Why generalists triumph in a specialized world
David Epstein

Two years ago I decided I didn’t want to keep pursuing a college degree. I’d rather educate myself and trust (I always like to emphasize that it’s not the same as hope) that I’d still manage to make my life better than it was back then (trying to consider all the aspects in my life).

As today, I’m still not sure what were all the reasons that made me take that decision. And the more I keep thinking about it time after time, I feel like the reasons keep changing (I’m pretty happy with it, though!).

Yet, one of the reasons that sticks with me is that I wanted to have a broader set of knowledge than what staying in college would have allowed me to. It all started when I read Chaos: Making a new science, and learned a little bit about wheather, the circulatory system, and materials; which made me get a strong interest in non-fiction reading.

For that reason, this book was one of those that you constantly keep nodding and chuckling.

Trying to briefly write something I could re-read instead of re-reading the book (which I feel I’d may do anyways) is this:

A lot of experts start with a sampling period of different activities, instead of deliberate practice in the activity in which they’ll eventually become experts. Sampling (which I prefer to call broad exploration) instead of focusing (which I prefer to call deep exploration) can make someone to feel like a slow learner falling behind. However, it’s usually more effective.

Lasting learning is usually aquired with slow and struggling learning. Fast, focused and repeated rehearsal helps when trying to measure immediate learning. But slow, distributed, spaced rehearsal helps when trying to transfer information from short-term memory to long-term memory.

When trying to learn to learn mathematical analysis, for example, it’s better to mix problems and try to decide the appropiate procedure to solve each one, instead of separating them beforehand. The important thing here is struggling when trying to decide what procedure to use.

Other useful tip that was more or less a direct conclusion of favoring breadth rather than depth is learning to quit. You shouldn’t quit when making progress gets difficult, but when you objectively (as possible) think there are better approaches.

[Seth] 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.” Godin clearly did not advocate quitting simply because a pursuit is difficult. Persevering through difficulty is a competitive advantage for any traveler of a long road, but he suggested that knowing when to quit is such a big strategic advantage that every single person, before undertaking an endeavor, should enumerate conditions under which they should quit. 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.

One of the things that amazed me the most was the study that concluded that, when an individual creator broadens their experience, is capable of more innovation than a team with the same collective experience.

Individual creators started out with lower innovativeness than teams—they were less likely to produce a smash hit—but as their experience broadened they actually surpassed teams: an individual creator who had worked in four or more genres was more innovative than a team whose members had collective experience across the same number of genres. Taylor and Greve suggested that “individuals are capable of more creative integration of diverse experiences than teams are.”

The most unexpected tip, and the one I’ll be reflecting on during the next weeks (or more probably, years) was favoring short-term over long-term planning.

I’ve always considered myself someone that has (or rather “at least believes having”) a pretty much clear idea of the life I want for me in the future (even when I’ve experienced contradictory evidence of it, like getting into college hoping to graduate, just to months later decide I’d rather not).

And not just that. I’ve always considered that having clear long-term objectives was “the right” way to approach important decisions in my life.

So, why should I, instead, favor short-term planning? Because I’ll keep growing, leaving, and changing.

Maybe one of my favorite pieces of knowledge was what Dan Gilbert calls the “end of history” illusion. Which states that most people easily recognize how much their desires and motivations have changed a lot in the past, but believe they won’t change much in the future.

The most momentous personality changes occur between age eighteen and one’s late twenties, so specializing early is a task of predicting match quality for a person who does not yet exist. It could work, but it makes for worse odds. Plus, while personality change slows, it does not stop at any age. Sometimes it can actually happen instantly.

I was already familiar with some of the ideas in here.

For example, the idea of having a sampling period before narrowing focus and increasing practice, is also talked about in Algorithms to Live By: The Computer Science of Human Decisions, with the first two chapters: Optimal stopping, and Explore/Exploit.

This has been one of my favorite ideas, and one that I still try to incorporate in the way I approach life in general, not just learning.

The idea of approaching a single problem from a broad set of perspectives and points of view, is also explored in The Model Thinker: What You Need to Know to Make Data Work for You, in the chapter The Many Model Thinker; and (if I recall correctly) The Wisdom of Crowds.

This makes your final decisions more robust, and, in average, more correct.

In short, I loved the book. It reinforced my confidence on some of my life decisions, and encouraged me to keep trying new things.

[Herminia] 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.