Year of Books 2021: Range: Why Generalists Triumph in a Specialized World by David Epstein
All views, opinions and statements are my own.
Greetings, Romulo here! đź‘‹
Welcome to the third post of my Year of Books 2021 series đź“š. Find here my first post with the introduction to the project and key takeaways from the book High Output Management by Andrew Grove.
As I mentioned there:
This year, I’m trying something new and bringing you value along the way. For each book I read (excludes fiction), I’ll publish a Medium post with my takeaways. While I hope this will spark your interest and help you succeed, this will also help me, since IMO there’s no better way to learn than receiving and digesting new information, processing and summarizing it, and explaining it to someone else (hopefully in an understandable way!) .
Let’s get started!
Overview (description provided by Amazon)
Plenty of experts argue that anyone who wants to develop a skill, play an instrument, or lead their field should start early, focus intensely, and rack up as many hours of deliberate practice as possible. If you dabble or delay, you’ll never catch up to the people who got a head start. But a closer look at research on the world’s top performers, from professional athletes to Nobel laureates, shows that early specialization is the exception, not the rule.
David Epstein examined the world’s most successful athletes, artists, musicians, inventors, forecasters and scientists. He discovered that in most fields — especially those that are complex and unpredictable — generalists, not specialists, are primed to excel. Generalists often find their path late, and they juggle many interests rather than focusing on one. They’re also more creative, more agile, and able to make connections their more specialized peers can’t see.
Provocative, rigorous, and engrossing, Range makes a compelling case for actively cultivating inefficiency. Failing a test is the best way to learn. Frequent quitters end up with the most fulfilling careers. The most impactful inventors cross domains rather than deepening their knowledge in a single area. As experts silo themselves further while computers master more of the skills once reserved for highly focused humans, people who think broadly and embrace diverse experiences and perspectives will increasingly thrive.
Key Takeaways (TL;DR)
- “Many hours of practice” inevitably leads to expert performance, but only for domains centered on patterns that repeat over time
- A rapidly changing, wicked world demands conceptual reasoning skills that connect ideas across context
- “Go broad before going deep” is integral to the development of great performers — more often than not, people choose to skip step 1
- Deep learning is about making connections, developing mental schemes that can be matched to new problems
- Before solutioning, define the right problem; when solutioning, think outside your own domain — how would person / company X tackle this?
- You change over time and so do your desires and motivations — embrace the possibilities of what you can be and test and learn your way into your future self
- To break through, build a diverse team. "Birds can see farther, frogs can see deeper. The world is broad and deep. You need both." (Freeman Dyson)
- What brought you here may not take you there — "active open-mindedness" is your best shot at tackling new problems
- Learning how to think and integrate skills and knowledge into new problems and domains is highly underrated
Key Takeaways (One-click down)
#1 “Many hours of practice” inevitably leads to expert performance, but only for domains centered on patterns that repeat over time.
From firefighters to chess players to professional athletes, the world is full of expert performers that we aspire to be and regret that we will never had the same head start, since they’s been practicing for years.
In isolation, that seems to be the case — if I want to be a golfer, I’ll be where Tiger Woods was 20 years ago — but what’s omitted is that “many hours of practice” works great with “kind” domains, those centered on patterns that repeat over time.
For wicked domains, those that have no “pattern repetition” and typically involve human behavior — e.g. potential of a college student, success rate in job training, and patient performance — there’s no causal (or even strong association) between pattern repetition and top performance.
The problem is that we’ve been using the expert-performer type of stories as inspiration, which represent the very same examples that can and will be fully automated in the future. As we shift to more strategic, big-picture thinking and a world with exponential challenges and solutions — get inspired here (Singularity University, Global Grand Challenges) — this is where we find the unique, lasting, and differentiated value of being human.
#2 A rapidly changing, wicked world demands conceptual reasoning skills that connect ideas across context.
Consider abstract thinking — the ability to move freely, to shift from one category to the other.
Here's an example. What do you see below?
If your answer was "it's a mug," congratulations, you just put into practice your specialized thinking, centered on patterns that repeat over time.
Now let's try again. What do you see?
Washington DC? Vacation? Coffee? Breakfast? Ceramic? Objects with handle?Celebratory theme? Starbucks (this one is only for the pros!) and the list goes on and on.
That's abstract thinking, a critical tool to develop critical intelligence, see the world beyond the area of specialization, and tackle new, never-experienced-before problems.
#3 “Go broad before going deep” is integral to the development of great performers — more often than not, people choose to skip step 1
The author offers a series of examples that range from violinists to olympic professional athletes, all centered on the fact that high performers go through a trajectory of learning from distinct instruments, techniques, and practices before specializing themselves on being extraordinary in one thing.
Great perspective on the criticality of getting exposed to different learnings, shapes, and forms (lightly structured sampling period) before investing in focused specialization (increased structured with an explosion of practice).
#4 Deep learning is about making connections, developing mental schemes that can be matched to new problems
There are two types of learnings out there:
- Using procedures: practice based on something that has just been learned, guided by an intuition that "immediate results" and "nailing down one particular thing" is the way to go.
- Making connections: connecting broader concepts, focused on problem solving in varied conditions; it results in knowledge that is flexible (applicable to other problems) and sticks (vs being forgotten in a few days).
#5 Before solutioning, define the right problem; when solutioning, think outside your own domain — how would person / company X tackle this?
In a wicked world with wicked problems, it can be disastrous to quickly apply your “go-to procedures and specialized knowledge” when problem solving. However, when leveraging analogies from different domains, do not settle for a single one — otherwise and maybe unintentionally, you may be looking for an example to support how you think instead of changing your approach to how the problem is solved.
Some additional definition and example for you. "Deep analogical thinking is the practice of recognizing conceptual similarities in multiple domains or scenarios that many seem to have little in common on the surface.” Learn more here or google "Karl Duncker save patient with tumor" (this is one of the possible results with some really interesting problem solving).
#6 You change over time and so do your desires and motivations — embrace the possibilities of what you can be and test and learn your way into your future self.
A great way to illustrate the above is a commencement speech prepared by the amazing Paul Graham (entrepreneur, investor, and co-founder of Y Combinator —his essays are a "must read").
Oh btw, the speech was never delivered, the school rescinded Paul's invitation. Why? Well, if I have your attention until this point, you may have realized that advocating for the key takeaways from the book — making the case against "blind specialization” — hits quite hard the very foundation of most of our educational institutions.
It might seem that nothing would be easier than deciding what you like, but it turns out to be hard, partly because it’s hard to get an accurate picture of most jobs…Most of the work I’ve done in the last ten years didn’t exist when I was in high school. The world changes fast, and the rate at which it changes is itself speeding up. In such a world it’s not a good idea to have fixed plans.
And yet every May, speakers all over the country fire up the Standard Graduation Speech, the theme of which is: don’t give up on your dreams. I know what they mean, but this is a bad way to put it, because it implies you’re supposed to be bound by some plan you made early on. The computer world has a name for this: premature optimization. And it is synonymous with disaster. These speakers would do better to say simply, don’t give up.
Instead of working back from a goal, work forward from promising situations. This is what most successful people actually do anyway.
In the graduation-speech approach, you decide where you want to be in twenty years, and then ask: what should I do now to get there? I propose instead that you don’t commit to anything in the future, but just look at the options available now, and choose those that will give you the most promising range of options afterward.
#7 To break through, build a diverse team. “Birds can see farther, frogs can see deeper. The world is broad and deep. You need both” (Freeman Dyson)
Freeman Dyson, — British-American theoretical and mathematical physicist, mathematician, and statistician — once wrote the masterpiece Birds and Frogs. Here's his intro paragraph:
Some mathematicians are birds, others are frogs. Birds fly high in the air and survey broad vistas of mathematics out to the far horizon. They delight in concepts that unify our thinking and bring together diverse problems from different parts of the landscape. Frogs live in the mud below and see only the flowers that grow nearby. They delight in the details of particular objects, and they solve problems one at a time. I happen to be a frog, but many of my best friends are birds. Mathematics needs both birds and frogs. Mathematics is rich and beautiful because birds give it broad visions and frogs give it intricate details. Mathematics is both great art and important science, because it combines generality of concepts with depth of structures. It is stupid to claim that birds are better than frogs because they see farther, or that frogs are better than birds because they see deeper. The world of mathematics is both broad and deep, and we need birds and frogs working together to explore it.
When the path is clear (kind problems), you want specialization. When the path is unclear (wicked problems), the same specialized routines no longer suffice and will pull you away from breakthrough innovation. In this case, you need breadth of experience, which is commonly found on diverse teams.
#8 What brought you here may not take you there — “active open-mindedness” is your best shot at tackling new problems
Two things for you to remember:
- Treat your own ideas and views of the world as hypotheses and encourage people to falsify them.
- Because #1 becomes harder and harder the more specialized and experienced you are, be aware that others have the same challenge, so don't blindly accept their point of view, data insights highly curated into slides, and problem-solving approaches that have "always" worked.
#9 Learning how to think and integrate skills and knowledge into new problems and domains is highly underrated
Here are two quotes from the book that stuck with me:
People walk around with all the knowledge of humanity on their phone, but they have no idea how to integrate it. We don't train people in thinking and reasoning."
At its core, hyper-specialization is a well-meaning drive for efficiency — the most efficient way to develop, assemble, and learn something. Inefficiency needs cultivating too…when you push the boundaries, a lot of it it is just probing. It has to be inefficient.
That’s a wrap!
Since I have you here, please consider reading my previous posts:
- Interview with Rodrigo Iannuzzi, Product Lead and ex-Nubank, a company on a mission of reinventing what’s possible to redefine people’s relationship with money (link here).
- My key takeaways from the book “No Rules Rules: Netflix and the Culture of Reinvention by Reed Hastings and Erin Meyer” (link here).
Thank you again for your support and looking forward to continuing my journey with you on Medium.
Cheers, Romulo
