Range Book Notes
by David Epstein
My personal book notes/summary on David Epstein's book, Range.
Table of Contents:
The 10,000 hour rule - the idea that the number of accumulated hours of highly specialized training is the sole factor in skill development, no matter the domain
Deliberate practice - learners "given explicit instructions about the best method", individually supervised by an instructor, supplied with "immediate informative feedback and knowledge of the rules of their performance", and "repeatedly perform the same or similar tasks"
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.
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.
Experience led to expertise depended entirely on the domain in question.
"kind" learning environment, patterns repeat over and over, feedback is extremely accurate and usually very rapid. True here.
"wicked" environment 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. Not true here.
Our greatest strength is the exact opposite of narrow specialization. It is the ability to integrate broadly. Modern work demands knowledge transfer: the ability to apply knowledge to new situations and different domains.
A "variety of base domains" foster analogical thinking and conceptual connections that can help students categorize the types of problems they are facing.
Successful problem solvers are more able to determine the deep structure of a problem before they proceed to match a strategy to it.
"Switchers", those who capitalized on experience to identify better career matches, are winners despite the adages about quitting.
Match quality - an individual starts with no knowledge, then tests various possible paths in a manner that provides information as quickly as possible, and increasingly refines decisions about where to allocate energy (aka finding work that you "match" with)/
The "Sunk Cost Fallacy" - having invested time or money in something, we loath to leave it, because that would mean we had wasted our time or money, even though it is already gone.
Change of interest, recalibration of focus, is not a disadvantage, it is actually an advantage
We should focus on short term planning: one short term pivot (goal) after another, applying lessons as we go instead of long term planning. Because it doesn't make sense for us to pick long term goals and careers for someone who we don't even know. We've changed a lot in the past 10 years (when we look back) but usually when we predict how much we will change in the next 10 years we don't think as much.
"So specializing early is a task of predicting match quality for a person who does not yet exist".
One of the benefits of having range is there's always going to be this somewhat serendipitous outside thinking that was going to make a solution more clever, cost-effective, efficacious, more on the money than anyone else's.
"Outside-in" thinking - finding solutions in experiences far outside of focused training for the problem itself. You don't necessarily reply on your specific domain training.
"Big innovation most often happens when an outsider who may be far away from the surface of the problem reframes the problem in a way that unlocks the solution"
Lateral thinking - reimaging of information in new contexts, including the drawing together of seemingly disparate concepts or domains that can give old ideas new uses
Specialists v. Generalists v. Polymaths
Specialists - adept at working for a long time on difficult technical problems, and for anticipating development obstacles
Generalists - tend 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
Polymaths (T-person) - broad knowledge with at least one area of depth, most likely to succeed
high tolerance for ambiguity
additional technical knowledge from peripheral domains
repurposing what is already available
adept at using analogous domains for finding inputs to the invention process
ability to connect disparate pieces of information from many different sources
appear to flit among ideas
broad range of interests
read more (and more broadly) than technologists and have a wider range of outside interests
learn significantly across multiple domains
Dropping one's tools is key for unlearning an already learned, unnecessary and useless skill, for adaptation and flexibility (e.g. firefighters clung to trusty methods, even when they led to bewildering decisions). These types of people need to improvise rather than throw out information that didn't fit into the established rubric
Author argues against the "congruence" culture: cultural fit among an institution's components-values, goals, visions, self-concepts, and leadership styles, all thoughts and signals are pointed in the same direction. This promotes consistency, predictability, and standard procedures rather than constantly adapting and reviewing standard procedures to better them.
Effective problem-solving culture balances standard practices with ambiguity.
An example of an effective problem solving culture was: "Monday Notes" by Von Braun of NASA - every week engineers submitted a single page of notes on their salient issues. Von Braun handwrote comments in the margins, then circulated the entire compilation. Everyone saw what other divisions were up to, and how easily problems could be raised. Monday Notes were rigorous, but informal - this encouraged cross-boundary communication which lead to more problems being solved
Professionals that remained deliberate amateurs in many fields and have a wide variety of hobbies and interests are incredibly useful. They could move easily among different teams, crossing organizational and disciplinary boundaries and create new collaborations. These new collaborations allow creators to "take ideas that are convention in one area and bring them into a new area, where they're suddenly seen as invention"
Work that builds bridges between disparate pieces of knowledge is less likely to be funded, less likely to appear in famous journals, more likely to be ignored upon publication, and then more likely in the long run to be a smash hit in the library of human knowledge
Innovation ecosystems should intentionally preserve range and inefficiency (dabbling and experimenting). Individuals should be encouraged to take detours, have a wide breadth of knowledge, and experiment with different hobbies and interests.
Original creators produce a lot of work that doesn't pan out but when they do produce an amazing piece of work it really stands out.
Don't feel behind, everyone progresses at a different rate. Start your own experiments and focus on your own personal voyage and goals
The book in 3 sentences.
Elites typically spend less time with mastery (10,000 hours) and deliberate practice on a specific field/skill and instead have a "sampling period" where they experiment with different hobbies and careers in unstructured or lightly structured environment; they gain a range of proficiencies from which they can draw; they learn about their own abilities; and only later do they focus in and ramp up technical practice in one area.
Professionals who have a large breadth of knowledge (being an amateur in many fields) and at least one area of depth (being an expert in at least one field) are more likely to succeed, they have a lot of qualities that successful people do: high tolerance for ambiguity, system thinkers, adept at using analogous domains, and more.
We as a society need to focus on developing range and preserve inefficiency, detours and experimentation or else we may be left with a bunch of highly specialized individuals who have a highly narrow way of thinking and are less likely to solve problems.