Range by David Epstein
I love this book! So much to unpack. Resonated so much with chapter 7.
Key takeaways #
- Having a head start is overrated. It’s only an advantage when you start on the right thing.
- Match quality is more important. Have a sampling period before you start. Pivot when there are better matches available (not when it’s hard).
- How to improve match quality? Test-and-learn, not plan-and-implement. We discover what we love by doing, by trying new activities, building new networks and finding new role models.
- [[Prefer work that employs creativity]]. Repetitive work is easily replaceable by computers.
- Relying on past experience in an unkind domain, or a changing world, is dangerous. Know when to drop your experience or even knowledge, so you see things as they are.
- Struggle is good for learning. Tactics like “spacing” and “interleaving” makes it more difficult to learn but are more effective.
- “Eventual elites typically devote less time early on to deliberate practice… Instead they undergo what researches call a ‘sampling period.’” (p. 7)
- What’s the value of early sampling?
- Finding better fit — “One study showed that early career specializers jumped out to an earnings lead after college, but that later specializers made up for the head start by finding work that better fit their skills and personalities.” (p. 9)
- Studies have shown that “highly credentialed experts can become so narrow-minded that they actually get worse with experience, even while becoming more confident — a dangerous combination…” and that “learning itself is best done slowly to accumulate lasting knowledge, even when that means performing poorly on the tests of immediate progress.” (p. 11)
- “The challenge we all face is how to maintain the benefits of breadth, diverse experience, interdisciplinary thinking, and delayed concentration in a world that increasing incentivizes, even demands, hyper-specialization.” (p. 13)
Chapter 1 - The Cult of the Head Start #
- “In those domains, which involved human behavior and where patterns did not clearly repeat, repetition did not cause learning. Chess, golf, and firefighting are exceptions, not the rule… these are what psychologist Robin Hogarth termed “kind” environments. Patterns repeat over and over, and feedback is extremely accurate and usually very rapid.” (p. 21)
- “In wicked domains, the rules of the game are often unclear or incomplete, there may or may not be repetitive patterns and they may not be obvious, and feedback is often delayed, inaccurate, or both.”
- “There is a saying that ‘chess is 99 percent tactics.’ Tactics are short combinations of moves that players use to get an immediate advantage on the board. When players study all those patters, they are mastering tactics. Bigger-picture planning in chess — how to manage the little battles to win the war — is called strategy.” … when facilitated by computers, people realize “Human creativity was even more paramount under these conditions, not less.” (p. 23)
- “Chunking — rather than struggling to remember the location of every individual pawn, bishop, and rook, the brains of elite players grouped pieces into a smaller number of meaningful chunks based on familiar patters… this helps explain instances of apparently miraculous, domain-specific memory, from musicians playing long pieces by heart to… Chunking can seem like magic, but it comes from extensive, repetitive practice.” (p. 26)
- “Even when they did beat humans in individual games, human players adjusted with ‘long-term adaptive strategy’ and started winning. ‘There are so many layers of thinking,’ Julian Togelius, an NYU professor who studies gaming AI said. ‘We humans sort of suck at all of them individually, but we have some kind of very approximate idea about each of them and can combine them and be somewhat adaptive. That seems to be what the trick is.’… ‘Not just games, in open ended real-world problems we’re still crushing the machines,’ Gary Marcus, a psychology and neural science professor said. (p. 29)
- “When narrow specialization is combined with an unkind domain, the human tendency to rely on experience of familiar patterns can backfire horribly.” (p. 30)
- This is what Chris Argyris called “single-loop learning”
- A paper titled “How Not to Teach People to Discover Rules” — that is, by providing rewards for repetitive short-term success with a narrow range of solutions. (p. 31)
- Suggestion: vary challenges within a domain drastically, and insist on “having one foot outside your world.” (p. 32)
- Connolly’s primary finding: “early in their careers, those who later made successful transitions had broader training and kept multiple ‘career streams’ open even as they pursued a primary specialty.” They “traveled on an eight-lane highway,” he wrote, rather than down a single-lane one-way street. (p. 34)
Chapter 2 - How the Wicked World was Made #
Thoughts/Summary: What modern human learned from education is to use concepts — to make abstractions out of concrete things. This allows us to apply knowledge from one domain to another. On the flip side, with many concepts in the mind, it’s harder to jump out of the existing framework to see things as they are.
A lot of examples from this chapter to show [[How you think is more important than what you know]]
Chapter 3 - When Less of the Same is More #
- “The students who would go on to be most successful only started practicing much more once they identified an instrument they wanted to focus on.” (p. 66)
- Inner drive is more important.
- “The strict deliberate practice school describes useful training as focused consciously on error correction.” (p. 74)
- “While improving, musicians do pretty much the opposite of consciously identifying errors and stopping to correct them.” (p. 75)
- “The more contexts in which something is learned, the more the learner creates abstract models, and the less they rely on any particular example. Learners become better at applying their knowledge to a situation they’ve never seen before, which is the essence of creativity.” (p. 77)
- “Creativity may be difficult to nurture, but it is easy to thwart, ” noted by Adam Grant (p. 77)
- Note: the idea of “coach after”, not before.
Chapter 4 - Learning, Fast and Slow #
- Playing multiple choice — “what they’re doing is seeking rules”. They were trying to turn a conceptual problem they didn’t understand into a procedural one they could just execute… The problem is that when it comes to learning concepts that can be broadly wielded, expedience can backfire. (p. 83)
- “Students do not view mathematics as a system. They view it as just a set of procedures.”
- But for learning that is both durable (it sticks) and flexible (it can be applied broadly), fast and easy is precisely the problem.
- One of those “desirable difficulties” is known as “generation effect.” Struggling to generate an answer on your own, even a wrong one, enhances subsequent learning… It requires the learner to intentionally sacrifice current performance for future benefit. (p. 85)
- Struggling to retrieve information primes the brain for subsequent learning, even when the retrieval itself is unsuccessful. (p. 88)
- It can even help to be wildly wrong — “hypercorrection effect” — the more confident a learner is of their wrong answer, the better the information sticks when they subsequently learn the right answer. (p. 86)
- Note: hold strong but loose opinions.
- Footnote mentions that this is for motor-skill learning, as bad habits are hard to undo.
- Another desirable difficulty: “spacing”, or distributed practice.
- Repetition was less important than struggle… If you are doing too well when you test yourself, the simple antidote is to wait longer before practicing the same material again. (p. 89)
- “Interleaving” is also a desirable difficulty, which holds true for both physical and mental skills. (p. 95)
- “The most successful problem solvers spend mental energy figuring out what type of problem they are facing before matching a strategy to it, rather than jumping in with memorized procedures.” (p. 96)
- “Kind learning environment experts choose a strategy and then evaluate; experts in less repetitive environments evaluate and then choose.”
- The research team recommended that if programs want to impart lasting academic benefits they should focus instead on “open” skills that scaffold later knowledge. (p. 97)
Chapter 5 - Thinking Outside Experience #
- “Kepler was so far outside the bounds of previous thought that there was no evidence in existence for him to work from. He had to use analogies.” (p. 100)
- Note: one of the tools for creativity
- “Most problem solvers are not like Kepler. They will stay inside of the problem at hand, focused on the internal details, and perhaps summon other medical knowledge, since it is on the surface a medical problem. They will not intuitively turn to distance analogies to probe solutions. They should, though, and they should make sure some of those analogies are, on the surface, far removed from the current problem.” (p. 107)
- Note: how to practice doing this?
- “Our natural inclination to take the inside view can be defeated by following analogies to the ‘outside view.’ The outside view probes for deep structural similarities to the current problem in different ones. The outside view is deeply counterintuitive because it requires a decision maker to ignore unique surface features of the current project, on which they are the experts, and instead look outside for structurally similar analogies. It requires a mindset switch from narrow to broad.” (p. 109)
- “Psychologists have shown repeatedly that the more internal details an individual can be made to consider, the more extreme their judgment becomes.” (p. 110)
- “Evaluating an array of options before letting intuition reign is a trick for the wicked world.” (p. 112)
- Successful problem solvers are more able to determine the deep structure of a problem before they proceed to match a strategy to it… As education pioneer John Dewey put it in Logic, The Theory of Inquiry, “a problem well put is half-solved.” (p. 115)
- “Those labs were Keplers by committee. They included members with a wide variety of experiences and interests. When the moment came to either dismiss or embrace and grapple with information that puzzled them, they drew on their range to make analogies. Lots of them.” (p. 118)
- Note: seems interesting environment to work in. I think there are more than simply “analogy”.
Chapter 6 - The Trouble with Too Much Grit #
- Malamud’s conclusion: “The benefits to increased match quality… outweigh the greater loss in skills.” Learning stuff was less important than learning about oneself. Exploration is not just a whimsical luxury of education; it is a central benefit. (p. 130)
- “You lose a good fraction of your skills, so there’s a hit,” Malamud said, “but you do actually have higher growth rates after switching.” Regardless of when specialization occurred, switchers capitalized on experience to identify better matches.
- (Career) matching process — An individual starts with no knowledge, tests various possible paths in a manner that provides information as quickly as possible, and increasingly refines decisions about where to allocate energy. The expression “young and foolish”, he wrote, describes the tendency of young adults to gravitate to risky jobs, but it is not foolish at all. It is ideal. They have less experience than older workers, and so the first avenues they should try are those with high risk and reward, and that have high informational value. (p. 136)
- The important trick, Seth Godin said, is staying attuned to whether switching is simply a failure of perseverance, or astute recognition that better matches are available.
- “I was not the type of person who wanted to spend my entire life learning one or two things new to the world, but rather the type who wanted constantly to learn things new to me and share them.” (p. 142)
- Note: I’m exactly such type of person too.
Chapter 7 - Flirting with Your Possible Selves #
- As Steven Naifeh said regarding Van Gogh’s life, some “undefinable process of digestion” occurred as diverse experiences accumulated. Hesselbein: “I was unaware that I was being prepared, I did not intend to become a leader, I just learned by doing what was needed at the time.” (p. 152)
- Dark horses were on the hunt for match quality. “They never look around and say, ‘Oh, I’m going to fall behind, these people started earlier and have more than me at a younger age,’” Ogas told me. “They focused on, ‘ Here’s who I am at the moment, here are my motivations, here’s what I’ve found I like to do, here’s what I’d like to learn, and here are the opportunities. Which of these is the best match right now? And maybe a year from now I’ll switch because I’ll find something better.’ ” (p. 154)
- Note: 1) start here, 2) motivation, 3) learn, 4) do.
- “The people we study who are fulfilled do pursue a long-term goal, but they only formulate it after a period of discovery.” (p. 155)
- Note: I think this is a better strategy than [[So Good They Can’t Ignore You]], which treats human somewhat like a machine (“just get good at it, don’t ask why”). But this strategy only works if you have financial support (e.g. for rich kids), for most people I agree it’s better to improve your skills first.
- In Gilbert’s terms, we are works in progress calming to be finished… some personality traits change over time in fairly predictable way… plus, while personality change slows, it does not stop at any age. Sometimes it can actually happens instantly. (p. 157)
- Shoda maintained that the most exciting aspect of the studies was demonstrating how easily children could learn to change a specific behavior with simple mental strategies, like thinking about the marshmallow as a cloud rather than food. (p. 159)
- At a given point in life, an individual’s nature influences how they respond to a particular situation, but their nature can appear surprisingly different in some other situation. (p. 159)
- This can be framed as “if-then signature”, or “context principle” as Ogas and Rose call it.
- “If you get someone into a context that suits them,” Ogas said, “they’ll more likely work hard and it will look like grit from the outside.”
- “It’s no use going back to yesterday,” she said, “because I was a different person then.” Alice captured a grain of truth, one that has profound consequences for the best way to maximize match quality.
- Ibarra concluded that we maximize match quality throughout life by sampling activities, social groups, contexts, jobs, careers, and then reflecting and adjusting our personal narratives. And repeat… come up with some experiments and see what happens… “First act and then think.”… “We discover the possibilities by doing, by trying new activities, building new networks, finding new role models.” We learn who we are in practice, not in theory. (p. 161)
- “Which among my various possible selves should I start to explore now? How can I do that?”… “Test-and-learn, not plan-and-implement.” (p. 163)
- Paul Graham: “Instead of working back from a goal, work froward from promising situations.”
Chapter 8 - The Outsider Advantage #
- InnoCentive: post “challenges” and rewards for outside “solvers”.
- “The trick: to frame the challenge so that it attracted a diverse array of solvers. The more likely a challenge was to appeal not just to scientists but also to attorneys and dentists and mechanics, the more likely it was to be solved.” (p. 173)
- Note: How does outside thinking work exactly? Can we reframe it in a way so it resembles problems from other fields?
- The Einstellung effect: the tendency of problem solvers to employ only familiar methods even if better ones are available.
- Pegau said “I think it happens more often than we’d love to admit, because we tend to view things with all the information we’ve gathered in our industry, and sometimes that puts us down a path that goes into a wall. It’s hard to back up and find another path.” (p. 177)
- “As Alph Bingham noticed, for difficult challenges organizations tend toward local search. They rely on specialists in a single knowledge domain, and methods that have worked before. If those fail, they’re stuck.”
- “Knowledge is a double-edged sword. It allows you to do some things, but it also makes you blind to other things that you could do.” (p. 179)
- Note: [[How you think is more important than what you know]]
Chapter 9 - Lateral Thinking with Withered Technology #
- “The generalists tended to get bored working in one area for too long. They added value by integrating domains, taking technology from one area and applying it in others.” (p. 204)
- “T-people like myself can happily go to the I-people with questions to create the trunk for the T,” she (Jayshree Seth) told me. “My inclination is to attack a problem by building a narrative. I figure out the fundamental questions to ask, and if you ask those questions of the people who actually do know their stuff, you are still exactly where you would be if you had all this other knowledge inherently…” (p., 207)
- “Melero and Palmer’s measured uncertainty in each technological domain: a high-uncertainty area had a lot of patents that proved totally useless, and some blockbusters; low-uncertainty domains were charactered by linear progression with more obvious next steps and more patents that were moderately useful… The higher the domain uncertainty, the more important it was to have a high-breadth team member.” (p. 208)
- Note: more upside in uncertain environments.
- Darwin only personal carried out experiments “opportune for experimental attack by a scientific generalist such as he was.” For everything else, he relied on correspondents, Jayshree Seth style. (p. 212)
- Note: how to choose what to do? Be a connector of smart people.
- Griffin’s research team noticed that serial innovators repeatedly claimed that they themselves would be screened out under their company’s current hiring practices. (p. 213)
Chapter 10 - Fooled by Expertise #
- “The average expert was a horrific forecaster… They were bad at short-term forecasting, bad at long-term forecasting, and bad at forecasting in every domain… The Danish proverb that warns ‘It is difficult to make predictions, especially about the future,’ was right.” (p. 219)
- “Experts remained undefeated while losing constantly.” — fail at “hard to vary” is described in [[The Beginning of Infinity]].
- “The more information they had to work with, the more they could fit any story to their worldview.” (p. 221)
- “Tetlock is clearly a fox… ‘But if your assumptions about human nature and how a good society needs to be structured are different, you would see this completely differently.’… ‘Let’s say for the sake of argument.’… He tried on ideas like Instagram filters until it was hard to tell which he actually believed.” (p. 222)
- “foxiest forecasters — just bright people with wide-ranging interests and reading habits but no particular relevant background.”
- Note: I want to be one of them.
- “A hallmark of interactions on the best teams is what psychologist Jonathan Baron termed ‘active open-mindedness.’ The best forecasters view their own ideas as hypotheses in need of testing. Their aim is not to convince their teammates of their own expertise, but to encourage their teammates to help them falsify their own notions.” (p. 227)
- When more information is dangerous (without realizing we are most likely wrong) — “Yale law and psychology professor Dan Kahn has shown that more scientifically literate adults are actually more likely to become dogmatic about politically polarizing topics in science. Khan thinks it could be because they are better at finding evidence to confirm their feelings: the more time they spend on the topic, the more hedgehog-like they become.”
- “[Charles Darwin] made a point of copying into his notes any fact or observation he encountered that ran contrary to a theory he was working on.” (p. 228)
- He also “needed a push from an actively open-minded teammate — or mentor, really.”
- “None of this is to say that hedgehog experts are unnecessary… Beneath complexity, hedgehogs tend to see simple, deterministic rules of cause and effect framed by their area of expertise, like repeating patterns on a chessboard. Foxes see complexity in what others mistake for simple cause and effect. They understand that most cause-and-effect relationships are probabilistic, not deterministic. There are unknowns, and luck, and even when history apparently repeats, it does not do so precisely.” (p. 229)
- “Skillful forecasters depart from the problem at hand to consider completely unrelated events with structural commonalities rather than replying on intuition based on personal experience or a single area of expertise.” (p. 230)
- Note: what is “structural commonalities” and how to practice finding them?
- “Sometimes, it involves putting experience aside entirely.”
- Note: learning not from experience (contra [[The learning loop]])
Chapter 11 - Learning to Drop Your Familiar Tools #
- When making decisions based on data, we usually didn’t do a good job of asking “Is this the data that we want to make the decision we need to make?” (p. 240)
- In The Challenger Launch Decision, Diane Vaughan suggested that using quantitative approach is so ingrained in NASA’s DNA, that reason without numbers was not accepted. (p. 245)
- When you drop your familiar too, you feel you’re doing something unnatural. “Dropping one’s tools is a proxy for unlearning, for adaptation, for flexibility.”
- It’s difficult for experienced professionals who have done the same thing over and over until the behavior has become so automatic that they no longer even recognize it as a situation-specific tool — Wick called “overlearned behavior” (p. 248)
- View your leadership not as decision making, but as sense making.
- “If I make a decision, it is a possession, I take pride in it, I tend to defend it and not listen to those who question it,” Gleason explained. “If I make sense, then this is more dynamic and I listen and I can change it.”
- There are no tools that cannot be dropped, reimagined, or repurposed in order to navigate an unfamiliar challenge.
- Note: Culture is a tool too. Emotions, prior experience, skills are tools too. They should serve the purpose to getting you to where you want (with moral values of course).
- One organizational strategy is to send a mixed message.
- The researcher found that the most effective leaders and organizations had range; they were, in effect, paradoxical. They could be demanding and nurturing, orderly and entrepreneurial, even hierarchical and individualistic all at once. A level of ambiguity, it seemed, was not harmful.
- Philip Fetlock also showed that thinkers who tolerate ambiguity make the best forecasts.
- The trick is to identify the dominant culture and then diversify it by pushing in the opposite direction.
- Balance formal process culture with a dose of informal individualism.
- “The chain of communication has to be informal, completely different from the chain of command.”
- “I told them I will not intercept your decisions that belong in your chain of command, but I will give and receive information anywhere in the organization, at any time. I just can’t get enough understanding of the organization from listening to the voices at the top.” (p. 264)
- A stunning study: patients with heart failure were less likely to die if they were admitted during a national cardiology conference, when thousands of top cardiologists were away.
- “No tool is omnicompetent. There is no such thing as a master-key that will unlock all doors.”
Chapter 12 - Deliberate Amateurs #
- One needs to let the brain think about something different from its daily work, Oliver Smithies would say. “On Saturday, you don’t have to be completely rational.”
- What sounds like hyper specialization today was actually a bold hybrid at the time.
- “Take you skills and apply them to a new problem, or take your problem and try completely different skills.” (p. 271)
- “A paradox of innovation and mastery is that breakthroughs often occur when you start down a road, but wander off for a ways and pretend as if you have just begun.”
- “I do not dig deep—I graze shallow… I go into a different subject every five years or so…” Deviating from what Gein calls the “straight railway line” of life is “not secure… psychologically,” but comes with advantages, for motivation and for “questioning things people who work in that area never bother to ask.”