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専門家ほど多趣味になろう!―「早期専門化=キャリアの成功」とは限らない理由(TED)

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ライフハックとしてではなく、英語学習にも極めて有用なのが、著名人が10分程度のプレゼンを行うTEDです。

TED Talksとは、あらゆる分野のエキスパートたちによるプレゼンテーションを無料で視聴できる動画配信サービスのことです。10年ほど前にサービスが開始されてから、政治、心理学、経済、日常生活などの幅広いコンテンツが視聴できることから人気を集めています。

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TEDは4000を超える膨大な数の動画があります。しかし慣れないうちは、動画の探し方や視聴のコツが分かりませんよね。この記事では、数多くのTEDを見てきた管理人(塩@saltandshio)が、心を揺さぶられたトークをあらすじと一緒にご紹介します。

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デイヴィッド・エプスタイン:「早期専門化=キャリアの成功」とは限らない理由

デイヴィッド・エプスタイン:「早期専門化=キャリアの成功」とは限らない理由

早く始めた方がキャリア達成が早いこともあります。しかし、ジャーナリストのデイヴィッド・エプスタインは、スポーツ、技術、経済等様々な例を挙げながら、早期から1つのスキルに特化することは長期的な発達を損なう可能性があると語ります。そして、数種類のことに挑戦し幅広いスキルを身につける「サンプリング期間」の効果について説明します。直感的に早期専門化を信じ込むのではなく、幅広い視野を持てば(焦らずゆっくりと)、キャリアもプライベートも充実した人生を送ることができるのです(約14分)。David Epstein / Why specializing early doesn’t always mean career success.

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「1万時間の法則」は正しいか

「1万時間の法則」という言葉をご存知でしょうか。2008年にMalcolm Gladwell(マルコム・グラッドウェル)が書籍『天才! 成功する人々の法則 (OUTLIERS:THE STORY OF SUCCESS)』にて、「物事を極めたエキスパートは練習や努力に約1万時間を費やしていた」という事例から導き出された「人は何かを習得するのに1万時間の練習が必要である」という説、主張のことです。

このように、ジャンルを問わず世界でプロになるには、年齢的に早く始める方が有利だという考えは多くの人から支持されています。その例として有名なのはタイガー・ウッズでしょう。

彼は生後7ヶ月で父親からパターを与えられました。10ヶ月ですでに父親のスイングを真似し、2才になると全国テレビに出ました。YouTubeで閲覧できます。その後、21才で世界一のゴルファーになりました。

1万時間の法則の典型的な例です

His father famously gave him a putter when he was seven months old. At 10 months, he started imitating his father’s swing. At two, you can go on YouTube and see him on national television. Fast-forward to the age of 21, he’s the greatest golfer in the world.

Quintessential 10,000 hours story.

このような、いわゆる“英才教育”は「計画的訓練」と呼ばれ、指導者のもと誤りを正しながら行う訓練で、単なる練習とは異なります。確かに、研究者たちによると多くのトップアスリートはたくさんの時間を計画的訓練にかけてきました。では、そうでない人たちは落ちこぼれなのでしょうか。

じつは、トップアスリートたちの発達の経過を追った研究によると、タイガー・ウッズのように幼少期からひとつの競技に絞って訓練をしていた人は少なく、多くのトップアスリートは異なるタイプの運動をたくさん行っていたのがわかったのです。

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多くのトップアスリートは遅咲き

異なるタイプの運動を行って幅広く汎用的なスキルを身につける期間を、科学用語では「サンプリング期間」と呼ばれます。この期間に、自分に合った興味や能力を習得していくため、「計画的訓練」と比べると時間がかかります。しかし調査の結果、多くのトップアスリートは競技を1つに絞るまでにたくさんの回り道をしていたことがわかったのです。

私はこれを知った時、こう思いました。「1万時間の法則に当てはまらないんじゃないか?」

And so when I saw that, I said, “Gosh, that doesn’t really comport with the 10,000 hours rule, does it?”

そんな疑問を感じたデイヴィッド・エプスタインは、ジャンルを変えて早期訓練と専門化が必要な分野である音楽家について、同様の調査を試みました。すると、ここでも驚きの結果がわかったのです。

世界最高レベルの音楽アカデミーの生徒を調べてみたところ、「早期」「集中」「計画的訓練」を行なった人は少なく、多くの演奏家は3つの楽器を試してから1つの楽器に絞っていたのです。じつは、冒頭で紹介した「1万時間の法則」ですが、最近では眉唾物だという意見が増えてきています。

プリンストン大学のマクナマラ准教授他のグループは「自覚的訓練」に関する88件の研究についてメタ分析を行い、「練習が技量に与える影響の大きさはスキルの分野によって異なり、スキル習得のために必要な時間は決まっていない」という、極めて真っ当な結論を出しています。

【山口周】努力は本当に報われる?「1万時間の法則」がデタラメな理由 / DIAMOND online

これは、なにもスポーツや音楽に限った話ではありません。学習の面でも、なにかに特化して勉強した生徒は、確かに成長もキャリア形成は早いのですが、選択した時期が早すぎて早々にキャリアを諦めるという人も多かったのです。

逆に、様々な科目を履修してきた生徒は、スタートこそ差がありますが、6年後にはその差は埋まり、さらにその後はキャリアが逆転していたのです。このことからわかるのは、「遅く選択した者は短期的には不利だが、長期的には有利」ということです。

趣味
多趣味な人こそ必要な人―天職が見つからない人がいるのはどうしてでしょう?(TED)【TED 紹介・解説】エミリー・ワプニック: 天職が見つからない人がいるのはどうしてでしょう?/これからの世界は、さまざまなことに関心を持ち、いろんな仕事をする人たちが求められているのです(約12分半)。そんなトークの詳細を紹介します。...
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「優しい学習環境」と「厄介な学習環境」について

タイガー・ウッズと逆の人生を歩んできたことで、例を挙げられるのはテニスプレーヤーのロジャー・フェデラーでしょう。

ロジャー・フェデラーは、スイス・バーゼル出身の元男子プロテニス選手。ATPツアーでシングルス103勝、ダブルス8勝。グランドスラム優勝回数歴代3位20勝。史上6人目のキャリア・グランドスラム達成者。ウィンブルドン最多8回優勝、全米オープン最多連覇の5連覇、マスターズ1000では歴代3位となる28回の優勝記録を持つ。世界ランキング1位最長連続記録237週。芝コートでは無類の強さを誇り、ツアー通算歴代最多111勝。

Roger Federer / Wikipediaより

彼は、6歳の頃はラグビーをしており、バスケットボール、卓球、水泳、ハンドボール、バレーボール、サッカー、バドミントン、スケートボードと、実にたくさんのスポーツを経験してからテニスをやるようになりました。母親がテニスコーチだったのですが、卓球の練習をした際にボールを素直に打ち返さなかったため、フェデラーにテニスを教えなかったのは有名なエピソードとして知られています。

専門化すれば上達するスビートが早いという、わかりやすくドラマチックな成功物語のタイガー・ウッズのほうが人には好まれるでしょう。しかし、それだけがすべてではないのです。

しかし、これが問題なのです。人間が習得したいものの中で、ゴルフはあらゆる点で最悪な例だからです。

ゴルフは、心理学者ロビン・ホガースの言う「優しい学習環境」で学びます。プロセスやゴールが明白で、明確かつ一貫したルールがあり、結果を 早く正確に得られるので予想しやすいのが特徴です。

But that, I think, is a problem, because it turns out that in many ways, golf is a uniquely horrible model of almost everything that humans want to learn.

Golf is the epitome of what the psychologist Robin Hogarth called a “kind learning environment.” Kind learning environments have next steps and goals that are clear, rules that are clear and never change, when you do something, you get feedback that is quick and accurate, work next year will look like work last year.

「優しい学習環境」の場合、繰り返しパターンの知識が基礎になるので、自動化しやすいのが特徴です。この反対が「厄介な学習環境」で、プロセスやゴールが不明瞭でルールの変更もあり得ます。結果が出るか出ないかは不明で、出たとしてもゆっくりだったり正確でなかったりします。

しかし、社会で息が長いのは「厄介な学習環境」で育った人たちです。なぜなら、様々な経験をしたことで応用がきくため、時代や仕事の変化においても順応性が高いのです。もちろん、専門性が高い分野ではそれに特化して勉強してきた人のほうが強いでしょう。しかし、そういう人は変化に対応しにくいということを忘れてはいけません。

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ベストセラーを生み出すまで、多くの人は寄り道をしている

米国特許庁が認定している優れた特許は、ひたすら技術の1分野を掘り下げた個人の成果ではなく、異なる分野から寄せ集めたチームの成果であることがこのごろは増えてきています。

また、ある研究者によるとコミックの作者がベストセラーを作り出すには、

  • 特定の分野の経験の年数
  • 出版社の資金
  • 過去のコミックの数

重要ではなく作者が関わった仕事のジャンルの数が他の人より多かったという調査結果を発表しました。

ここで興味深いのは、幅広さを持つ個人が専門家集団を凌駕していることです。幅広さを持つ人はそれほど多くは育たないでしょう。なぜなら、子供の頃からこのような人々は発達遅滞と見られ、スタートから好調、あるいは専門教育でなければ期待しないからです。

And interestingly, a broad individual could not be entirely replaced by a team of specialists. We probably don’t make as many of those people as we could because early on, they just look like they’re behind and we don’t tend to incentivize anything that doesn’t look like a head start or specialization.

このことから、スタートダッシュが早くても、長い目で人間的成長を考えると、決して効果的ではないということがわかります。

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まとめ:最短で成功することが幸せとは限らない

あたりまえですが、人と同じ数だけ成功の形は様々です。特化したことで見えてくるものがありますし、雑多なことを学んだことで知ることもあります。

または、有名な物理学者・数学者・ライターのフリーマン・ダイソンが言ったように ― 昨日 亡くなりました。敬意を表し、彼の言葉を紹介します。

―「健全な生態系を保つには鳥もカエルも必要である。カエルは泥の中にいて、細かい物が全て見える。鳥は空高く舞い上がり、細かい物は見えないが、カエルの知識を統合し、俯瞰することができる。どちらも必要だ。

問題は皆にカエルになるよう言うことなのだ」

Or as the eminent physicist and mathematician and wonderful writer, Freeman Dyson, put it — and Dyson passed away yesterday, so I hope I’m doing his words honor here —

as he said: for a healthy ecosystem, we need both birds and frogs. Frogs are down in the mud, seeing all the granular details. The birds are soaring up above not seeing those details but integrating the knowledge of the frogs. And we need both.

The problem, Dyson said, is that we’re telling everyone to become frogs.

「これしか出来ない」というよりも、「これもできる」と言える人は強いでしょう。専門性に特化した人だけが素晴らしいわけではありません。多くのキャリアを経験している事、または多趣味であることは、素晴らしい財産となって自分を助けてくれるでしょう。

英語全文

So, I’d like to talk about the development of human potential, and I’d like to start with maybe the most impactful modern story of development. Many of you here have probably heard of the 10,000 hours rule. Maybe you even model your own life after it. Basically, it’s the idea that to become great in anything, it takes 10,000 hours of focused practice, so you’d better get started as early as possible.

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The poster child for this story is Tiger Woods. His father famously gave him a putter when he was seven months old. At 10 months, he started imitating his father’s swing. At two, you can go on YouTube and see him on national television. Fast-forward to the age of 21, he’s the greatest golfer in the world. Quintessential 10,000 hours story.

Another that features in a number of bestselling books is that of the three Polgar sisters, whose father decided to teach them chess in a very technical manner from a very early age. And, really, he wanted to show that with a head start in focused practice, any child could become a genius in anything. And in fact, two of his daughters went on to become Grandmaster chess players.

So when I became the science writer at “Sports Illustrated” magazine, I got curious. If this 10,000 hours rule is correct, then we should see that elite athletes get a head start in so-called “deliberate practice.” This is coached, error-correction-focused practice, not just playing around. And in fact, when scientists study elite athletes, they see that they spend more time in deliberate practice — not a big surprise. When they actually track athletes over the course of their development, the pattern looks like this: the future elites actually spend less time early on in deliberate practice in their eventual sport. They tend to have what scientists call a “sampling period,” where they try a variety of physical activities, they gain broad, general skills, they learn about their interests and abilities and delay specializing until later than peers who plateau at lower levels.

And so when I saw that, I said, “Gosh, that doesn’t really comport with the 10,000 hours rule, does it?” So I started to wonder about other domains that we associate with obligatory, early specialization, like music. Turns out the pattern’s often similar.

This is research from a world-class music academy, and what I want to draw your attention to is this: the exceptional musicians didn’t start spending more time in deliberate practice than the average musicians until their third instrument. They, too, tended to have a sampling period, even musicians we think of as famously precocious, like Yo-Yo Ma. He had a sampling period, he just went through it more rapidly than most musicians do.

Nonetheless, this research is almost entirely ignored, and much more impactful is the first page of the book “Battle Hymn of the Tiger Mother,” where the author recounts assigning her daughter violin. Nobody seems to remember the part later in the book where her daughter turns to her and says, “You picked it, not me,” and largely quits.

So having seen this sort of surprising pattern in sports and music, I started to wonder about domains that affect even more people, like education. An economist found a natural experiment in the higher-ed systems of England and Scotland. In the period he studied, the systems were very similar, except in England, students had to specialize in their mid-teen years to pick a specific course of study to apply to, whereas in Scotland, they could keep trying things in the university if they wanted to. And his question was: Who wins the trade-off, the early or the late specializers? And what he saw was that the early specializers jump out to an income lead because they have more domain-specific skills. The late specializers get to try more different things, and when they do pick, they have better fit, or what economists call “match quality.” And so their growth rates are faster. By six years out, they erase that income gap. Meanwhile, the early specializers start quitting their career tracks in much higher numbers, essentially because they were made to choose so early that they more often made poor choices. So the late specializers lose in the short term and win in the long run. I think if we thought about career choice like dating, we might not pressure people to settle down quite so quickly.

So this got me interested, seeing this pattern again, in exploring the developmental backgrounds of people whose work I had long admired, like Duke Ellington, who shunned music lessons as a kid to focus on baseball and painting and drawing. Or Maryam Mirzakhani, who wasn’t interested in math as a girl — dreamed of becoming a novelist — and went on to become the first and so far only woman to win the Fields Medal, the most prestigious prize in the world in math. Or Vincent Van Gogh had five different careers, each of which he deemed his true calling before flaming out spectacularly, and in his late 20s, picked up a book called “The Guide to the ABCs of Drawing.” That worked out OK. Claude Shannon was an electrical engineer at the University of Michigan who took a philosophy course just to fulfill a requirement, and in it, he learned about a near-century-old system of logic by which true and false statements could be coded as ones and zeros and solved like math problems. This led to the development of binary code, which underlies all of our digital computers today.

Finally, my own sort of role model, Frances Hesselbein — this is me with her — she took her first professional job at the age of 54 and went on to become the CEO of the Girl Scouts, which she saved. She tripled minority membership, added 130,000 volunteers, and this is one of the proficiency badges that came out of her tenure — it’s binary code for girls learning about computers. Today, Frances runs a leadership institute where she works every weekday, in Manhattan. And she’s only 104, so who knows what’s next.

We never really hear developmental stories like this, do we? We don’t hear about the research that found that Nobel laureate scientists are 22 times more likely to have a hobby outside of work as are typical scientists. We never hear that. Even when the performers or the work is very famous, we don’t hear these developmental stories.

For example, here’s an athlete I’ve followed. Here he is at age six, wearing a Scottish rugby kit. He tried some tennis, some skiing, wrestling. His mother was actually a tennis coach but she declined to coach him because he wouldn’t return balls normally. He did some basketball, table tennis, swimming. When his coaches wanted to move him up a level to play with older boys, he declined, because he just wanted to talk about pro wrestling after practice with his friends. And he kept trying more sports: handball, volleyball, soccer, badminton, skateboarding … So, who is this dabbler? This is Roger Federer. Every bit as famous as an adult as Tiger Woods, and yet even tennis enthusiasts don’t usually know anything about his developmental story. Why is that, even though it’s the norm?

I think it’s partly because the Tiger story is very dramatic, but also because it seems like this tidy narrative that we can extrapolate to anything that we want to be good at in our own lives. But that, I think, is a problem, because it turns out that in many ways, golf is a uniquely horrible model of almost everything that humans want to learn.

Golf is the epitome of what the psychologist Robin Hogarth called a “kind learning environment.” Kind learning environments have next steps and goals that are clear, rules that are clear and never change, when you do something, you get feedback that is quick and accurate, work next year will look like work last year. Chess: also a kind learning environment. The grand master’s advantage is largely based on knowledge of recurring patterns, which is also why it’s so easy to automate. On the other end of the spectrum are “wicked learning environments,” where next steps and goals may not be clear. Rules may change. You may or may not get feedback when you do something. It may be delayed, it may be inaccurate, and work next year may not look like work last year.

So which one of these sounds like the world we’re increasingly living in? In fact, our need to think in an adaptable manner and to keep track of interconnecting parts has fundamentally changed our perception, so that when you look at this diagram, the central circle on the right probably looks larger to you because your brain is drawn to the relationship of the parts in the whole, whereas someone who hasn’t been exposed to modern work with its requirement for adaptable, conceptual thought, will see correctly that the central circles are the same size.

So here we are in the wicked work world, and there, sometimes hyperspecialization can backfire badly. For example, in research in a dozen countries that matched people for their parents’ years of education, their test scores, their own years of education, the difference was some got career-focused education and some got broader, general education. The pattern was those who got the career-focused education are more likely to be hired right out of training, more likely to make more money right away, but so much less adaptable in a changing work world that they spend so much less time in the workforce overall that they win in the short term and lose in the long run.

Or consider a famous, 20-year study of experts making geopolitical and economic predictions. The worst forecasters were the most specialized experts, those who’d spent their entire careers studying one or two problems and came to see the whole world through one lens or mental model. Some of them actually got worse as they accumulated experience and credentials. The best forecasters were simply bright people with wide-ranging interests.

Now in some domains, like medicine, increasing specialization has been both inevitable and beneficial, no question about it. And yet, it’s been a double-edged sword. A few years ago, one of the most popular surgeries in the world for knee pain was tested in a placebo-controlled trial. Some of the patients got “sham surgery.” That means the surgeons make an incision, they bang around like they’re doing something, then they sew the patient back up. That performed just as a well. And yet surgeons who specialize in the procedure continue to do it by the millions.

So if hyperspecialization isn’t always the trick in a wicked world, what is? That can be difficult to talk about, because it doesn’t always look like this path. Sometimes it looks like meandering or zigzagging or keeping a broader view. It can look like getting behind. But I want to talk about what some of those tricks might be. If we look at research on technological innovation, it shows that increasingly, the most impactful patents are not authored by individuals who drill deeper, deeper, deeper into one area of technology as classified by the US Patent Office, but rather by teams that include individuals who have worked across a large number of different technology classes and often merge things from different domains.

Someone whose work I’ve admired who was sort of on the forefront of this is a Japanese man named Gunpei Yokoi. Yokoi didn’t score well on his electronics exams at school, so he had to settle for a low-tier job as a machine maintenance worker at a playing card company in Kyoto. He realized he wasn’t equipped to work on the cutting edge, but that there was so much information easily available that maybe he could combine things that were already well-known in ways that specialists were too narrow to see. So he combined some well-known technology from the calculator industry with some well-known technology from the credit card industry and made handheld games. And they were a hit. And it turned this playing card company, which was founded in a wooden storefront in the 19th century, into a toy and game operation. You may have heard of it; it’s called Nintendo.

Yokoi’s creative philosophy translated to “lateral thinking with withered technology,” taking well-known technology and using it in new ways. And his magnum opus was this: the Game Boy. Technological joke in every way. And it came out at the same time as color competitors from Saga and Atari, and it blew them away, because Yokoi knew what his customers cared about wasn’t color. It was durability, portability, affordability, battery life, game selection. This is mine that I found in my parents’ basement.

It’s seen better days. But you can see the red light is on. I flipped it on and played some Tetris, which I thought was especially impressive because the batteries had expired in 2007 and 2013.

So this breadth advantage holds in more subjective realms as well. In a fascinating study of what leads some comic book creators to be more likely to make blockbuster comics, a pair of researchers found that it was neither the number of years of experience in the field nor the resources of the publisher nor the number of previous comics made. It was the number of different genres that a creator had worked across. And interestingly, a broad individual could not be entirely replaced by a team of specialists. We probably don’t make as many of those people as we could because early on, they just look like they’re behind and we don’t tend to incentivize anything that doesn’t look like a head start or specialization. In fact, I think in the well-meaning drive for a head start, we often even counterproductively short-circuit even the way we learn new material, at a fundamental level.

In a study last year, seventh-grade math classrooms in the US were randomly assigned to different types of learning. Some got what’s called “blocked practice.” That’s like, you get problem type A, AAAAA, BBBBB, and so on. Progress is fast, kids are happy, everything’s great. Other classrooms got assigned to what’s called “interleaved practice.” That’s like if you took all the problem types and threw them in a hat and drew them out at random. Progress is slower, kids are more frustrated. But instead of learning how to execute procedures, they’re learning how to match a strategy to a type of problem. And when the test comes around, the interleaved group blew the block practice group away. It wasn’t even close.

Now, I found a lot of this research deeply counterintuitive, the idea that a head start, whether in picking a career or a course of study or just in learning new material, can sometimes undermine long-term development. And naturally, I think there are as many ways to succeed as there are people. But I think we tend only to incentivize and encourage the Tiger path, when increasingly, in a wicked world, we need people who travel the Roger path as well. Or as the eminent physicist and mathematician and wonderful writer, Freeman Dyson, put it — and Dyson passed away yesterday, so I hope I’m doing his words honor here — as he said: for a healthy ecosystem, we need both birds and frogs. Frogs are down in the mud, seeing all the granular details. The birds are soaring up above not seeing those details but integrating the knowledge of the frogs. And we need both. The problem, Dyson said, is that we’re telling everyone to become frogs. And I think, in a wicked world, that’s increasingly shortsighted.

Thank you very much.

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TEDまとめ(1):エキスパートたちが贈る極上のメッセージ ライフハックとしてではなく、英語学習にも極めて有用なのが、著名人が10分程度のプレゼンを行うTEDです。 TED Talksと...