Flirting with Your Possible Selves
A review of David Epstein’s Range: Why Generalists Triumph in a Specialized World
Roger Federer is considered to be one of the greatest tennis players of all time. He holds the record for most Grand Slam men’s singles Championships with 20 titles and has been in 30 finals. Roger has the longest grass-court winning streak in the Open Era as he won 65 consecutive matches on grass from 2003 to 2008.
The popular advice to attain such mastery? Start early, focus intensely, and rack up as many hours of deliberate practice as possible. Well, maybe there’s another way to look at it.
As a young kid, Roger didn’t focus on tennis early on. He dabbled in skiing, wrestling, swimming and skateboarding. He played basketball, handball, tennis, table tennis, and soccer at school. “I was always very much more interested if a ball was involved,” he would say.
By the time he finally gave up other sports to focus on tennis, other kids had long since been working with strength coaches, sports psychologists and nutritionists. But it didn’t seem to hamper his development. In his mid-30s, an age by which even legendary players are typically retired, he would still be ranked №1 in the world.
In his book: Range: Why Generalists Triumph in a Specialized World, David Epstein makes a strong point for accumulating a breadth of different experiences. “In a world that increasingly incentivizes, even demands, hyperspecialization,” he writes, “we … need more Rogers: people who start broad and embrace diverse experiences and perspectives while they progress.”
It’s been proven severally that for tasks when the rules are known — clear and don’t change over time: a computer will easily overperform a human being. IBM supercomputer Deep Blue evaluated two hundred million chess positions per second when it defeated Garry Kasparov in 1997. Consider many of the popular AI-is-coming-to-replace jobs: bookkeeping, data entry, courier services, etc. A bookkeeper clerk has very low surprises on the job compared to an event manager. Quickbooks or Microsoft Office is faster at recording transactions and identifying which of those is debit, credit, receivables or payables than a human being. You can create a macro in Excel to perform the entire person’s role.
Our greatest strength as human beings, I think, is the exact opposite of narrow specialization — the ability to wield different facts and connect disparate pieces of information. The author puts it clearly: “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 domain and apply it in an entirely new one”
This is why I think life should be an experiment. You may consider it weird but I can’t tell you the exact job I think I’ll be doing in 5 years. In fact, it’s not likely I’ll be involved in a single vocation. It’s like travelling on an eight-way lane, rather than down a single-lane one-way street.
The author narrated what the computational neuroscientist Ogi Ogas found out when he set out to study folks with unusually winding paths: “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?’”
Paul Graham, the co-founder of Y Combinator, puts it nicely:
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. . . . 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...
When you consider that many of the largest problems we face today hardly require a single skill to solve, you get to appreciate cross-functional learning even more.
Like Michael Simmons described, let’s examine obesity for instance.
The chart below from the Diversity Bonus book by researcher Scott Page shows a portion of just how complex the obesity epidemic is.
As you can see, many different fields are needed to solve this problem: exercise physiology, genetics, behavioural psychology, sociology, economics, marketing, general psychology, education system, nutrition.
Of course, this doesn’t mean, for example, you shouldn’t pursue a PhD in a field you’re particularly interested in. We all specialize to one degree or another at some point in time. But while doing that, actively pursue knowledge outside your core field. Explore, diversify and broaden your range.
