Table of Contents
Deliberate practise
Deliberate practice, according to the study of thirty violinists that spawned the rule, occurs when learners are “given explicit instructions about the best method,” individually supervised by an instructor, supplied with “immediate informative feedback and knowledge of the results of their performance,” and “repeatedly perform the same or similar tasks.”
Period of exploration
Eventual elites typically devote less time early on to deliberate practice in the activity in which they will eventually become experts. Instead, they undergo what researchers call a “sampling period.” They play a variety of sports, usually in an unstructured or lightly structured environment; they gain a range of physical proficiencies from which they can draw; they learn about their own abilities and proclivities; and only later do they focus in and ramp up technical practice in one area.
Improvement later on after a period of sampling
Those who participated in more sports and nonorganized soccer, “but not more organized soccer practice/training,” improved more by age thirteen.
Early sampling is important
Prominent sports scientist Ross Tucker summed up research in the field simply: “We know that early sampling is key, as is diversity.”
Too much of an expert is dangerous with confidence
dove into work showing that highly credentialed experts can become so narrow-minded that they actually get worse with experience, even while becoming more confident — a dangerous combination.
Immediate progress might not aid accumulating knowledge
learning itself is best done slowly to accumulate lasting knowledge, even when that means performing poorly on tests of immediate progress. That is, the most effective learning looks inefficient; it looks like falling behind.
Too much specialisation
Everyone is digging deeper into their own trench and rarely standing up to look in the next trench over, even though the solution to their problem happens to reside there.
All areas, all ages
The research pertains to every stage of life, from the development of children in math, music, and sports, to students fresh out of college trying to find their way, to midcareer professionals in need of a change and would-be retirees looking for a new vocation after moving on from their previous one.
Where do we get wrong prediction for future success?
college administrators assessing student potential to psychiatrists predicting patient performance to human resources professionals deciding who will succeed in job training. 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.
Narrow domains yes, broad domains no
Whether or not experience inevitably led to expertise, they agreed, depended entirely on the domain in question. Narrow experience made for better chess and poker players and firefighters, but not for better predictors of financial or political trends, or of how employees or patients would perform.
Kind learning environments
“kind” learning environments. Patterns repeat over and over, and feedback is extremely accurate and usually very rapid. In golf or chess, a ball or piece is moved according to rules and within defined boundaries, a consequence is quickly apparent, and similar challenges occur repeatedly.
Deliberate practise work well with kind learning environemnts
That is the very definition of deliberate practice, the type identified with both the ten-thousand-hours rule and the rush to early specialization in technical training. The learning environment is kind because a learner improves simply by engaging in the activity and trying to do better.
Wiched learning domains
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.
Chunking
The grandmasters never had photographic memories after all. Through repetitive study of game patterns, they had learned to do what Chase and Simon called “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 patterns.
Superhuman in one narrow domain
The reason that elite athletes seem to have superhuman reflexes is that they recognize patterns of ball or body movements that tell them what’s coming before it happens. When tested outside of their sport context, their superhuman reactions disappear.
AI has also challenges in an unkind learning world of driving
The progress of AI in the closed and orderly world of chess, with instant feedback and bottomless data, has been exponential. In the rule-bound but messier world of driving, AI has made tremendous progress, but challenges remain. In a truly open-world problem devoid of rigid rules and reams of perfect historical data, AI has been disastrous. IBM’s Watson destroyed at Jeopardy!
AI systems need kind environments
Tellingly, Marcus gave me this analogy for the current limits of expert machines: “AI systems are like savants.” They need stable structures and narrow worlds.
Rewards will foster the same pattern
Incredibly, every student who was brand-new to the puzzle discovered the rule for all seventy solutions, while only one of the students who had been getting rewarded for a single solution did. The subtitle of Schwartz’s paper: “How Not to Teach People to Discover Rules” — that is, by providing rewards for repetitive short-term success with a narrow range of solutions.
Avoid cognitive entrenchment
Erik Dane, a Rice University professor who studies organizational behavior, calls this phenomenon “cognitive entrenchment.” His suggestions for avoiding it are about the polar opposite of the strict version of the ten-thousand-hours school of thought: vary challenges within a domain drastically, and, as a fellow researcher put it, insist on “having one foot outside your world.”
Nobel laureates have another hobby
Compared to other scientists, Nobel laureates are at least twenty-two times more likely to partake as an amateur actor, dancer, magician, or other type of performer.
Successful Adapters
They had range. The successful adapters were excellent at taking knowledge from one pursuit and applying it creatively to another, and at avoiding cognitive entrenchment.
Range is useful in the wicked world
They drew on outside experiences and analogies to interrupt their inclination toward a previous solution that may no longer work. Their skill was in avoiding the same old patterns. In the wicked world, with ill-defined challenges and few rigid rules, range can be a life hack.
Conceptual schemes
Conceptual schemes are flexible, able to arrange information and ideas for a wide variety of uses, and to transfer knowledge between domains. Modern work demands knowledge transfer: the ability to apply knowledge to new situations and different domains.
Self-directed varied problems
Research on thousands of adults in six industrializing nations found that exposure to modern work with self-directed problem solving and nonrepetitive challenges was correlated with being “cognitively flexible.”
Training is school is not analogous to the real world
In Flynn’s words, “the traits that earn good grades at [the university] do not include critical ability of any broad significance.”
Problem with higher education
Almost none of the students in any major showed a consistent understanding of how to apply methods of evaluating truth they had learned in their own discipline to other areas.
How to think
This must change, he argues, if students are to capitalize on their unprecedented capacity for abstract thought. They must be taught to think before being taught what to think about.
Fermi problems
The professor later explained that these were “Fermi problems,” because Enrico Fermi—who created the first nuclear reactor beneath the University of Chicago football field—constantly made back-of-the-envelope estimates to help him approach problems. The ultimate lesson of the question was that detailed prior knowledge was less important than a way of thinking.
Good at learning from the past, but not for the future
They were perfectly capable of learning from experience, but failed at learning without experience. And that is what a rapidly changing, wicked world demands — conceptual reasoning skills that can connect new ideas and work across contexts.
Constrained vs conceptual knowledge
The more constrained and repetitive a challenge, the more likely it will be automated, while great rewards will accrue to those who can take conceptual knowledge from one problem or domain and apply it in an entirely new one.
Early structured lessons vs late bloomers
As to structured lessons, every single one of the students who had received a large amount of structured lesson time early in development fell into the “average” skill category, and not one was in the exceptional group. “The strong implication,” the researchers wrote, is “that that too many lessons at a young age may not be helpful.”
Path to excellence starts with sampling period
The psychologists highlighted the variety of paths to excellence, but the most common was a sampling period, often lightly structured with some lessons and a breadth of instruments and activities, followed only later by a narrowing of focus, increased structure, and an explosion of practice volume.
Breadth == Transfer
In totality, the picture is in line with a classic research finding that is not specific to music: breadth of training predicts breadth of transfer. That is, the more contexts in which something is learned, the more the learner creates abstract models, and the less they rely on any particular example.
The economy of the past
Focusing on “using procedures” problems worked well forty years ago when the world was flush with jobs that paid middle-class salaries for procedural tasks, like typing, filing, and working on an assembly line. “Increasingly,” according to Duncan, “jobs that pay well require employees to be able to solve unexpected problems, often while working in groups.
Career goals change because people change
Career goals that once felt safe and certain can appear ludicrous, to use Darwin’s adjective, when examined in the light of more self-knowledge. Our work preferences and our life preferences do not stay the same, because we do not stay the same.
We learn who we are by doing and trying
As she put it, “We discover the possibilities by doing, by trying new activities, building new networks, finding new role models.” We learn who we are in practice, not in theory.
Riskier to commit before knowing yourself
“The people we study who are fulfilled do pursue a long-term goal, but they only formulate it after a period of discovery,” he told me. “Obviously, there’s nothing wrong with getting a law or medical degree or PhD. But it’s actually riskier to make that commitment before you know how it fits you.
Specialist contributions are decreasing
Specialist contributions skyrocketed around and after World War II, but more recently have declined. “Specialists specifically peaked about 1985,” Ouderkirk told me. “And then declined pretty dramatically, leveled off about 2007, and the most recent data show it’s declining again, which I’m trying to understand.”
T-shaped speciality
She described her approach to innovation almost like investigative journalism, except her version of shoe-leather reporting is going door-to-door among her peers. She is a “T-shaped person,” she said, one who has breadth, compared to an “I-shaped person,” who only goes deep, an analog to Dyson’s birds and frogs. “T-people like myself can happily go to the I-people with questions to create the trunk for the T,”
Specialists work great for specific domain of surgery
Surgical teams work faster and make fewer mistakes as they repeat specific procedures, and specialized surgeons get better outcomes even independent of repetitions. If you need to have surgery, you want a doctor who specializes in the procedure and has done it many times, preferably with the same team,
Kids need to make their own decision about their career
Duckworth added that it is neither “necessary nor healthy” for children to be directed toward one career before they can make that decision themselves—a decision that, again, took her years of adulthood.
Self-taught
I think when you’re self-taught you experiment more, trying to find the same sound in different places, you learn how to solve problems.”
Desirable difficulties
Kornell was explaining the concept of “desirable difficulties,” obstacles that make learning more challenging, slower, and more frustrating in the short term, but better in the long term.
When wrong answer is good
Struggling to generate an answer on your own, even a wrong one, enhances subsequent learning.
What does early frequent hinting does
The overall experiment results went like this: the more hints that were available during training, the better the monkeys performed during early practice, and the worse they performed on test day.
Frustrations means you are learning!!!
Frustration is not a sign you are not learning, but ease is.
Mix up the problems
In a study using college math problems, students who learned in blocks—all examples of a particular type of problem at once—performed a lot worse come test time than students who studied the exact same problems but all mixed up.
Figure out the problem before applying a procedure
Whether chemists, physicists, or political scientists, the most successful problem solvers spend mental energy figuring out what type of problem they are facing before matching a strategy to it, rather than jumping in with memorized procedures.
Evaluate then choose the strategy
Kind learning environment experts choose a strategy and then evaluate; experts in less repetitive environments evaluate and then choose.
Work ethic, resilience, direction
She designed a self-assessment that captured the two components of grit. One is essentially work ethic and resilience, and the other is “consistency of interests” — direction, knowing exactly what one wants.
Quit
Godin argued that “winners”—he generally meant individuals who reach the apex of their domain—quit fast and often when they detect that a plan is not the best fit, and do not feel bad about it. “We fail,” he wrote, when we stick with “tasks we don’t have the guts to quit.”
Switching because of perseverance or match
The important trick, he said, is staying attuned to whether switching is simply a failure of perseverance, or astute recognition that better matches are available.
Test and learn, not plan and implement
it is better to be a scientist of yourself, asking smaller questions that can actually be tested — “Which among my various possible selves should I start to explore now? How can I do that?” Be a flirt with your possible selves. Rather than a grand plan, find experiments that can be undertaken quickly. “Test-and-learn,” Ibarra told me, “not plan-and-implement.”
Einstellung effect
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.” Pegau was basically describing the Einstellung effect, a psychology term for the tendency of problem solvers to employ only familiar methods even if better ones are available.
Contributions from both generalists and specialists
The specialists and the generalists, they found, both made contributions. One was not uniformly superior to the other. (They also found inventors who had neither significant depth nor breadth—they rarely made an impact.) The specialists were adept at working for a long time on difficult technical problems, and for anticipating development obstacles. The generalists tended to get bored working in one area for too long.
Fame and accuracy
There was also a “perverse inverse relationship” between fame and accuracy. The more likely an expert was to have his or her predictions featured on op-ed pages and television, the more likely they were always wrong.
Hedgehogs vs Foxes
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.
Experience in one domain can always be applied in another
Even when you move on from an area of work or an entire domain, that experience is not wasted.
Only compare to yourself
Compare yourself to yourself yesterday, not to younger people who aren’t you. Everyone progresses at a different rate, so don’t let anyone else make you feel behind. You probably don’t even know where exactly you’re going, so feeling behind doesn’t help.
Quantity means more failures, but more successes
Creativity researcher Dean Keith Simonton has shown that the more work eminent creators produced, the more duds they churned out, and the higher their chances of a supernova success. Thomas Edison held more than a thousand patents, most completely unimportant, and was rejected for many more.
Stories always look orderly in retrospect
Told in retrospect for popular media, stories of innovation and self-discovery can look like orderly journeys from A to B. Sort of like how inspirational-snippet accounts of the journeys of elite athletes appear straightforward,
Kepler
In an age when alchemy was still a common approach to natural phenomena, Kepler filled the universe with invisible forces acting all around us, and helped usher in the Scientific Revolution. His fastidious documentation of every meandering path his brain blazed is one of the great records of a mind undergoing creative transformation. It is a truism to say that Kepler thought outside the box. But what he really did, whenever he was stuck, was to think entirely outside the domain.
Phil Knight, founder of Nike
In his memoir, Knight wrote that he “wasn’t much for setting goals,” and that his main goal for his nascent shoe company was to fail fast enough that he could apply what he was learning to his next venture. He made one short-term pivot after another, applying the lessons as he went.
Experts getting more and more entrenched in their own views
“The opposite happened with Paul Ehrlich and Julian Simon.” As each man amassed more information for his own view, each became more dogmatic, and the inadequacies in their models of the world more stark. There is a particular kind of thinker, one who becomes more entrenched in their single big idea about how the world works even in the face of contrary facts, whose predictions become worse, not better, as they amass information for their mental representation of the world.
NASA
Thanks to an extraordinarily strong technical culture, NASA had developed quantitatively rigorous “flight readiness reviews.” They were productively adversarial, like superforecasting team discussions. Managers grilled engineers and forced them to produce data to back up their assertions.
Apollo 11
flight director when Apollo 11 first landed on the moon, lived by that same mantra, the valorized process—“In God We Trust, All Others Bring Data”—but he also made a habit of seeking out opinions of technicians and engineers at every level of the hierarchy. If he heard the same hunch twice, it didn’t take data for him to interrupt the usual process and investigate.
Leadership with opposing trends
She 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.
Leadership interception at all levels
“I warned them, I’m going to communicate with all levels of the organization down to the shop floor, and you can’t feel suspicious or paranoid about that,” he said. “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.”
Information flow
Instead of a ladder, the organizational structure was concentric circles, with Hesselbein in the middle. Information could flow in many directions, and anyone in one circle had numerous entry points to communicate with the next circle, rather than just a single superior who acted as a gate.
Challenges of a hierarchical system
hierarchical teams benefitted from a clear chain of command, but suffered from a one-way chain of communication that obscured problems. The teams needed elements of both hierarchy and individualism to both excel and survive.
Creative work in a crisis
his observation that companies do their most impactful creative work in a crisis, because the disciplinary boundaries fly out the window.