Range: Why Generalists Triumph in a Specialized World 4/5

David Epstein

Parts 1, 2, 3.

7/ Flirting with Your Possible Selves

  • Personalities change over time; adults are more agreeable, conscientious, emotionally stable and less neurotic, but less open to experience. Adults are more consistent, less curious [MK: that’s why I’m forcing myself to learn every day], open-minded, inventive or violent.

  • Please throw the marshmallow test out of the window! It’s completely useless and pointless.

  • [MK: Here’s a direct link to Herminia Ibarra’s book I’ve summarized, make sure you read it.] The core point is that testing and learning has to precede creating a better picture of oneself.

  • Sorry, this chapter was filled with lots of examples and little content.

8/ The Outsider Advantage

  • Established companies tend to approach problems with a local view, involving people from the same domain and applying tried-and-true approaches. Proper problems are framed in a way to welcome people from other domains to participate.

  • It’s intuitive (and wrong) to believe that only insiders who are deeply engaged can find the solutions to complex problems; however, outsiders may be better equipped with their different ways of thinking.

  • [MK: I hate the term “thinking outside the box” with a passion as it’s a cliché of cliches.]

  • There’s no magic and definitely no insult towards the professionals; as shown in the previous chapters, an outside view is just the means to dig under the obvious surface to uncover the ways things work and apply experience from another domain where there are similar ways things work.

  • It should also be noted that all this glory of outside thinking is relevant for novel problems where the existing solutions don’t work. Well-defined (i.e. “kind”) problems most of the time don’t need outside involvement other than maybe by accident.

  • One can argue [MK: and I’ve made this point before] that being an outsider, i.e. offering a diverse experience, is a necessity for properly functioning Boards. Indeed, there has to be an experience to build on (it’s a given), but an outside perspective in high-stake games is worth its weight in gold. Or Bitcoin, whatever you prefer.

  • Dilettantes (i.e. non-professionals) are in a better position (overall) to merge the strands of publicly available but disparate information. Maybe it’s a numbers game, or maybe it’s just a fresh point of view, but funnily enough, the deeper the specialization – the higher the impact an outsider can make.

9/ Lateral Thinking with Withered Technology

  • If people say “Oh, this is a great idea”, you’re not the first one to have come up with it.

  • Interesting terms: a “T person” is one who has breadth and depth; an “I person” is one who’s only deep.

  • A high-repetition workload negatively impacts performance, so the length of experience is a liability, not an asset.

10/ Fooled by Expertise

  • The higher “experts” think about the quality of their predictions, the poorer their predictions really are. [MK: It’s an anecdotal case, but all of us have seen instances of this in any trade: VC investment, business case analysis, predicting product-market fit, etc.).

  • Integrating disparate bits of information coming from “experts” (inevitably passing it through one’s own lens), trying to get the possibly compatible parts of incompatible opinions and positions may have the best predicting power compared to any individual forecasts, however prized their authors are.

  • Strangely enough, experts are the worst at predicting the long-term picture of the world in their own domain. The explanation is obvious: no domain exists in isolation, and there are always disruptive factors present that make forecasting and planning meaningless.

  • This observation is anecdotal to the book, but a bunch of smart generalists can beat a bunch of smart specialists in the specialists’ field of expertise, provided the challenge is not codified (i.e. NOT “kind”) and the forecast is needed.

  • The book makes another example of a semi-generalist (a fraud researcher) using specialists for information, but not the interpretation. [MK: I’m trying to project this to a, say, GP trying to read MRI images and ignoring the, say, gastroenterologist’s opinion on these images. The trust in specialization is too ingrained into me, I’d pick the specialist’s opinion any time of the day.]

  • Active open-mindedness is when people are making predictions as hypotheses and are trying to verify them using the devil’s advocate method [MK: sounds a bit too good to be true, as intellectual honesty is quite rare. This means (in this instance) that most people would try not to verify the hypothesis, but to prove it, especially if the stakes are high]. But a really productive approach is trying to make others prove that the idea won’t work (or google the opposite examples). It’s goes straight up against the Silicon Valley culture, but Russians would feel at home with this approach. Maybe, just maybe, this is one of the 100 reasons why the Silicon Valley is in the US and not Russia.

  • Just found out a good term: a specialist is looking for simplicity behind complexity and a generalist is looking for a complexity behind simplicity. Feel free to attribute this sentence to me :)

  • Specialists are better than generalists in picking facts proving their theories. It’s not a question of intellectual honesty, but rather of convenience.

  • It’s presented in the book in an anecdotal way, but I’ve seen this left and right: many specialists tend to ignore the negative feedback from their predictions (i.e. which didn’t work); generalists tend to review their assumptions much earlier after the mistake.

Part 5.