’ve practiced before.
Strategy, on the other hand, is all about broad, abstract understanding. By combining past experience with higher-level reasoning, humans can make effective decisions in situations they’ve never experienced before. For example, Netflix employed the unorthodox strategy of operating at a loss for about a decade, borrowing over sixteen billion dollars since 2011 to keep the lights on. This strategy is based on the idea that original content is a far more sustainable investment than licensing rights.
Epstein asserts that, generally, specialization teaches tactics while generalism teaches strategy. And in the modern world, strategy (abstract decision-making) is what matters.
The Value of Subconscious Tactics
This isn’t to say instinctive tactics are useless in modern times—in fact, we use tactics far more than we realize. In his book Skin in the Game, author Nassim Nicholas Taleb criticizes the “rationalist” school of thought for over-attributing human behavior to innate complex strategy instead of recognizing simpler tactics. For example, he quotes “rationalist” and evolutionary biologist Richard Dawkins (The Selfish Gene), who argued that, at some subconscious level, the brain of a baseball player trying to catch a pop fly is calculating incredibly complex differential equations in order to determine where to stand. In reality, however, the baseball player has subconsciously picked up on a much simpler tactic—fix your gaze on the flying ball, and run toward it at a speed that keeps the ball steady in your field of vision.
Taleb uses this example to make the point that we vastly overestimate the potential of human strategy. While Epstein focuses on the creative potential of human strategy, Taleb focuses on its fallibility. In contrast, even though tactics can only function in narrow situations, they’re incredibly reliable in those situations. Walking, driving, and biking all involve sets of internalized tactics, and for the most part, we do those tasks extremely well.
In the distant past, there was no use for abstract strategic thinking. Epstein cites the work of psychologist Alexander Luria, who studied isolated villages in modern-day Uzbekistan and Kyrgyzstan that were entirely untouched by industry of any kind.
The villagers in these communities were entirely unable to think in abstractions or classification. When asked to name colors, they used concrete descriptions such as “cotton in bloom,” or “decayed teeth.” When shown a picture of three adults and a child and asked which one did not belong, one villager insisted that they all must stay together—it was the boy’s job to fetch things for the working adults.
The premodern villagers had no need to learn strategy because they thrived by learning tactics: Growing food and cotton requires repeated procedures in predictable situations.
Today, however, strategy is what helps us succeed. Epstein describes the Flynn effect, the phenomenon that global IQ scores are rising over several generations, requiring tests to be constantly re-standardized to a new level of average intelligence.
The Flynn effect shows that as the world becomes more and more modernized, our brains are adapting to a greater demand for the ability to think conceptually and identify abstract patterns.
Epstein argues that just as the premodern villagers’ brains adapted to think concretely in order to succeed, this notable adaptation in our brains reflects how the world is changing. Our increasingly conceptual way of thinking is a result of widespread scientific classification—for example, the labeling and organization of every part of the body—as well as the economic rewards promised to professionals who can conceptualize strategically, such as entrepreneurs and scientists.
Epstein asserts that the ability to think strategically is humans’ greatest strength. While tactics can certainly be valuable, they can also more easily become obsolete.
The Plastic Brain
The brain’s ability to rewire itself in response to our environment is called “neuroplasticity,” and it explains why Luria’s villagers thought in an entirely different way than city folk. Neuroplasticity research took off in the late 1970s, when researchers first detected microscopic changes in the brain’s wiring caused purely by external experience.
As demonstrated by Luria’s villagers, the guiding principle behind neuroplasticity is “use it or lose it.” When the brain is repeatedly directed toward a specific task, new synapses form and neurons shift function in order to make that task easier in the future. If parts of the brain remain unused, they will wither or shift in function. For this reason, neuroplasticity has changed the way we treat stroke victims—instead of allowing them several weeks of “rest,” allowing time for unused neurons to die, stroke victims are given incremental training as soon as possible, in order for the brain to repair the parts that were destroyed.
Neuroplasticity allows the brain to do things we would never expect. Dementia is a purely genetic disease, so it’s easy to assume that there’s nothing we can do about it. You can’t change your genes, after all. But recent research into neuroplasticity has found that certain behaviors can strengthen the parts of the brain that dementia would attack, reducing the risk of getting dementia by up to 60%. Specifically, regular vigorous exercise has been shown to be the best tool for fighting dementia.
Perhaps the most shocking example of the incredible power of neuroplasticity: Children are able to survive hemispherectomies in which half of their brains are removed, as the remaining hemisphere adapts to perform the functions of one full brain.
Epstein argues that as industry and technology have advanced, specialization has only become less valuable.
For much of the 20th century, specialization was handsomely rewarded. Employees stayed with the same companies for decades. Loyalty to the company meant the prospect of promotion, and pension plans for long-term employees were common.
However, computers rendered many specialized procedural jobs obsolete. Epstein points out that the qualities of tasks that make them suitable for specialization—repeated recognizable patterns, unchanging rules—also make them suitable for automation.
Today, we’ve entered the era of the “knowledge economy,” where the ability to innovate and generate good ideas has grown to define success.
The advent of artificial intelligence and machine learning has only intensified automation’s threat to specialized workers. For example, IBM has recently developed a chatbot called Watson Assistant that could make call-in customer service representatives obsolete. Similarly, the Internet has increased the ease with which we can access knowledge, further devaluing in-house specialists. A significant amount of expert knowledge is now online.
How to Be a Linchpin in the Knowledge Economy
In his book Linchpin, author Seth Godin elaborates on Epstein’s argument that today’s knowledge economy requires us to become one-of-a-kind commodities in order to thrive.
Since the Industrial Revolution, people have flocked to safe corporate jobs where they’re told exactly what to do because they provide a comfortable certainty. These jobs weren’t always fun, but they were low-risk. However, as technology has advanced and labor markets have developed, jobs that simply consist of “following the rules” have become more and more scarce, driving down wages and killing job security. In Godin’s words, “There are no longer any great jobs where someone else tells you precisely what to do.”
Attaining a highly specialized skill seems like a safe bet. But if you bind yourself to a single specialized path, you’ll never stand out from others who do the same.
Godin asserts that in order to succeed in this new economy, you need to do things differently than anyone else. If all you do is fill your expected role, you’ll need to put in a massive amount of work to create even marginally more value than your peers. However, if you start executing on original ideas within your organization, you could deliver something worth hundreds or thousands of times more than someone else doing the same job. As he put it on an episode of The Tim Ferriss Show podcast, “We can’t out-obedience the competition.” Your most valuable contributions will be what your organization isn’t already asking for.
Unfortunately, despite the fact that specialization is becoming increasingly obsolete, our education system is more specialized than ever. Our modern education system fails to teach the most valuable skills—those required for critical thinking and problem solving. Epstein cites a study showing that, among college seniors, GPA has nearly zero correlation with critical thinking skills.
Specialization is rampant, especially in higher education. College students are taught how to successfully think within the bounds of one academic discipline, but it’s been shown that they struggle to apply similar ideas to new contexts. In Epstein’s eyes, they rely too heavily on tactics and not enough on strategy. In a world where three out of four undergraduates advance to a career unrelated to their major, narrow training in a single discipline is not good enough.
Hyper-specialized higher education also results in scientific professionals that are far too specialized. Some still lack these basic critical thinking skills. Epstein recounts an example: When physicians and med students at a Boston-area hospital were given a simple, albeit counterintuitive problem involving calculating the probability of a patient having a certain disease, only about one in four got it right.
In the study, “Medicine’s Uncomfortable Relationship With Math,” subjects were told that there’s a false positive rate of 5% for a test for a disease that affects 1 in 1000 people. If someone tests positive, what’s the likelihood that person has the disease? 27 of the 61 respondents said “95%,” and only 14 gave the correct answer of around 2%.
Why the Doctors Got It Wrong
These results are baffling when you consider that these were medical professionals with degrees from Harvard and Boston University, who theoretically are dealing with problems like this every day. Attending physicians performed no better than the med students.
Arguably, this mistake is rooted in an extremely common problem: Most people avoid thinking in base rates—the probability of something being true in the absence of any case-specific evidence. The medical staff being tested neglected to calculate that, out of 1,000 people, 50 will get false positives, while only one will actually have the disease.
This tendency to avoid dealing in base rates contributes to a number of mental biases, as detailed in psychologist Daniel Kahneman’s Thinking, Fast and Slow. Consider this question: Julie read fluently when she was four years old. What do you estimate her college GPA will be? We assume that a relatively smart child will be a relatively smart adult, so she’ll probably have a GPA of 3.7 or 3.8. The more accurate way to estimate this fact, however, is to begin with base rates: The average college student’s GPA is 3.1, so you would need much stronger evidence to assume that Julie has a GPA of 3.8.
Epstein cites esteemed microbiologist Arturo Casadevall, who argues that scientific progress is slowing as more students are pushed through higher education without having first learned to think critically. The number of retractions in scientific literature is increasing, indicating a growing inability to spot flawed research. Even though biomedical research funding has skyrocketed over the last 35 years, new discoveries have slowed.
But what would an education that emphasizes critical thinking look like? For a start, Epstein endorses Casadevall’s call for fewer required classes and greater opportunities for students to learn outside of their field.
Epstein cites a computer science professor who argues that the “computational thinking” required to code should be a part of the gen ed curriculum, as it’s a problem-solving framework that involves breaking down complex problems into solvable components.
To give another example of how critical thinking could be taught in schools, Epstein describes a valuable skill he learned in college: how to solve “Fermi problems.” Fermi problems are puzzles intended to test your estimation skills—for example, what is the mass of all automobiles scrapped in North America this month? You’re supposed to break down this problem into a series of rational assumptions. Roughly, how many people in North America own cars? How often does a car need to be scrapped? How heavy is the average car? Epstein argues that this process allows you to roughly know what statistics are reasonable and what aren’t, no matter what discipline you’re in.
Measuring Critical Thinking in Schools
The Collegiate Learning Assessment (CLA+), one of the most popular tests of critical thinking in higher education, provides us with insight as to which of these recommendations would be the most successful. The 90-minute exam tests students from around 200 schools across the United States, ranking them and comparing freshmen to seniors to determine how much students learn at each school. It requires students to analyze real-life research data and synthesize logical arguments based on a given set of evidence.
The institution boasting the biggest improvement in critical thinking is Plymouth State University, a liberal arts school in Plymouth, New Hampshire. PSU faculty attribute this prestigious score to their focus on concrete problem solving across their majors. Students in a technical writing class, for example, were asked to design a new course on resumés and covers. They ended up conducting interviews with professors and students before condensing their research into a proposal. Students in a philosophy of law class were asked to conduct a mock trial of Lizzie Borden, an alleged ax murderer from 1892. This kind of problem lacks fixed instructions or a single definitive answer, and as such, more closely resembles problems in the real world.
Big-name schools that scored low on the CLA+, including the University of Kentucky and the University of Texas at Austin, blamed the test itself and stopped using it. Seniors at those schools performed about as well as freshmen—and at UT Austin, they did slightly worse. To many, the lackluster value of large universities like this is not a surprise—43% of the general public no longer believes that a college education is a “good investment,” and one-third of millennials regret going to college themselves. Just as Epstein argues, many college graduates are suffering from a lack of emphasis on critical thinking.
By now, you’ve seen why the traditional path to excellence—early specialization—is misguided and outdated. Luckily, Epstein has outlined a new path to excellence—a formula to help us thrive in the modern world. He argues that this generalist approach is effective even for narrow domains in which hyperspecialization seems necessary, such as sports or music.
Instead of picking one skill and trying to stick with it for your whole life, Epstein suggests that you:
In Part 2 of this guide, we’ll examine each of these life stages in turn.
Epstein asserts that the first step to mastery is an era of exploration and experimentation with different activities—a “sampling period,” as he calls it. Musicians, entrepreneurs, and athletes alike benefit from a period of early exploration.
This exploration provides you with two valuable benefits: It gives you a broad range of experience and ensures that you’re a good fit for the activity you decide to pursue.
Epstein establishes the principle that broad learning teaches transferable skills. Basic training in a wide range of activities teaches a unique kind of skillset—one founded on instincts and principles that apply across disciplines rather than habits that apply in only one context.
A period of broad exploration provides robust expertise that is transferable to unfamiliar situations. In some cases, it even leads to greater skill than someone who narrowly specialized. To prove this, Epstein dives into the world of professional musicians.
One of the greatest groups of musicians in history was the figlie del coro, a classical ensemble in 17th-century Venice comprised entirely of orphaned girls. The figlie performed for royalty, had pieces composed specifically for them by greats such as Vivaldi and Haydn, and were widely regarded as the finest musicians in the world. The figlie’s success wasn’t due to extreme amounts of deliberate practice.
Epstein recounts that the girls only had formal lessons three days a week, although they were allowed to practice in their spare time—which wasn’t much. The orphanage eventually devoted more time to music practice after the figlie became famous, but at first, the orphans were only allowed to practice for an hour a day, in between schoolwork and chores.
According to Epstein, what made the figlie’s training uniquely successful was the number of different instruments they were required to learn. The girls were encouraged to learn every instrument the orphanage owned, and many achieved virtuoso-level skill on multiple instruments.
This same phenomenon has been studied among modern-day musicians. A study conducted at a high-level music boarding school found that the highest-performing students didn’t practice more than others, took fewer formal lessons, didn’t start playing at a younger age, and didn’t even come from musical families. Instead, what set them apart was the number of instruments they knew how to play. The most exceptional students typically spread their practice time across three instruments.
The Limits of Transferable Learning
While there is evidence in favor of broad learning across musical instruments, it’s important to note that there are limits to how “broad” transferable learning can be.
Back in 1923, psychologists distinguished between “near transfer” and “far transfer” of learning, based on the principle that experience can transfer proportionally to the number of similar elements shared by two activities. For example, you can use your knowledge of how to drive a car to learn how to drive a bus—near transfer. Similarly, Epstein asserts that near transfer allowed the figlie to transfer their musical skills across surprisingly dissimilar instruments, for instance, from singing to the violin. The two skills have enough in common for near transfer to function. Far Transfer, on the other hand, would be like transferring your chess experience to better learn mathematics, and it’s been largely debunked.
In the 19th century, Latin was a core component of an American schoolchild’s education because it was assumed that learning Latin would make children “smarter” overall. Many people still hold the belief that learning something like chess or piano will somehow enrich your overall cognitive faculties, and some studies have confirmed this assumption.
However, in 2016, a couple of researchers conducted a meta-analysis of these studies and found that many of them fell prey to a common fallacy—they mistook correlation for causation. Successful students enjoy playing music or chess because they’re stimulating activities; it doesn't necessarily make them smarter. When these studies were adjusted under more narrow conditions, the correlation all but disappeared.
Still, as we’ll see in the rest of this guide, there are plenty of reasons to practice generalism, even if most of your specific skills don’t transfer from one discipline to another.
Epstein suggests that broad learners create “abstract models” based on the commonalities across activities, internalizing skills that apply in multiple contexts. Narrow specialists, on the other hand, merely learn to repeat what they’ve already seen done.
For example, children learn to talk by hearing the rules of grammar implicitly applied in a broad variety of contexts. They don’t learn by repeatedly practicing selected sentences over and over, like formal music students do in deliberate practice. In the same way, musicians that learn multiple instruments discover a greater understanding of music that applies in all contexts.
Does Knowing Two Languages Help You Learn a Third?
Recent science shows that, just as it’s easier to learn a third musical instrument after you’ve played two, it’s easier to learn a third language if you’re already bilingual.
A study from Israel compared two groups of sixth-graders—one group of immigrants from the former Soviet Union that spoke both fluent Russian and Hebrew, and one group of natives who only spoke Hebrew. Interestingly, the kids who spoke Russian were not only better at learning English, they were more proficient in Hebrew than the native speakers who only spoke Hebrew.
Additionally, if you learned your second language later in life, you gain the additional advantage of discovering which language-learning strategies best work for you, whether that be a focus on reading and writing, conversing with native speakers, or even watching foreign movies.
Epstein emphasizes the importance of what psychologists call “match quality”—whether an activity is a good fit for an individual or not. An activity that’s a good fit for you is one that suits your inherent talents, and more importantly, it’s something you’re excited about pursuing.
Epstein argues that taking time to explore your options is worth it to discover a life direction that suits you. To demonstrate this, he cites a study that compared match quality between education systems in Great Britain. At the time, students in England and Wales were required to pick a specialty before they went to college, while Scotland required its students to explore multiple fields throughout the first two years of college. How did the two groups compare?
English and Welsh students were far more likely to switch career fields than Scots, since they weren’t given the chance to find a good fit earlier in their education. This shows that they were significantly dissatisfied with the careers they picked in high school—enough to sacrifice the years of specialized knowledge they had accumulated. Finding a good fit was more valuable to them than the money and success they could earn with specialized skills. Early exploration allows us to discover activities that are more likely to make us happy.
Attempts at Broad Learning Outside of Scotland’s Universities
Scotland’s emphasis on broad learning isn’t restricted to its universities. Since 2010, students in Scotland aged 3 to 18 have been taught according to the “Curriculum for Excellence,” notable for the freedom given for individual schools to design their own curriculums and its minimal standardized testing. These changes were intended to put greater emphasis on critical thinking rather than test-oriented narrow memorization.
However, a 2021 OECD report declared the current implementation of this curriculum a failure, prompting another wave of reform. The main problem, according to the report, is the lack of effective administrative oversight. As we discussed earlier, it’s difficult to standardize an education in non-disciplinary thinking. Simply providing students the freedom to stumble upon subjects with high match quality isn’t enough.
Extending this idea, Epstein suggests that parents should nurture exploration in their children, allowing them to discover what’s a good fit for themselves. Eager parents try to get their kids to skip the era of exploration by choosing lifelong pursuits for them as early as possible—often a particular musical instrument or sport.
However, an externally-imposed specialization is far less likely to be a good fit than one you choose for yourself. A study of 1,200 musicians showed that kids who had their destinies chosen for them were far more likely to quit later down the road.
Speaking more broadly, the fewer limitations put on children, the better. Epstein cites a study showing that children who grow up to be extremely creative have fewer rules imposed on them at home than average. In these families, parents are more likely to allow their children to make their own decisions and offer judgment after the fact.
Balancing Exploration With Discipline in Parenting
One of the rules in psychologist Jordan Peterson’s 12 Rules for Life advises parents to set strong boundaries for their children and discipline them as necessary to get them to live within those boundaries. In his words, “Do not let your children do anything that makes you dislike them.” His argument is that if a child’s parents don’t teach them to behave within the rules of society, the cold, unforgiving world will eventually cause them far more suffering than early discipline would have. For example, the other kids at school won’t want to be friends with someone who knows nothing about mutual respect.
However, Peterson agrees with Epstein that parents shouldn’t set any more rules than they need to. He argues that if disciplinarian parents set too many unnecessary rules, children won’t respect the rules that matter. They shouldn’t prescribe a specific path like violin lessons for their children if they don’t want to take them. Instead, parents should limit themselves to being “proxies for society.” The only necessary restrictions are those which allow children to avoid being rejected by society—which, counterintuitively, allows them to more freely explore the world and develop competence in a good fit of their choice.
Epstein has shown us the benefits of exploration, but we’re left with the question: What to explore? An exercise answering this question called the “List of 100 Dreams” has become popular in recent years. The goal is to identify fulfilling new experiences to fill your free time instead of spending it on cheap leisure like TV by default.
List as many “dreams” as you can think of. Anything that you’re curious about experiencing in life should make the list. They can be big, like “write a book” or small, like “sleep outside.” Try to get to 25, no matter how bad some of your ideas are.
What item on your list excites you the most? Did you come up with anything that surprised you?
Now that you’re inspired, how much time per week do you want to devote to exploration? What priorities can you shift to allow this to happen?
After an era of exploration in which they’ve built up a broad base of experience and found an activity that’s a good fit for them, generalists do engage in specialized practice, but they do so a little differently than traditional specialists.
On average, generalists have slow “inefficient” starts, but end up outpacing specialists in the long run. This comes down to the way they learn, which is more complex than the typical idea of deliberate practice. Epstein argues that we shouldn’t optimize learning for efficiency—the most effective learning is slow and difficult.
Specialists assume that all you need to master piano scales or trigonometric formulas is the discipline to work as many hours as it takes. But spending a massive number of hours studying isn’t going to cut it, as not all hours spent learning are created equal.
(Shortform note: This part of Epstein’s argument overlaps with general consensus. Several of the most popular books on learning, including Anders Ericsson’s Peak, Ultralearning by Scott Young, and Make It Stick by Peter C. Brown, emphasize the fact that how you learn matters far more than how much time you spend learning.)
We’re going to take a look at several forms of slow, difficult learning that hinder short-term retention but pay off years down the line. First, we’re going to distinguish between two categories of educational content—How Questions and Why Questions—and explain why the more challenging of the two is more valuable. Then, we’ll take a look at a few brain tricks that make it easier to retain information that’s difficult to learn. Finally, we’ll learn about an unusually difficult method of skill acquisition that enables new heights of mastery.
Epstein distinguishes between two types of problems given to students in educational settings—what psychologists have termed “using procedures” questions and “making connections” questions. We can more simply describe them as “How” questions and “Why” questions.
For How Questions, students are asked to carry out specific instructions—for example, reducing a fraction to its simplest form—while for Why Questions, students are asked to analyze a situation and determine for themselves what procedures they need to use—for example, calculating how much money to tip at a restaurant.
Epstein notes that to solve How Questions, students just need to memorize how to do something—tactics which are best learned through repeated practice. To solve Why Questions, however, students need to understand why specific procedures are helpful in a broader context that more closely approximates the real world—they need strategies that require generalist understanding.
Both types of questions are necessary for effective learning. You need to know the rules of basic math in order to calculate a tip at a restaurant. However, because they’re slow and difficult, Why Questions are drastically underrepresented in most schools, leaving students unable to use what they’re learning in real life.
Epstein bases his argument on a study that filmed and analyzed hundreds of elementary school math classes from a wide range of countries around the world. He emphasizes one recurring mistake made in many countries. Even though Why Questions were included in the curriculum to force students to think conceptually, teachers who were unable to quickly or easily teach students these difficult concepts would instead give hints until Why Questions were stripped down into How Questions. Students would guess at which procedure to use until they got it right, and the teacher would move on without ever establishing a deeper level of understanding.
For example, imagine if a teacher asked the students to write a mathematical expression to describe the area of one slice of a pizza divided into fourths. The teacher tells the class to use “a” to represent the pizza’s area, hinting to the class that they need to use “a” somehow. The students guess “4/a” and “4a” before landing on the correct answer of “a/4” without ever considering why.
In the United States, around one out of every five math problems began as a Why Question, but by the time the class solved it, zero percent of them remained Why Questions.
Japan, on the other hand, was the most successful country at teaching Why Questions. Epstein recounts how students in Japanese classrooms sometimes spent entire periods solving a single problem, trying out different conceptual strategies and learning why procedures worked the way they did. Japan’s schools were successful because they embraced the need for education to be slow and difficult.
Education Around the World
As Epstein’s study shows, education differs widely in countries around the world. As Epstein describes, a Japanese child’s education is uniquely rigorous from the very beginning. Kindergarteners have to study in order to pass elementary school entrance exams and often attend after-school tutoring to ace them. University entrance exams are life-and-death in such a work-obsessed industrial culture, and many high school students spend late nights at “cram schools.” 44% of these high schoolers fail their first attempt at university exams and become ronin, “samurai without a master,” studying on their own for a year before trying again.
This rigorous education system has been a mixed bag for Japan. After World War II, Japan implemented its highly competitive mandatory testing to prepare its students for the workforce, skyrocketing the nation to become the second-largest economy in the world. However, Japanese growth ground to a halt in the 90s, provoking reform in Japanese schools, including a reduction in Saturday classes.
Some attribute Japanese stagnation to the school system’s de-emphasis of valuable creative and critical thinking skills in favor of specialized exam prep. Others argue that the work-obsessed culture has pushed the Japanese people to their limits, leading to unproductive and unfulfilling social isolation. Still, they consistently rank among the top nations of the world in reading literacy, math, and science.
On the opposite end of the spectrum, Finland imposes far less academic rigor on its youngest students, yet they too rank among the highest scorers worldwide. For every hour of class, students get a fifteen-minute recess to play outside. They don’t start formally learning math or reading and writing until they’re seven years old. Instead, young children focus on developing social skills and “play-based learning”—teachers direct their students’ play with the deliberate intent of cultivating focus and problem-solving. For example, one assignment given to a class of first-graders was to go outside, collect fifty rocks and acorns, and organize them in groups of ten. Most importantly, Finnish teachers try to give students the “joy of learning” and help them learn to motivate themselves.
Classes are small enough for teachers to form deep connections with their students. When a student falls behind, teachers consult one another to come up with the best way to catch them up. Nearly 30% of students in Finland receive some kind of individual help in grade school. The Finnish mandate just one standardized test to high school seniors, and don’t ascribe much value to it. They don’t assign much homework, either. It’s a counterintuitive success story that shows there’s more than one way to teach deep understanding.
This problem doesn’t just exist at the elementary level. Epstein cites a study that observed undergraduate-level calculus classes at the Air Force Academy. Over the course of a decade, researchers studied the performance of more than ten thousand students and a hundred different professors, who all taught the exact same curriculum.
Some professors posed more Why Questions and emphasized broad, interdisciplinary understanding, while others emphasized efficient mastery of specific procedures that would be on the test. At first, it looked like the deep learning prompted by Why Questions was unnecessary. The professors who didn’t bother to teach Why Questions yielded students with higher test scores and earned more positive student evaluations than the professors who emphasized general knowledge.
However, once the students advanced to Calculus II and more complex math classes, students of deep learning vastly outperformed their procedurally-minded peers. Epstein uses this to argue that Why Questions requiring deeper understanding result in more robust, practical knowledge over the long term, but far too often, they’re downplayed in the name of specialized efficiency.
Educational Peers at the Air Force Academy
Difference in teaching styles isn’t the only significant factor influencing students’ performance at the Air Force Academy. One study found a strong correlation between a freshman’s GPA and the average SAT scores of the other members in their squadron, indicating that spending time with studious peers has a significant influence on academic performance.
However, when some squadrons were specifically assembled to match together low performers and high performers, the low performers actually performed worse than low performers in fully random squadrons. Researchers concluded that the gulf between the high and low performers was so great that the two groups didn’t want to mix, resulting in separate cliques within a single squadron. This indicates that attempts to “inspire” low performers in schools by manipulating their peer groups could easily backfire.
Epstein describes several other slow, difficult learning methods that stick. The “generation effect” refers to the well-documented psychological phenomenon that someone struggling to come up with the answer to a question will retain more knowledge for a longer time when the answer is revealed, even if they completely failed at coming up with an answer. The generation effect attests to the effectiveness of unpleasant, difficult learning methods, such as frequent testing without the benefit of multiple choice.
The “spacing effect” is a similar phenomenon—people retain more knowledge if there are lengthy gaps between study sessions on the same information. In the long run, someone who studies the facts about a historical battle will retain more information if they’re tested in a month than if they have to take the test on the same day. The more time that’s passed since you reviewed the information, the harder it is to recall—which is exactly the point. It’s the struggle of a difficult test that makes the information easier to remember for years to come.
(Shortform note: Because of the spacing effect, the best way to learn anything is to create a long-term review schedule. The review sessions don’t have to be long—30 minutes is plenty—but they should be spaced out over a long period of time. Use longer intervals as you get better at retaining the information in order to keep recall difficult, and eventually you’ll remember it indefinitely.)
Epstein’s last technique for effective learning is called “interleaving.” Interleaving is when multiple kinds of problems are mixed together in review—for example, a cumulative math test in which consecutive problems are drawn from different chapters of the book. Interleaving works because it requires learners to analyze each problem before determining how to solve it, which engages their abstract strategic mindset. This is more difficult than if all the problems of one type are “blocked” together, but it vastly improves retention.
(Shortform note: Because interleaving is meant to train the specific skill of distinguishing between similar kinds of problems, you shouldn’t weave together types of practice that are completely unrelated. Flipping between Spanish, math, and history homework, for example, wouldn’t provide the benefits of interleaving.)
How People Learn Incorrectly
These difficult learning strategies are all discussed at length in Peter C. Brown’s Make It Stick. Interestingly, like Range, Make It Stick contradicts the accepted wisdom surrounding deliberate practice by specifically condemning the use of immediate feedback. While immediate feedback makes the learning experience more enjoyable, Brown argues that it acts like “training wheels,” hindering learning by never allowing the learner to struggle in the absence of the right answer. Instead, feedback should be delayed in order to make use of the generation effect and keep the learning difficult enough to stick.
After covering the learning methods cited by Epstein, Brown argues that one of the biggest mistakes learners make is misperceiving their own level of competence. There are many factors at play that make it difficult to accurately estimate your own knowledge. For example, the fluency illusion is when we assume that because learning feels easy, we know far more than we actually do. For example, if you smoothly grasp all the ideas of a TED Talk on organic chemistry, you could falsely estimate that you have at least an undergraduate level of chemistry knowledge—unaware of all the complex ideas the presenter left out.
To accurately gauge your proficiency, Brown suggests that you test yourself on how easily you can recall information after an extended period of time and rephrase the learned concepts in your own words. Frequently interacting with peers and teachers can also ensure that you have a realistic idea of your own knowledge.
When it comes to skill acquisition, Epstein makes the case that slow, directionless exploration provides more robust skill than the specialist’s style of learning through intense, efficient drills.
To illustrate, Epstein examines the life stories of world-class jazz musicians from the very start of their musical training. He finds that, after exploring and discovering their preferred instrument, many jazz legends taught themselves how to play, without formal lessons, through an excruciatingly inefficient process of trial and error.
Many of the greatest jazz musicians learned through “osmosis,” discovering on their own how to mimic the music they heard around them. The struggle of aimlessly fiddling around gave these musicians a deeply ingrained familiarity with their instruments that formal training could never intentionally teach. Just like the other learning methods we’ve been discussing, this untutored learning style is much slower and less effective at first, but in the long run, it provides the foundation to achieve top-level performance.
By teaching themselves, these musicians also discovered the unique skill of effortless improvisation. Epstein argues that because they were forced to painstakingly generate their own techniques instead of simply learning to read sheet music (translating something that’s already been written), the self-taught jazz musicians developed a creative instinct that classically trained musicians never could. For this reason, master improvisors are often able to learn and perform classical arrangements, but classically trained musicians are fundamentally unable to improvise.
Epstein implies that the slow struggle of experimentation provides its own unique, lasting skills in any pursuit. All the time you spend learning and every mistake you make add up to invaluable mastery down the road, even if you can’t see it immediately. There’s no need to worry if you’re not progressing as quickly as specialists expect—they don’t realize that the most effective learning is slow and difficult.
The Strengths and Weaknesses of “Overlearning”
Countering Epstein’s argument that efficient specialists miss out on the depth of inefficient practice, recent research has identified the benefits of “overlearning”: practicing a skill after you’ve already achieved proficiency. If specialists can continue to train their existing skills indefinitely, the efficient path to mastery doesn’t seem to miss much. However, research shows that overlearning in narrow specialized domains may limit these specialists in a different way.
In one study on overlearning, two groups of subjects were trained to identify subtle striped patterns embedded in static on a screen. One group was assigned to overlearn, practicing for twenty minutes after both groups had already learned to pick out the correct pattern. The next day, the overlearners were able to complete their task far better than those who didn’t overlearn. However, when asked to perform a new task—identifying a slightly different pattern in the static—the overlearners actually performed worse than the control group.
What does this tell us? The researchers concluded that the overlearners’ weakened performance was a side effect of their “resilient” experience with the first task. They had learned the first skill so well that they found it difficult to stray from the procedure. In other words, overlearning narrow skills hinders the application of those skills in new contexts.
When specialists attempt to learn adjacent skills, like classical musicians attempting to improvise, their overlearning of narrow procedures may do more harm than good.
By now, you’ve explored your options and discovered a path that’s a good fit for you, and you’ve specialized enough to become a master in your field, but your journey isn’t over yet. We live in a constantly changing world, and you need to be prepared to pivot—that is, to start chasing an entirely new specialization, if need be.
If you decide to pivot—for example, you quit your job at a top law firm to start a daycare for dogs—a specialist would tell you you’re throwing away a lifetime of experience. A generalist would disagree. Epstein argues that pivoting is a valuable and often necessary part of a fulfilling life.
First, we’ll show why specialists are wrong to dismiss pivoting by debunking the value of “grit.” Next, we’ll discuss how to integrate pivoting into your life by planning in the short term instead of the long term. Finally, we’ll close by arguing that pivoting is an inherently satisfying part of life.
Often, we see pivoting as a sign of weakness, giving up on what we’ve promised to do—a deficiency of “grit.” Epstein disagrees, arguing that “grit” is a deeply flawed way to measure human potential.
Popularized in Angela Duckworth’s 2016 book Grit, “grit” refers to the personality trait needed to set impressive goals and achieve them.
Epstein’s problem with grit is that it lumps together persistence and commitment—two concepts that are similar, but not synonymous. While it’s beneficial to be as persistent as possible—to not be discouraged by struggles and setbacks—it’s not necessarily in your best interest to deeply commit to everything you’re doing. Duckworth’s “Grit Scale” test conflates persistence and commitment by assessing how much subjects agree with statements like “I often set a goal but later choose to pursue a different one” and “My interests change from year to year.”
While Duckworth is right to value commitment—after all, if you can’t commit to anything, you’ll never get anything done—she overlooks the fact that too much commitment can be just as harmful. Epstein cites a Gallup survey showing that 85% of workers around the world are either “not engaged” at work or “actively disengaged.” This shows that many people are far too committed to the jobs they currently have—if you’re actively apathetic about what you do eight hours a day, avoiding a job change not only hurts you, but it also the people who count on you at work.
Epstein argues that if a specific pursuit isn’t a good fit for you, sticking it out in the name of grit is the worst thing you can do. He points out that making a big, risky life change often takes more courage than doing nothing and continuing to plug away at whatever is in front of you.
The Dip: How to Know When to Quit
Epstein directly cites Seth Godin’s The Dip in this section—a book all about how grit is overrated.
Many people conflate two very different types of quitting: quitting because you want to refocus on something new (the good kind of quitting, as Epstein describes), and quitting because you’re in “the Dip.”
“The Dip” is the long span of time between being a beginner at something and being the best at something that’s difficult and less fun. However, because it weeds out the vast majority of people who try to do something, pushing through the Dip ensures that you are a scarce resource, and therefore, are valuable.
To Godin, it’s possible for anyone to become the best in the world at something if they stick at it long enough and push through the Dip. By his definition, “the world” might be a single country, a niche software market, or just a small town. Being the “best in the world” just means that everyone in your “world” wants you. Only then do you receive a disproportionate share of rewards.
Being the best in the world at something is a very attainable goal. You’ll often need to quit certain things to get there. But if you quit trying to be the best in the world, you’ll get stuck in a dead-end, and any more hard work you put in will give little in return.
Contrary to accepted wisdom, Epstein argues that it’s better to chase whatever opportunities you’re passionate about in the short term than to commit to a single long-term goal or vision for your future. This is true for a number of reasons and is rooted in the fact that the world is impossible to predict.
Firstly, people change, and it’s impossible for you to know how much you’ll change. A job that was a good fit for you ten years ago may not be anymore, and you’ll need to pivot.
Studies show that people vastly underestimate how much they’re likely to change over the next several years—a phenomenon known as the “end-of-history-illusion”—so they often overcommit to plans they make at a young age. Epstein states that our personalities change the most between the ages of 18 and 30, yet this is when many people decide what they’re going to do for the rest of their lives.
If you realize that the life you’ve planned for yourself doesn’t fit you anymore, it’s time to pivot.
Why We Don’t Think We’ll Change
Studies have shown that people will consistently underestimate how much they will change in the next ten years, even after reflecting on how much they’ve changed in the last ten years. This effect has been shown to last even among subjects in their 60s.
The psychologists behind the original 2013 end-of-history illusion study have offered a couple of theories to explain this phenomenon. The first is that we do it because it feels good—believing that you won’t change much is, in a subtle way, deeply comforting. The terrifying alternative is that the goals you’re working toward and sacrificing for may eventually seem pointless, or you may change your mind completely about the person you decided to marry.
Alternatively, we may assume that we won’t change just to conserve mental energy—it would be exhausting to try and predict your future self every time you make a decision.
Epstein argues that it’s impossible to predict what opportunities will or won’t be available in the future. Many of today’s jobs didn’t exist ten years ago. The people who get them don’t need to specifically aim for them—they just build up skills and pivot when the time feels right. Planning your career years in advance is like drawing a map for a city that hasn’t been built yet.
Epstein cites a Harvard study of nonlinear career paths known as the Dark Horse Project. The researchers assumed that they would struggle to find successful professionals with meandering careers, but, interestingly, 90% of their first 50 subjects acknowledged that their journeys were unusually indirect. They found that these professionals shared a propensity for short-term planning, passionately pursuing whatever seemed right at the time and pivoting if the need arose.
Roadtrip Nation’s Nonlinear Success Stories
As described in Cal Newport’s So Good They Can’t Ignore You, Roadtrip Nation is a nonprofit founded by a group of friends who went on a cross-country journey to interview people who successfully live meaningful lives. Their goal is to help people figure out what to do with their lives—and, like Harvard’s Dark Horse Project, they’ve found that most fulfilled people stumbled into their pursuits without a long-term plan.
In an interview with Roadtrip Nation, astrobiologist Andrew Steele admits that he never knew what his end goal was. When he started his PhD in biotechnology, all he wanted was “options.” He saw the degree as a valuable resource that would let him pivot into a wide range of interesting fields, understanding that it would be impossible for him to predict all the specifics.
Al Merrick, the founder and owner of revered surfboard manufacturer Channel Islands Surfboards, phrased it this way in his interview with Roadtrip Nation: “I set goals for myself at being the best I could be at what[ever] I did.” Short-term planning is all about working hard at what you can control and letting go of what you can’t.
The only way to know if a pursuit is a good fit for you is to try it. It’s impossible to know for certain how much you’ll enjoy something or how good you’ll be at it unless you experience it firsthand.
Circumstances and context have a far greater impact on personality than you would expect—people change drastically when they’re put in different situations. Think of an “ambivert” who is extroverted at parties but introverted at home with family. Epstein cites many examples of professionals who tried new things and discovered unexpected affinities for new pursuits.
In light of this, Epstein urges us to “first act, and then think”—you can plan all you want, but the only way you can know if a life is right for you is to try it out.
It’s better to live in the real world of immediate opportunities than the abstract, theoretical world of long-term plans. If you have even the slightest interest in trying something new, Epstein encourages you to give it a shot—it may click with you on a deeper level than you would ever expect.
The Pitfalls of Passion
In So Good They Can’t Ignore You, Cal Newport warns against taking Epstein’s argument too far—you shouldn’t be afraid to pivot if you’re stuck in a job you hate, but you shouldn’t expect your job to be thrilling and life-affirming every second of the day, either.
In Newport’s eyes, it’s alright to start a career in something you’re not passionate about. The idea that everyone has a single life purpose that they need to discover in order to be happy is a myth. In fact, studies have found that most people aren’t passionate about their dream jobs until after they’ve been working there for several years.
This is because the elements of motivation that get you excited to go to work in the morning are extremely different than most people expect. Psychologists have developed a framework called self-determination theory, identifying the primary contributors to motivation as autonomy, competence, and relatedness—that is, how much you feel you’re in control over your responsibilities, how skilled and capable you feel, and how connected you feel to those around you. None of these require a deeply emotional divine calling—you can acquire them as you work.
Finally, Epstein argues that people who aren’t afraid of making changes in their lives wind up happier, regardless of the specific situations they end up in. Studies show that people who make significant life changes report being significantly happier than those who don't.
In the book’s conclusion, Epstein shares what he believes to be his most important piece of advice: “Don’t feel behind.” You never need to despair that you’re “too late” to pursue something you’re interested in—the simple act of pivoting is fulfilling in itself.
Changing and Growing Makes You Happier
In The Happiness Project, Gretchen Rubin emphasizes the role of personal growth in a happy life. Rubin points out that no matter how happy your external circumstances make you, that feeling will fade with time—a principle called hedonic adaptation. As a result, in order to be happy, you must learn to find joy in the struggle toward a goal.
In her chapter on cultivating a passion, Rubin recounts the time she decided to write a novel—a leap outside of her comfort zone. Rubin asserts that, in order to be optimally fulfilled, not only should you find a passion that interests you, you should find one that challenges you. Setting a series of ambitious goals and achieving them provides sustainable happiness, circumventing hedonic adaptation by requiring constant change. Pivoting toward something you’ve never done before, like Rubin’s foray into novel-writing, provides this deeply satisfying element of challenge.
It’s difficult to strike the right balance between commitment to difficult goals and the flexibility to pursue exciting new opportunities. Take some time to reflect on whether you need more grit in your life or the courage to pivot and reset.
Write about a long-term goal you’ve set for yourself. Does it still seem worthwhile, or does a different goal sound more appealing?
Imagine your life five years from now. Would you rather be living the life where you’ve successfully accomplished your goal, or one where you’ve succeeded doing something totally different?
If you think you want to pivot, brainstorm new goals here. What sounds exciting to you, and what concrete steps can you take to get there?
If you want to stay on your current path, try to bolster your grit by writing about what’s motivating you. What do you want to get out of this goal? Who, specifically, are you trying to help?
Now that we’ve compared the traditional specialist’s path to excellence to Epstein’s new model for generalists, we’ll compare how each group performs in the professional world.
First of all, Epstein argues that, by and large, generalists are more likely to come up with successful creative ideas than specialists. We’re going to discuss various strategies generalists use to come up with fresh ideas and solve problems they’ve never seen before—analogical thinking, the use of familiar patterns in new situations; lateral thinking, the use of old information in new situations; and playful curiosity, the openness necessary to discover solutions by accident.
While specialists succeed by being one of a rare few who understand something, generalists are uniquely good at using less knowledge in more effective ways. Generalists try to limit themselves to only the information relevant to the problem at hand, and they draw that relevant information from a bevy of unlikely sources.
Epstein asserts that, due to rapid advances in scientific research, the mass of discovered human knowledge has been growing exponentially over the last several decades, and it’s now outpacing our ability to interpret, combine, and apply that knowledge to solve problems. The skills of generalists have never been in greater demand.
Generalists’ Pareto Principle
This is an instance of the now-ubiquitous Pareto Principle, otherwise known as the “80/20 Rule.” It’s a near-universal truth that a set of inputs yields extremely imbalanced outputs—in many cases, 20% of customers account for 80% of sales, 80% of your success comes from 20% of your work, and 80% of your stress is caused by 20% of your problems.
Generalists are uniquely positioned to take advantage of this kind of imbalance. If 80% of results come from 20% of ideas, deep, specialized knowledge isn’t always required. Generalists prioritize the quality of ideas over quantity of ideas, and as a result, often find more success than specialists despite knowing far less.
Epstein asserts that one of the most valuable tools generalists have is analogical thinking—the ability to use analogies to discover commonalities between dissimilar situations. For example, a start-up CEO struggling to decide whether to sell her rapidly growing company could inform her decision by studying 20th-century farmers who discovered massive wealths of oil underneath their land.
Analogical thinking is effective because seemingly unrelated problems often have the same underlying structure, enabling similar solutions. Research has shown that generalists’ diverse background experience makes it easier for them to identify this kind of deep structure and make valuable connections.
To prove the value of analogical thinking, Epstein cites a study in which a psychologist observed the problem-solving brainstorming meetings of research labs. The most successful labs were made up of scientists with diverse background experience in a number of different fields, all offering a multitude of analogies. The best group posed an analogy every four minutes on average.
(Shortform note: Kevin Dunbar, the psychologist who conducted this study, reveals that when he asked the researchers how they arrived at their conclusions, they forgot they had used any analogies at all. This shows that even when they aren’t consciously seeking out analogies, thinkers with wide-ranging backgrounds use them instinctively.)
The Danger of Faulty Analogies
While analogies are an invaluable tool in creative problem solving, they can also be a potent weapon for rhetoricians. Writers and speakers use analogies to ostensibly strengthen the rationale of their position, but faulty analogies can easily create the illusion of logic where there is none.
The reason analogies can be such powerful rhetorical devices is that they can transfer feelings attached to one concept to something entirely new. Karl Marx’s analogy comparing the proletariat class to slaves in chains gives his argument a specific, powerful emotional tenor. It takes far less careful reasoning to make a powerful analogy than it does to dissect one and tease apart exactly why two concepts aren’t as similar as they appear.
In order to detect whether or not an analogy is valid, ask yourself these two questions, identified in the textbook Writing Analytically: First, “Are the basic similarities greater and more significant than the obvious differences?” Second, “Am I over-relying on surface similarities and ignoring more essential differences?" These questions force us to slow down and consider the logic of an argument instead of being swept away by our initial emotional response.
Intuition would tell us that a single, closely related analogy would provide the most useful, relevant information to any given problem, but according to Epstein, this isn’t the case.
For example, if you wanted to create a successful app, your instinct might be to look at Uber’s early business plan and copy it as closely as possible—but this isn’t ideal. Often, distant analogies can offer more useful insights. If your idea is for a new anonymous dating app, you may be better off comparing it to the masquerade balls of Renaissance Italy than Uber. The more superficially unrelated an analogy is, the more likely it is to spark new ideas.
Additionally, Epstein asserts that it’s best to consider a wide range of many different analogies. If you study too many details about any one situation, you’re more likely to overanalyze and draw inaccurate conclusions than if you studied a wider range of examples. For example, if you only studied Uber while making your app, you may overvalue the 5-star rating system. Considering multiple analogies also helps inspire a greater number of ideas than considering just one.
Artists Use Analogies
In Steal Like an Artist, Austin Kleon collects and condenses widely accepted advice about creative inspiration. He writes, “You are a mashup [...] of what you choose to let into your life.” Since all art is essentially trying to do the same thing—evoke a reaction in its audience—each piece of art can be seen as an analogy for your own work. Each idea that inspires you is another way an artist has tackled your problem, and you’re free to adopt this strategy yourself.
Just as a wide range of analogies can help you figure out what works and what doesn’t, a wide range of creative inspirations helps you determine what is worth including in your own art. “Your job is to collect good ideas,” writes Kleon, “The more good ideas you collect, the more you can choose to be influenced by.”
Epstein’s logic applies here, too—the more superficially distant an artistic inspiration is from the situation at hand, the more likely it is you’ll come up with something original and effective. The screenwriter of Groundhog Day was inspired by a novel about vampires (The Vampire Lestat by Anne Rice), which got him thinking about what people would do if they lived forever.
In contrast with “forward thinking,” “lateral thinking” refers to any use of pre-existing knowledge in a new context. Specialists assume that new, undiscovered knowledge and technology is the key to innovation, but Epstein argues that this isn’t necessarily the case. Often, old ideas used in a new way are more valuable than cutting-edge discoveries. For example, the construction workers who popularized duct tape were simply repurposing an older tape they had used to seal ammunition boxes during World War II.
Lateral thinking is much more difficult to cultivate than specialized efficiency. Epstein argues that specialization is sometimes a shortcut around the need for fresh ideas—for instance, when video game companies compete for better graphics instead of more engaging gameplay. However, the evidence shows you can’t buy innovation—a study of private Research and Development teams (who are hired solely to innovate) found no correlation between funding and performance.
Instead, the key to lateral thinking is to get rid of perceived constraints on ideas—back away from the cutting edge and draw from a broader range of experience.
Creativity Requires Inefficiency
This intentional distance from the cutting edge is one of many counterintuitive strategies that have proven to be successful at fostering creativity and innovation. Often, the management strategies that yield the most creative ideas are the opposite of those required for efficient procedural work. Robert Sutton, author of Weird Ideas That Work, concludes that the most innovative organizations are “inefficient (and often annoying) places to work.”
Sutton offers another piece of counterintuitive advice: Managers of creative teams should reward employees for success and failure and only punish employees for inaction. Quantity, not quality, is the path to creative success.
Here’s another: Companies that want innovation should hire employees that often refuse to listen to bosses or coworkers. The Xerox employee who invented the laser printer was someone like this. He was working at a research and development lab, an organization whose sole purpose is innovation, yet when he suggested they look into the blossoming new potential of laser technology, he was dismissed by his coworkers and ordered to stop looking into it by his boss. Fortunately, he complained to someone higher up, got transferred to a new lab, and revolutionized the printing industry.
Epstein writes extensively about cases in which outsiders with less expertise and less information about a given situation solve problems that have stumped teams of experts for years. This speaks to the value of lateral thinking—sometimes, specialists are simply looking for answers in the wrong places.
Epstein describes a company called InnoCentive that allows organizations to post descriptions of problems and challenges they’re facing and crowdsource solutions from strangers on the Internet. Examples of problems solved by InnoCentive users include NASA’s inability to predict solar particle storms and the Oil Spill Recovery Institute’s struggle to clean oil out of their recovery barges.
One advantage unique to amateurs is not knowing enough to believe that an idea is ridiculous. For example, NASA employees scoffed at the idea to predict particle storms with telescopes built to detect radio waves—until it worked.
When Crowdsourcing Goes Wrong
Crowdsourcing like InnoCentive has become a popular problem-solving strategy in recent years. However, research has shown that it’s only successful when it’s designed in a specific way. Crowdsourcing works best when it’s directed at a single solvable problem and only attracts the right kind of people. Netflix’s 2006 “Netflix Prize” is a prime example: The company offered to pay $1 million to whatever team could improve their suggestion algorithm by 10%. The nature of the technical problem ensured that those posing solutions had at least some degree of expertise, and the quantitative nature of the solution made it easy for Netflix to sort out ineffective solutions.
Compare this to the crowdsourcing disaster of the BP oil spill. More than a hundred experts at BP were forced to sort through 123,000 potential solutions purporting to help clean up the millions of barrels of oil in the Gulf of Mexico. Out of these, only 470 were deemed potentially useful, and just 30 were put to use, most of which were minor improvements on existing techniques. Overall, it was declared a waste of time, due to the fact that the proposals attracted ineffective problem solvers and couldn’t be easily filtered.
It’s important to note that a team entirely comprised of outsiders wouldn’t succeed. Epstein admits that most groups require a certain amount of specialization. Researchers studying engineers have found that specialists and generalists are evenly matched in terms of innovation. Specialists are better at solving difficult technical issues, and generalists are better at lateral thinking.
The most innovative team members, however, are polymaths—whom Epstein defines as those who possess both broad knowledge in many areas and heavily specialized knowledge in at least one area. Polymaths represent the best of both worlds. They’re generalist enough to generate unique ideas and specialized enough to implement those ideas at a high level.
It’s easier than ever before to become a polymath and find success, for a number of reasons. The Internet has proven to be an invaluable resource for people who want to educate themselves to a professional level. When Michael Sayman was 13, he learned how to code online and released an app that became one of the top 100 in the world.
Additionally, as human knowledge expands into more and more domains, the number of unique potential combinations of knowledge between those domains grows exponentially. This increases your chances of mastering a skillset that no one else in the world has—“quantum biology,” for example, only rose to prominence in the last couple of decades.
The final way generalists come up with creative ideas is by deliberately cultivating a sense of playful curiosity.
Epstein argues that when professionals loosen up and temporarily abandon the need to accomplish anything serious, they often make wild breakthroughs that would never have normally been discovered. By freeing themselves from the constraints of serious work, they’re more likely to explore uncharted territory with unexpected value.
Because generalists largely only pursue things they’re excited about, through short-term planning and fearless pivoting, it’s easier for them to produce work for the intrinsic joy of exploration. Obviously, you need rules and direction to get most work done, but a healthy amount of playful curiosity can be surprisingly valuable.
For example, Epstein recounts how Nobel-winning physicist Andre Geim schedules “Friday night experiments”—time dedicated to fooling around in the lab with whatever interests him, regardless if he thinks it’ll amount to anything. One Friday night, he unexpectedly discovered that the water in a frog’s body was magnetic enough to levitate a frog in midair. On another, he found out that Scotch tape was able to strip off extremely thin layers of graphite, directly leading him to discover how to isolate graphene, a nanomaterial that’s one atom thick and two hundred times stronger than steel—which won him the Nobel.
The Power of Detachment
The defining characteristic of Geim’s Friday Night Experiments is detachment from outcomes—full acceptance of the possibility of failure and waste. In fact, this detachment is precisely what makes them so successful.
Detachment from the outcomes of your actions at first sounds just like giving up. However, it can be a powerful tool to achieve your goals, as well as an invaluable blessing for your mental health. Detaching from the outcome doesn’t necessarily mean you don’t care about the outcome. Instead, you’re simply becoming less hostile toward unfavorable outcomes. This mental shift provides a number of pragmatic benefits.
Being less desperate for a specific outcome gives you more power in negotiations and makes you appear more competent. It keeps you oriented toward future opportunities instead of tunnel-visioning into whatever is in front of you. It preserves your emotional energy for the tasks that really matter. Attaching yourself to a single outcome blinds you to everything else in the world, and in creative fields, this makes your job infinitely more difficult.
Efficiency-obsessed specialists would see Geim’s Friday night experiments as a waste of time, but they’re another example of why efficiency shouldn’t be your highest priority.
Epstein mourns that today’s science is far too concerned with efficiency. Research grants are more likely to be doled out if the research can prove that it’s worth the resources, but only funding research that looks promising is the quickest way to stifle new discoveries.
Epstein cites the example of HIV—before the AIDS epidemic, scientists believed that retroviruses were an insignificant phenomenon found only in animals. Curious scientists studied them anyway, amassing a body of knowledge that led to the speedy development of treatment for AIDS. Curiosity for its own sake needs to be preserved for science to operate effectively.
Roll the Dice on Research Funding
Epstein isn’t the only one criticizing today’s efficiency-obsessed system of funding research. Multiple studies have shown that grant reviewers are extremely subjective, unreliable judges of potential research. On top of this, they’re biased toward research that appears promising instead of what’s actually promising. One researcher claims that this funding structure “is turning scientists into entrepreneurs and managers” as they compete based on appearances. The desire to bring back curiosity-driven research without pre-ordained outcomes has inspired some creative suggestions for reform.
The idea to have random chance decide what research gets funded was first suggested in 2016 by microbiologist Arturo Casadevall and his team, whom we introduced back in Part 1 of this guide. The proposal is to allow reviewers to reject any research that seems entirely worthless and enter the rest into a lottery in which randomly selected research is funded. Theoretically, this would allow unpredictably valuable research, like the retroviruses that helped doctors treat HIV, to once again become possible.
Deliberately brainstorming a wide range of analogies is a proven strategy to reframe your problems and make them easier to solve. Try it for yourself.
Think of a problem that’s been troubling you for some time. This might be an obstacle at work, a bad habit you want to break, or a conflict with a family member. Have you encountered any problems like this before? How did you solve them?
Think of the last movie you saw. In what ways can you relate the characters’ problems to yours? Remember, distant analogies often work best—even if it’s a stretch, try to make some connection.
Go to any Wikipedia page and click the “random article” button on the left. Can you think of anything this article has to do with your problem? Is it sparking any new ideas?
If you’re still stuck, free-write for a bit, as quickly as you can. Come up with any analogy you can to describe your problem in a new way.
Generalists’ wide-ranging experience helps them cultivate a broader perspective and avoid an all-too-common pitfall of professional expertise: the tendency to overestimate their own knowledge.
In this section, we’ll first dive into Epstein’s argument that specialists have poorer judgment than generalists, as their limited experience causes them to see the world as simpler than it really is. Secondly, we’ll look at the characteristics of generalists that make them uniquely good at integrating multiple points of view.
On this topic, Epstein extensively cites the work of political psychologist Philip Tetlock, specifically his book Superforecasting. Near the beginning of his career, Tetlock began a study on predictions: He collected a total of 82,361 forecasts from 284 highly credentialed experts on topics such as global politics and economics, then waited decades to see how accurate the predictions would be.
Surprisingly, expert predictions were no more accurate than guesses from outside the field. Neither education nor years of professional experience had any correlation with forecasting success. More than 25% of “sure thing” predictions never came to pass, while 15% of events proclaimed to be “impossible” ended up happening.
The key difference between expert predictions and outsiders’ predictions was that outsiders were less likely to hold strong positions and declare situations totally certain or impossible. Epstein notes that this reveals a special kind of bias of expertise: The more details you know about something, the more confident you’ll be in your opinion and the more extreme that opinion will be.
Specialists who spend their entire careers studying a single subject unconsciously overestimate the influence that subject has on the world. They interpret too many events through the lens of their specialty, simplifying the world into narrow patterns of cause and effect. Epstein describes a professional volcanologist he met in grad school who attributed every extinction event in history to volcanic activity, ignoring or downplaying all evidence to the contrary. It’s difficult to maintain a balanced view of the world if you’ve invested 30,000 hours studying a topic as narrow as volcanoes.
Finally, when confronted with the fact that they were wrong, specialists paradoxically became even more certain of their beliefs.
Radical Anti-Prediction
Author Nassim Nicolas Taleb is notorious for being skeptical (and often disdainful) of experts who overestimate their own knowledge, exhibiting what he calls “epistemic arrogance.” In his book The Black Swan, he, like Epstein, uses Tetlock’s research as the basis for a large part of his argument. In Taleb’s eyes, the world is so complex and unpredictable that there is effectively no difference between “guessing” and “predicting,” and we should take this fact into account whenever we make decisions.
Taleb takes this argument a step further than Epstein and Tetlock, arguing that any attempt to forecast the future of a complex domain is irresponsible, likely to cause more harm than good, and makes a point to avoid making any such predictions himself. He argues that those who forecast for a living should “get another job,” as there is simply no way to forecast well.
The Overconfidence of Cults
The potential for human overconfidence and tendency to “double down” when ostensibly proven wrong can be seen in the behavior of religious cults. As recounted in the book Influence, a group of social scientists witnessed this firsthand when they went undercover in a Chicago-based cult that prophesied the imminent apocalypse.
In the weeks leading up to the purported date of a worldwide flood, cultists committed wholeheartedly to the movement, quitting their jobs, throwing away their belongings, and in some cases, losing custody of their children. Notably, however, they didn’t actively seek converts or publicity. When the doomsday came and went without a flood, they not only refused to lose faith in their leaders, who were supposedly receiving messages from extraterrestrial beings, they seemingly became more certain of their beliefs, calling up newspapers and attempting to get their story into any publication that would have them.
The cultists had sacrificed so much for this belief that they weren’t able to cope when it was disproved. In the face of uncertainty caused by seemingly irrefutable evidence, the cultists had no choice but to strengthen their devotion to their beliefs in order to keep them. To a lesser degree, this same fallacy is committed by Tetlock’s specialists who were proven wrong. They’ve committed their entire lives to their expertise, so instead of reconsidering their beliefs, they double down.
While most of the forecasters in Tetlock’s original study were equally unsuccessful, one group rose above the rest. Tetlock concluded that what set “superforecasters” apart was their ability to integrate a broad range of information and contradictory perspectives instead of being bogged down by a single point of view—which Epstein argues is a generalist’s specialty.
When Tetlock himself formed a team of superforecasters, he sought out generalists with a uniquely effective way of making judgments. The best forecasters read widely and had diverse interests, but none of them were experts in the fields they were being asked to predict.
Generalist predictors based their forecasting strategies on the assumption that their understanding was limited. Epstein points out that one way they did this is by intentionally cultivating open-mindedness.
The most successful generalists on Tetlock’s team willingly and frequently adjusted their predictions in the face of new evidence and persuasive arguments. They held little emotional attachment to any particular opinion and actively sought out ways in which they could be wrong. In fact, superforecasters implemented a rigorous feedback system that forced them to acknowledge when they were wrong and try to learn from those mistakes.
Epstein notes that generalist forecasters also frequently practiced analogical thinking, comparing unfamiliar situations to events that were unrelated, yet structurally similar, as we discussed earlier. Effective mental habits like this are the only way to truly improve our judgment of serious issues. Relying on our own expertise is a recipe for failure.
(Shortform note: Check out our guide to Superforecasting for more characteristics and strategies shared by superforecasters.)
Generalists Are More Open-Minded
Superforecasters’ habit of open-mindedness may be a direct result of their diverse background experience. One study has shown that MBA students who have traveled and engaged more deeply with new cultures have a greater capacity for “integrative complexity”—that is, the exact ability to consider multiple conflicting perspectives that makes Tetlock’s superforecasters so super. Additionally, when undergraduate students who had studied abroad were “primed” by writing about their travel experiences, they were able to solve 50% more creative problems in a standardized test than those who were not.
One way travelers broaden their perspective is by observing the strikingly different ways of doing things around the world that are perfectly normal for the people who live there. In a TED Talk, Derek Sivers uses the example that in Japan, streets don’t have names—the blocks between them do. This is a perfectly valid point of view, even though it’s the opposite of what we do. In the same way, some doctors in China get paid every month that you’re healthy, and when you’re sick, they help you for free because they failed to keep you healthy.
Travelers realize again and again that the things they assume are universal aren’t. Perhaps this is the easiest way to train ourselves to have less blind faith in our own beliefs. The wide-ranging experience of Tetlock’s superforecasters likely serves them in the same way.
Just as the most versatile individuals have accumulated a wide range of experience, Epstein argues that the most robust organizations cultivate a wide range of perspectives.
First, we’ll argue that the greatest weakness of narrowly specialized organizations is self-destructive conformity and show how robust organizations overcome this fatal flaw. Then, we’ll conclude this guide by explaining how diversity among team members enables innovation within an organization.
In the same way narrow-minded specialists assume their area of expertise applies to everything, narrow-minded organizations make the mistake of assuming that all problems can be solved in the same way.
To support this argument, Epstein draws heavily on an analysis of the 1986 Challenger space shuttle explosion. He argues that this disaster was due to NASA’s over-reliance on a single guiding principle, specifically, to ignore unreliable human intuition and make decisions based on objective quantitative data.
This principle is a good one—human intuition is sometimes dead wrong, and when it’s your job to build rockets, the idea that you would trust a gut instinct instead of data from rigorous testing is laughable. However, Epstein argues that this guiding principle didn’t fit the situation at hand.
The engineers were aware of a malfunctioning seal in the rocket’s booster and suspected that it was related to low air temperature. They made reasonable judgments based on a photo of the rocket’s interior—there was more soot on the wall after a cold day’s test launch than on a warm one, indicating that the cold was hardening their sealant, causing a leak. Unfortunately, since all they had were photos, with no conclusive data linking cold temperature to failure, the higher-ups at NASA felt the engineers’ argument wasn’t strong enough to justify canceling the launch.
Even though the engineers’ logic made perfect sense, NASA employees were in the habit of ignoring reason without data. In Epstein’s eyes, relying on a single solution for a problem it couldn’t solve is what caused the disaster.
An Alternative Lesson From the Challenger Explosion
In Think Like a Rocket Scientist, NASA scientist-turned-lawyer Ozal Varol offers an alternative takeaway from the Challenger disaster. Both the Challenger and the similar 2003 Columbia explosion were preceded by a series of successful test flights, giving the teams at NASA unwarranted confidence in the safety of the next flight, despite evidence to the contrary.
Every success makes us more likely to take bigger risks and make careless mistakes. One study showed that successful financial analysts become overconfident, ironically making their future predictions less accurate than someone with a less successful track record.
Varol points out the principal logical fallacy at work here—just because a system functioned correctly doesn’t mean that every part of that system functioned correctly. Additionally, just because a strategy worked doesn’t mean it’s infallible, or even the best strategy available. People are far less likely to dissect what they did wrong after a success than a failure, even though it’s unlikely that they did everything perfectly.
After beating the odds and landing a man on the moon, NASA began to grow complacent. NASA engineers were so confident, they neglected to include an escape system for the crew of the Challenger, resulting in seven deaths. Its “quality assurance” team was cut from around 1,700 to 505 from 1970 to 1986. Success made them reckless. We should learn from this: pay attention to the parts of your successes that go wrong, and try to objectively evaluate each decision you make.
In contrast, the best organizations embrace the idea that there’s no one solution to every problem.
Epstein notes that it’s common advice for managers to foster “congruence” by aligning their organizations under a single guiding principle. This is based on the idea that mixed messages within an organization lead to confusion and counterproductivity. For example, a manager who tells his team to exercise more autonomy but refuses to stop micromanaging everyone is creating an unreliable, contradictory organization. This certainly isn’t healthy.
However, Epstein argues that organizations built around a single core value are likely to get stuck in one way of thinking. Instead, organizations, as well as the individuals within them, should strive to achieve the seemingly impossible task of embodying multiple conflicting ideals at once.
For example, one common conflict that many organizations struggle to balance is between protocol and intuition, as we saw happen at NASA. Both of these elements are valuable to a certain degree, and Epstein argues that organizations need to recognize this, even if it means embracing contradiction. Conflicting values put a healthy pressure on team members to question their own decisions and learn from their mistakes.
How Ray Dalio Resolves the Conflict of Ideals
In Principles, hedge fund manager Ray Dalio describes a unique way that he was able to balance trust in the organization and individual intuition at his company, Bridgewater. He describes a hybrid form of management that allows for either protocol or individual judgment to reign depending on the specific situation: “Believability-Weighted Decision-Making.”
Anyone is allowed to make a suggestion or weigh in on a decision at Bridgewater. But the influence each person has on the eventual outcome depends on their believability. Dalio breaks this quality down into two parts—someone who is “believable” has 1) a proven track record of success with this type of problem, and 2) the ability to logically articulate the rationale behind their opinion. When groups of employees are asked to vote on a given decision, their votes are mathematically weighted according to their believability.
This strategy prevents teams from becoming slaves to protocol, as any serious challenge to the protocol must be considered. The strategy is also protected from the biases of human intuition, as illogical and unproven arguments are devalued by default. Dalio’s decision-making process is proof that it’s possible to reconcile conflicting values with an elegant, non-contradictory solution.
Epstein argues that another way organizations should cultivate range is by bringing together diverse teams of members from different backgrounds.
As we discussed earlier, innovation is all about bringing together ideas in new ways. Team members with diverse backgrounds bring together diverse ideas, making it more likely that they’ll come up with something new. Epstein notes that for this reason, scientists who have worked abroad at some point in their lives, on average, make more impactful discoveries.
Diverse team members are also more likely to bring conflicting values which, when expressed constructively, contribute to a healthy tension, as we just discussed. The diverse superforecasting teams we mentioned earlier are particularly good at this.
Epstein asserts that diversity can be discovered even within a single organization. In the most effective organizations, team members frequently work with new collaborators, assisting departments outside of their specific area of expertise. In contrast, clustering into small teams that rarely interact or exchange members stifles creativity.
Reconciling Differences
True diversity of ideas in the workplace necessarily requires a constructive approach to conflict and dissent. It’s easy for differences between people to spark division and hurt rather than innovation. In the seminal 1999 work Nonviolent Communication, psychologist Marshall Rosenberg offers a detailed step-by-step guide to ensuring that conflicts are resolved in a compassionate and productive way.
Express your own needs without making demands
Identify the other person’s needs
Verify that each of you understands the other’s needs
Express empathy for the other person’s pain or frustration
Propose solutions that meet each person’s needs
As these steps indicate, the heart of nonviolent communication is human connection. Mutual understanding and compassion put greater emphasis on both parties’ similarities than their differences, taking some of the friction out of diversity.