[Script Info]
Title: 
[Events]
Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text
Dialogue: 0,0:00:01.69,0:00:04.61,Default,,0000,0000,0000,,So, I'd like to talk about\Nthe development of human potential,
Dialogue: 0,0:00:04.63,0:00:09.72,Default,,0000,0000,0000,,and I'd like to start with maybe the most\Nimpactful modern story of development.
Dialogue: 0,0:00:09.75,0:00:13.53,Default,,0000,0000,0000,,Many of you here have probably heard\Nof the 10,000 hours rule.
Dialogue: 0,0:00:13.55,0:00:15.66,Default,,0000,0000,0000,,Maybe you even model\Nyour own life after it.
Dialogue: 0,0:00:15.68,0:00:18.43,Default,,0000,0000,0000,,Basically, it's the idea\Nthat to become great in anything,
Dialogue: 0,0:00:18.46,0:00:21.39,Default,,0000,0000,0000,,it takes 10,000 hours\Nof focused practice,
Dialogue: 0,0:00:21.42,0:00:23.77,Default,,0000,0000,0000,,so you'd better get started\Nas early as possible.
Dialogue: 0,0:00:23.80,0:00:27.71,Default,,0000,0000,0000,,The poster child for this story\Nis Tiger Woods.
Dialogue: 0,0:00:27.74,0:00:30.100,Default,,0000,0000,0000,,His father famously gave him a putter\Nwhen he was seven months old.
Dialogue: 0,0:00:31.41,0:00:34.51,Default,,0000,0000,0000,,At 10 months, he started imitating\Nhis father's swing.
Dialogue: 0,0:00:34.97,0:00:38.44,Default,,0000,0000,0000,,At two, you can go on YouTube\Nand see him on national television.
Dialogue: 0,0:00:38.47,0:00:40.12,Default,,0000,0000,0000,,Fast-forward to the age of 21,
Dialogue: 0,0:00:40.15,0:00:42.01,Default,,0000,0000,0000,,he's the greatest golfer in the world.
Dialogue: 0,0:00:42.03,0:00:43.68,Default,,0000,0000,0000,,Quintessential 10,000 hours story.
Dialogue: 0,0:00:43.71,0:00:46.26,Default,,0000,0000,0000,,Another that features\Nin a number of bestselling books
Dialogue: 0,0:00:46.28,0:00:48.06,Default,,0000,0000,0000,,is that of the three Polgar sisters,
Dialogue: 0,0:00:48.08,0:00:51.29,Default,,0000,0000,0000,,whose father decided to teach them chess\Nin a very technical manner
Dialogue: 0,0:00:51.31,0:00:52.47,Default,,0000,0000,0000,,from a very early age.
Dialogue: 0,0:00:52.49,0:00:53.95,Default,,0000,0000,0000,,And, really, he wanted to show
Dialogue: 0,0:00:53.98,0:00:55.100,Default,,0000,0000,0000,,that with a head start\Nin focused practice,
Dialogue: 0,0:00:56.02,0:00:58.44,Default,,0000,0000,0000,,any child could become\Na genius in anything.
Dialogue: 0,0:00:58.46,0:00:59.64,Default,,0000,0000,0000,,And in fact,
Dialogue: 0,0:00:59.66,0:01:02.81,Default,,0000,0000,0000,,two of his daughters went on to become\NGrandmaster chess players.
Dialogue: 0,0:01:02.84,0:01:06.09,Default,,0000,0000,0000,,So when I became the science writer\Nat "Sports Illustrated" magazine,
Dialogue: 0,0:01:06.11,0:01:07.27,Default,,0000,0000,0000,,I got curious.
Dialogue: 0,0:01:07.29,0:01:09.24,Default,,0000,0000,0000,,If this 10,000 hours rule is correct,
Dialogue: 0,0:01:09.26,0:01:11.86,Default,,0000,0000,0000,,then we should see\Nthat elite athletes get a head start
Dialogue: 0,0:01:11.88,0:01:13.63,Default,,0000,0000,0000,,in so-called "deliberate practice."
Dialogue: 0,0:01:13.66,0:01:16.40,Default,,0000,0000,0000,,This is coached,\Nerror-correction-focused practice,
Dialogue: 0,0:01:16.42,0:01:17.91,Default,,0000,0000,0000,,not just playing around.
Dialogue: 0,0:01:17.93,0:01:20.29,Default,,0000,0000,0000,,And in fact, when scientists\Nstudy elite athletes,
Dialogue: 0,0:01:20.31,0:01:23.16,Default,,0000,0000,0000,,they see that they spend more time\Nin deliberate practice --
Dialogue: 0,0:01:23.18,0:01:24.34,Default,,0000,0000,0000,,not a big surprise.
Dialogue: 0,0:01:24.36,0:01:27.76,Default,,0000,0000,0000,,When they actually track athletes\Nover the course of their development,
Dialogue: 0,0:01:27.78,0:01:29.12,Default,,0000,0000,0000,,the pattern looks like this:
Dialogue: 0,0:01:29.14,0:01:31.78,Default,,0000,0000,0000,,the future elites actually spend\Nless time early on
Dialogue: 0,0:01:31.80,0:01:34.56,Default,,0000,0000,0000,,in deliberate practice\Nin their eventual sport.
Dialogue: 0,0:01:34.59,0:01:37.88,Default,,0000,0000,0000,,They tend to have what scientists\Ncall a "sampling period,"
Dialogue: 0,0:01:37.91,0:01:40.16,Default,,0000,0000,0000,,where they try a variety\Nof physical activities,
Dialogue: 0,0:01:40.19,0:01:42.02,Default,,0000,0000,0000,,they gain broad, general skills,
Dialogue: 0,0:01:42.04,0:01:44.20,Default,,0000,0000,0000,,they learn about\Ntheir interests and abilities
Dialogue: 0,0:01:44.22,0:01:48.18,Default,,0000,0000,0000,,and delay specializing until later\Nthan peers who plateau at lower levels.
Dialogue: 0,0:01:48.85,0:01:50.98,Default,,0000,0000,0000,,And so when I saw that, I said,
Dialogue: 0,0:01:51.00,0:01:54.44,Default,,0000,0000,0000,,"Gosh, that doesn't really comport\Nwith the 10,000 hours rule, does it?"
Dialogue: 0,0:01:54.46,0:01:56.47,Default,,0000,0000,0000,,So I started to wonder about other domains
Dialogue: 0,0:01:56.50,0:01:59.63,Default,,0000,0000,0000,,that we associate with obligatory,\Nearly specialization,
Dialogue: 0,0:01:59.65,0:02:00.96,Default,,0000,0000,0000,,like music.
Dialogue: 0,0:02:00.99,0:02:02.84,Default,,0000,0000,0000,,Turns out the pattern's often similar.
Dialogue: 0,0:02:02.86,0:02:05.28,Default,,0000,0000,0000,,This is research\Nfrom a world-class music academy,
Dialogue: 0,0:02:05.30,0:02:07.67,Default,,0000,0000,0000,,and what I want to draw\Nyour attention to is this:
Dialogue: 0,0:02:07.69,0:02:11.51,Default,,0000,0000,0000,,the exceptional musicians didn't start\Nspending more time in deliberate practice
Dialogue: 0,0:02:11.53,0:02:12.77,Default,,0000,0000,0000,,than the average musicians
Dialogue: 0,0:02:12.80,0:02:14.19,Default,,0000,0000,0000,,until their third instrument.
Dialogue: 0,0:02:14.21,0:02:16.29,Default,,0000,0000,0000,,They, too, tended to have\Na sampling period,
Dialogue: 0,0:02:16.31,0:02:18.73,Default,,0000,0000,0000,,even musicians we think of\Nas famously precocious,
Dialogue: 0,0:02:18.75,0:02:19.96,Default,,0000,0000,0000,,like Yo-Yo Ma.
Dialogue: 0,0:02:19.98,0:02:21.23,Default,,0000,0000,0000,,He had a sampling period,
Dialogue: 0,0:02:21.25,0:02:24.08,Default,,0000,0000,0000,,he just went through it more rapidly\Nthan most musicians do.
Dialogue: 0,0:02:24.11,0:02:27.30,Default,,0000,0000,0000,,Nonetheless, this research\Nis almost entirely ignored,
Dialogue: 0,0:02:27.32,0:02:28.65,Default,,0000,0000,0000,,and much more impactful
Dialogue: 0,0:02:28.67,0:02:31.72,Default,,0000,0000,0000,,is the first page of the book\N"Battle Hymn of the Tiger Mother,"
Dialogue: 0,0:02:31.74,0:02:34.84,Default,,0000,0000,0000,,where the author recounts\Nassigning her daughter violin.
Dialogue: 0,0:02:34.86,0:02:37.32,Default,,0000,0000,0000,,Nobody seems to remember\Nthe part later in the book
Dialogue: 0,0:02:37.34,0:02:40.47,Default,,0000,0000,0000,,where her daughter turns to her\Nand says, "You picked it, not me,"
Dialogue: 0,0:02:40.49,0:02:41.64,Default,,0000,0000,0000,,and largely quits.
Dialogue: 0,0:02:41.66,0:02:44.82,Default,,0000,0000,0000,,So having seen this sort of surprising\Npattern in sports and music,
Dialogue: 0,0:02:44.84,0:02:47.83,Default,,0000,0000,0000,,I started to wonder about domains\Nthat affect even more people,
Dialogue: 0,0:02:47.86,0:02:49.01,Default,,0000,0000,0000,,like education.
Dialogue: 0,0:02:49.04,0:02:50.92,Default,,0000,0000,0000,,An economist found a natural experiment
Dialogue: 0,0:02:50.94,0:02:53.24,Default,,0000,0000,0000,,in the higher-ed systems\Nof England and Scotland.
Dialogue: 0,0:02:53.26,0:02:55.92,Default,,0000,0000,0000,,In the period he studied,\Nthe systems were very similar,
Dialogue: 0,0:02:55.94,0:02:59.19,Default,,0000,0000,0000,,except in England, students had\Nto specialize in their mid-teen years
Dialogue: 0,0:02:59.22,0:03:01.42,Default,,0000,0000,0000,,to pick a specific course\Nof study to apply to,
Dialogue: 0,0:03:01.45,0:03:04.68,Default,,0000,0000,0000,,whereas in Scotland, they could\Nkeep trying things in the university
Dialogue: 0,0:03:04.70,0:03:05.85,Default,,0000,0000,0000,,if they wanted to.
Dialogue: 0,0:03:05.88,0:03:07.03,Default,,0000,0000,0000,,And his question was:
Dialogue: 0,0:03:07.05,0:03:09.83,Default,,0000,0000,0000,,Who wins the trade-off,\Nthe early or the late specializers?
Dialogue: 0,0:03:09.86,0:03:13.35,Default,,0000,0000,0000,,And what he saw was that the early\Nspecializers jump out to an income lead
Dialogue: 0,0:03:13.38,0:03:15.54,Default,,0000,0000,0000,,because they have more\Ndomain-specific skills.
Dialogue: 0,0:03:15.56,0:03:18.16,Default,,0000,0000,0000,,The late specializers get to try\Nmore different things,
Dialogue: 0,0:03:18.19,0:03:20.25,Default,,0000,0000,0000,,and when they do pick,\Nthey have better fit,
Dialogue: 0,0:03:20.28,0:03:22.23,Default,,0000,0000,0000,,or what economists call "match quality."
Dialogue: 0,0:03:22.25,0:03:24.91,Default,,0000,0000,0000,,And so their growth rates are faster.
Dialogue: 0,0:03:24.93,0:03:26.09,Default,,0000,0000,0000,,By six years out,
Dialogue: 0,0:03:26.11,0:03:27.75,Default,,0000,0000,0000,,they erase that income gap.
Dialogue: 0,0:03:27.77,0:03:30.97,Default,,0000,0000,0000,,Meanwhile, the early specializers\Nstart quitting their career tracks
Dialogue: 0,0:03:30.100,0:03:32.16,Default,,0000,0000,0000,,in much higher numbers,
Dialogue: 0,0:03:32.18,0:03:34.69,Default,,0000,0000,0000,,essentially because they were\Nmade to choose so early
Dialogue: 0,0:03:34.72,0:03:36.60,Default,,0000,0000,0000,,that they more often made poor choices.
Dialogue: 0,0:03:36.63,0:03:38.84,Default,,0000,0000,0000,,So the late specializers\Nlose in the short term
Dialogue: 0,0:03:38.86,0:03:40.02,Default,,0000,0000,0000,,and win in the long run.
Dialogue: 0,0:03:40.04,0:03:42.62,Default,,0000,0000,0000,,I think if we thought about\Ncareer choice like dating,
Dialogue: 0,0:03:42.64,0:03:45.51,Default,,0000,0000,0000,,we might not pressure people\Nto settle down quite so quickly.
Dialogue: 0,0:03:45.54,0:03:48.03,Default,,0000,0000,0000,,So this got me interested,\Nseeing this pattern again,
Dialogue: 0,0:03:48.05,0:03:52.00,Default,,0000,0000,0000,,in exploring the developmental backgrounds\Nof people whose work I had long admired,
Dialogue: 0,0:03:52.03,0:03:54.62,Default,,0000,0000,0000,,like Duke Ellington, who shunned\Nmusic lessons as a kid
Dialogue: 0,0:03:54.64,0:03:56.83,Default,,0000,0000,0000,,to focus on baseball\Nand painting and drawing.
Dialogue: 0,0:03:56.86,0:03:59.91,Default,,0000,0000,0000,,Or Maryam Mirzakhani, who wasn't\Ninterested in math as a girl --
Dialogue: 0,0:03:59.94,0:04:01.52,Default,,0000,0000,0000,,dreamed of becoming a novelist --
Dialogue: 0,0:04:01.55,0:04:04.06,Default,,0000,0000,0000,,and went on to become\Nthe first and so far only woman
Dialogue: 0,0:04:04.08,0:04:05.24,Default,,0000,0000,0000,,to win the Fields Medal,
Dialogue: 0,0:04:05.26,0:04:07.54,Default,,0000,0000,0000,,the most prestigious prize\Nin the world in math.
Dialogue: 0,0:04:07.56,0:04:09.77,Default,,0000,0000,0000,,Or Vincent Van Gogh\Nhad five different careers,
Dialogue: 0,0:04:09.80,0:04:13.31,Default,,0000,0000,0000,,each of which he deemed his true calling\Nbefore flaming out spectacularly,
Dialogue: 0,0:04:13.34,0:04:17.54,Default,,0000,0000,0000,,and in his late 20s, picked up a book\Ncalled "The Guide to the ABCs of Drawing."
Dialogue: 0,0:04:18.07,0:04:19.39,Default,,0000,0000,0000,,That worked out OK.
Dialogue: 0,0:04:19.87,0:04:23.28,Default,,0000,0000,0000,,Claude Shannon was an electrical engineer\Nat the University of Michigan
Dialogue: 0,0:04:23.31,0:04:26.29,Default,,0000,0000,0000,,who took a philosophy course\Njust to fulfill a requirement,
Dialogue: 0,0:04:26.31,0:04:29.50,Default,,0000,0000,0000,,and in it, he learned about\Na near-century-old system of logic
Dialogue: 0,0:04:29.53,0:04:32.74,Default,,0000,0000,0000,,by which true and false statements\Ncould be coded as ones and zeros
Dialogue: 0,0:04:32.76,0:04:34.69,Default,,0000,0000,0000,,and solved like math problems.
Dialogue: 0,0:04:34.71,0:04:37.04,Default,,0000,0000,0000,,This led to the development\Nof binary code,
Dialogue: 0,0:04:37.06,0:04:40.14,Default,,0000,0000,0000,,which underlies all\Nof our digital computers today.
Dialogue: 0,0:04:40.16,0:04:42.87,Default,,0000,0000,0000,,Finally, my own sort of role model,\NFrances Hesselbein --
Dialogue: 0,0:04:42.89,0:04:44.14,Default,,0000,0000,0000,,this is me with her --
Dialogue: 0,0:04:44.16,0:04:47.32,Default,,0000,0000,0000,,she took her first professional\Njob at the age of 54
Dialogue: 0,0:04:47.34,0:04:49.65,Default,,0000,0000,0000,,and went on to become\Nthe CEO of the Girl Scouts,
Dialogue: 0,0:04:49.67,0:04:50.85,Default,,0000,0000,0000,,which she saved.
Dialogue: 0,0:04:50.87,0:04:52.61,Default,,0000,0000,0000,,She tripled minority membership,
Dialogue: 0,0:04:52.64,0:04:55.40,Default,,0000,0000,0000,,added 130,000 volunteers,
Dialogue: 0,0:04:55.42,0:04:58.84,Default,,0000,0000,0000,,and this is one of the proficiency badges\Nthat came out of her tenure --
Dialogue: 0,0:04:58.86,0:05:01.53,Default,,0000,0000,0000,,it's binary code for girls\Nlearning about computers.
Dialogue: 0,0:05:01.56,0:05:03.63,Default,,0000,0000,0000,,Today, Frances runs a leadership institute
Dialogue: 0,0:05:03.65,0:05:05.86,Default,,0000,0000,0000,,where she works\Nevery weekday, in Manhattan.
Dialogue: 0,0:05:05.88,0:05:07.40,Default,,0000,0000,0000,,And she's only 104,
Dialogue: 0,0:05:07.42,0:05:08.94,Default,,0000,0000,0000,,so who knows what's next.
Dialogue: 0,0:05:08.96,0:05:10.11,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:05:10.74,0:05:13.59,Default,,0000,0000,0000,,We never really hear developmental\Nstories like this, do we?
Dialogue: 0,0:05:13.62,0:05:15.17,Default,,0000,0000,0000,,We don't hear about the research
Dialogue: 0,0:05:15.19,0:05:18.31,Default,,0000,0000,0000,,that found that Nobel laureate scientists\Nare 22 times more likely
Dialogue: 0,0:05:18.34,0:05:19.82,Default,,0000,0000,0000,,to have a hobby outside of work
Dialogue: 0,0:05:19.84,0:05:21.09,Default,,0000,0000,0000,,as are typical scientists.
Dialogue: 0,0:05:21.11,0:05:22.27,Default,,0000,0000,0000,,We never hear that.
Dialogue: 0,0:05:22.29,0:05:24.74,Default,,0000,0000,0000,,Even when the performers\Nor the work is very famous,
Dialogue: 0,0:05:24.76,0:05:26.72,Default,,0000,0000,0000,,we don't hear these\Ndevelopmental stories.
Dialogue: 0,0:05:26.75,0:05:28.88,Default,,0000,0000,0000,,For example, here's\Nan athlete I've followed.
Dialogue: 0,0:05:28.90,0:05:31.36,Default,,0000,0000,0000,,Here he is at age six,\Nwearing a Scottish rugby kit.
Dialogue: 0,0:05:31.39,0:05:33.59,Default,,0000,0000,0000,,He tried some tennis,\Nsome skiing, wrestling.
Dialogue: 0,0:05:33.62,0:05:36.83,Default,,0000,0000,0000,,His mother was actually a tennis coach\Nbut she declined to coach him
Dialogue: 0,0:05:36.86,0:05:39.05,Default,,0000,0000,0000,,because he wouldn't return balls normally.
Dialogue: 0,0:05:39.08,0:05:41.30,Default,,0000,0000,0000,,He did some basketball,\Ntable tennis, swimming.
Dialogue: 0,0:05:41.33,0:05:43.50,Default,,0000,0000,0000,,When his coaches wanted\Nto move him up a level
Dialogue: 0,0:05:43.52,0:05:44.67,Default,,0000,0000,0000,,to play with older boys,
Dialogue: 0,0:05:44.70,0:05:47.67,Default,,0000,0000,0000,,he declined, because he just wanted\Nto talk about pro wrestling
Dialogue: 0,0:05:47.70,0:05:49.23,Default,,0000,0000,0000,,after practice with his friends.
Dialogue: 0,0:05:49.26,0:05:50.75,Default,,0000,0000,0000,,And he kept trying more sports:
Dialogue: 0,0:05:50.78,0:05:53.76,Default,,0000,0000,0000,,handball, volleyball, soccer,\Nbadminton, skateboarding ...
Dialogue: 0,0:05:53.79,0:05:56.01,Default,,0000,0000,0000,,So, who is this dabbler?
Dialogue: 0,0:05:56.67,0:05:58.53,Default,,0000,0000,0000,,This is Roger Federer.
Dialogue: 0,0:05:58.55,0:06:01.75,Default,,0000,0000,0000,,Every bit as famous\Nas an adult as Tiger Woods,
Dialogue: 0,0:06:01.78,0:06:05.06,Default,,0000,0000,0000,,and yet even tennis enthusiasts\Ndon't usually know anything
Dialogue: 0,0:06:05.08,0:06:06.60,Default,,0000,0000,0000,,about his developmental story.
Dialogue: 0,0:06:06.62,0:06:09.22,Default,,0000,0000,0000,,Why is that, even though it's the norm?
Dialogue: 0,0:06:09.24,0:06:12.42,Default,,0000,0000,0000,,I think it's partly because\Nthe Tiger story is very dramatic,
Dialogue: 0,0:06:12.45,0:06:14.84,Default,,0000,0000,0000,,but also because it seems like\Nthis tidy narrative
Dialogue: 0,0:06:14.86,0:06:17.86,Default,,0000,0000,0000,,that we can extrapolate to anything\Nthat we want to be good at
Dialogue: 0,0:06:17.88,0:06:19.24,Default,,0000,0000,0000,,in our own lives.
Dialogue: 0,0:06:19.26,0:06:20.86,Default,,0000,0000,0000,,But that, I think, is a problem,
Dialogue: 0,0:06:20.88,0:06:24.42,Default,,0000,0000,0000,,because it turns out that in many ways,\Ngolf is a uniquely horrible model
Dialogue: 0,0:06:24.44,0:06:26.70,Default,,0000,0000,0000,,of almost everything\Nthat humans want to learn.
Dialogue: 0,0:06:26.72,0:06:28.05,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:06:28.07,0:06:29.24,Default,,0000,0000,0000,,Golf is the epitome of
Dialogue: 0,0:06:29.26,0:06:32.73,Default,,0000,0000,0000,,what the psychologist Robin Hogarth\Ncalled a "kind learning environment."
Dialogue: 0,0:06:32.76,0:06:35.96,Default,,0000,0000,0000,,Kind learning environments\Nhave next steps and goals that are clear,
Dialogue: 0,0:06:35.99,0:06:37.84,Default,,0000,0000,0000,,rules that are clear and never change,
Dialogue: 0,0:06:37.86,0:06:41.12,Default,,0000,0000,0000,,when you do something, you get feedback\Nthat is quick and accurate,
Dialogue: 0,0:06:41.14,0:06:43.34,Default,,0000,0000,0000,,work next year will look like\Nwork last year.
Dialogue: 0,0:06:43.36,0:06:45.80,Default,,0000,0000,0000,,Chess: also a kind learning environment.
Dialogue: 0,0:06:45.82,0:06:47.20,Default,,0000,0000,0000,,The grand master's advantage
Dialogue: 0,0:06:47.23,0:06:49.69,Default,,0000,0000,0000,,is largely based on\Nknowledge of recurring patterns,
Dialogue: 0,0:06:49.72,0:06:51.76,Default,,0000,0000,0000,,which is also why\Nit's so easy to automate.
Dialogue: 0,0:06:51.79,0:06:55.03,Default,,0000,0000,0000,,On the other end of the spectrum\Nare "wicked learning environments,"
Dialogue: 0,0:06:55.06,0:06:57.28,Default,,0000,0000,0000,,where next steps and goals\Nmay not be clear.
Dialogue: 0,0:06:57.30,0:06:58.88,Default,,0000,0000,0000,,Rules may change.
Dialogue: 0,0:06:58.90,0:07:01.45,Default,,0000,0000,0000,,You may or may not get feedback\Nwhen you do something.
Dialogue: 0,0:07:01.47,0:07:03.41,Default,,0000,0000,0000,,It may be delayed, it may be inaccurate,
Dialogue: 0,0:07:03.44,0:07:06.12,Default,,0000,0000,0000,,and work next year\Nmay not look like work last year.
Dialogue: 0,0:07:06.14,0:07:10.35,Default,,0000,0000,0000,,So which one of these sounds like\Nthe world we're increasingly living in?
Dialogue: 0,0:07:10.38,0:07:12.84,Default,,0000,0000,0000,,In fact, our need to think\Nin an adaptable manner
Dialogue: 0,0:07:12.87,0:07:14.98,Default,,0000,0000,0000,,and to keep track of interconnecting parts
Dialogue: 0,0:07:15.00,0:07:17.34,Default,,0000,0000,0000,,has fundamentally changed our perception,
Dialogue: 0,0:07:17.36,0:07:19.20,Default,,0000,0000,0000,,so that when you look at this diagram,
Dialogue: 0,0:07:19.22,0:07:22.55,Default,,0000,0000,0000,,the central circle on the right\Nprobably looks larger to you
Dialogue: 0,0:07:22.58,0:07:24.01,Default,,0000,0000,0000,,because your brain is drawn to
Dialogue: 0,0:07:24.04,0:07:26.17,Default,,0000,0000,0000,,the relationship\Nof the parts in the whole,
Dialogue: 0,0:07:26.19,0:07:28.86,Default,,0000,0000,0000,,whereas someone who hasn't been\Nexposed to modern work
Dialogue: 0,0:07:28.88,0:07:31.50,Default,,0000,0000,0000,,with its requirement for adaptable,\Nconceptual thought,
Dialogue: 0,0:07:31.53,0:07:34.60,Default,,0000,0000,0000,,will see correctly that\Nthe central circles are the same size.
Dialogue: 0,0:07:35.07,0:07:38.14,Default,,0000,0000,0000,,So here we are in the wicked work world,
Dialogue: 0,0:07:38.17,0:07:41.68,Default,,0000,0000,0000,,and there, sometimes\Nhyperspecialization can backfire badly.
Dialogue: 0,0:07:41.70,0:07:44.04,Default,,0000,0000,0000,,For example, in research\Nin a dozen countries
Dialogue: 0,0:07:44.06,0:07:46.88,Default,,0000,0000,0000,,that matched people\Nfor their parents' years of education,
Dialogue: 0,0:07:46.90,0:07:48.07,Default,,0000,0000,0000,,their test scores,
Dialogue: 0,0:07:48.09,0:07:49.50,Default,,0000,0000,0000,,their own years of education,
Dialogue: 0,0:07:49.52,0:07:52.23,Default,,0000,0000,0000,,the difference was\Nsome got career-focused education
Dialogue: 0,0:07:52.25,0:07:54.41,Default,,0000,0000,0000,,and some got broader, general education.
Dialogue: 0,0:07:54.44,0:07:57.21,Default,,0000,0000,0000,,The pattern was those who got\Nthe career-focused education
Dialogue: 0,0:07:57.23,0:07:59.61,Default,,0000,0000,0000,,are more likely to be hired\Nright out of training,
Dialogue: 0,0:07:59.64,0:08:01.67,Default,,0000,0000,0000,,more likely to make more money right away,
Dialogue: 0,0:08:01.69,0:08:04.10,Default,,0000,0000,0000,,but so much less adaptable\Nin a changing work world
Dialogue: 0,0:08:04.12,0:08:06.86,Default,,0000,0000,0000,,that they spend so much less time\Nin the workforce overall
Dialogue: 0,0:08:06.88,0:08:09.79,Default,,0000,0000,0000,,that they win in the short term\Nand lose in the long run.
Dialogue: 0,0:08:09.81,0:08:13.19,Default,,0000,0000,0000,,Or consider a famous,\N20-year study of experts
Dialogue: 0,0:08:13.21,0:08:16.01,Default,,0000,0000,0000,,making geopolitical\Nand economic predictions.
Dialogue: 0,0:08:16.04,0:08:20.12,Default,,0000,0000,0000,,The worst forecasters\Nwere the most specialized experts,
Dialogue: 0,0:08:20.14,0:08:23.33,Default,,0000,0000,0000,,those who'd spent their entire careers\Nstudying one or two problems
Dialogue: 0,0:08:23.35,0:08:26.46,Default,,0000,0000,0000,,and came to see the whole world\Nthrough one lens or mental model.
Dialogue: 0,0:08:26.48,0:08:27.99,Default,,0000,0000,0000,,Some of them actually got worse
Dialogue: 0,0:08:28.02,0:08:30.45,Default,,0000,0000,0000,,as they accumulated\Nexperience and credentials.
Dialogue: 0,0:08:30.47,0:08:35.29,Default,,0000,0000,0000,,The best forecasters were simply\Nbright people with wide-ranging interests.
Dialogue: 0,0:08:35.79,0:08:37.76,Default,,0000,0000,0000,,Now in some domains, like medicine,
Dialogue: 0,0:08:37.79,0:08:40.98,Default,,0000,0000,0000,,increasing specialization has been\Nboth inevitable and beneficial,
Dialogue: 0,0:08:40.100,0:08:42.16,Default,,0000,0000,0000,,no question about it.
Dialogue: 0,0:08:42.18,0:08:44.11,Default,,0000,0000,0000,,And yet, it's been a double-edged sword.
Dialogue: 0,0:08:44.14,0:08:47.78,Default,,0000,0000,0000,,A few years ago, one of the most popular\Nsurgeries in the world for knee pain
Dialogue: 0,0:08:47.80,0:08:49.79,Default,,0000,0000,0000,,was tested in a placebo-controlled trial.
Dialogue: 0,0:08:49.81,0:08:51.73,Default,,0000,0000,0000,,Some of the patients got "sham surgery."
Dialogue: 0,0:08:51.75,0:08:53.71,Default,,0000,0000,0000,,That means the surgeons make an incision,
Dialogue: 0,0:08:53.74,0:08:55.92,Default,,0000,0000,0000,,they bang around like\Nthey're doing something,
Dialogue: 0,0:08:55.94,0:08:57.61,Default,,0000,0000,0000,,then they sew the patient back up.
Dialogue: 0,0:08:57.64,0:08:59.12,Default,,0000,0000,0000,,That performed just as a well.
Dialogue: 0,0:08:59.14,0:09:02.30,Default,,0000,0000,0000,,And yet surgeons who specialize\Nin the procedure continue to do it
Dialogue: 0,0:09:02.32,0:09:03.47,Default,,0000,0000,0000,,by the millions.
Dialogue: 0,0:09:04.04,0:09:08.26,Default,,0000,0000,0000,,So if hyperspecialization isn't always\Nthe trick in a wicked world, what is?
Dialogue: 0,0:09:08.28,0:09:10.04,Default,,0000,0000,0000,,That can be difficult to talk about,
Dialogue: 0,0:09:10.07,0:09:12.28,Default,,0000,0000,0000,,because it doesn't always\Nlook like this path.
Dialogue: 0,0:09:12.31,0:09:14.62,Default,,0000,0000,0000,,Sometimes it looks like\Nmeandering or zigzagging
Dialogue: 0,0:09:14.65,0:09:15.94,Default,,0000,0000,0000,,or keeping a broader view.
Dialogue: 0,0:09:15.96,0:09:17.54,Default,,0000,0000,0000,,It can look like getting behind.
Dialogue: 0,0:09:17.56,0:09:20.39,Default,,0000,0000,0000,,But I want to talk about what\Nsome of those tricks might be.
Dialogue: 0,0:09:20.41,0:09:24.16,Default,,0000,0000,0000,,If we look at research on technological\Ninnovation, it shows that increasingly,
Dialogue: 0,0:09:24.18,0:09:26.95,Default,,0000,0000,0000,,the most impactful patents\Nare not authored by individuals
Dialogue: 0,0:09:26.97,0:09:29.84,Default,,0000,0000,0000,,who drill deeper, deeper, deeper\Ninto one area of technology
Dialogue: 0,0:09:29.87,0:09:31.71,Default,,0000,0000,0000,,as classified by the US Patent Office,
Dialogue: 0,0:09:31.73,0:09:34.70,Default,,0000,0000,0000,,but rather by teams\Nthat include individuals
Dialogue: 0,0:09:34.73,0:09:37.99,Default,,0000,0000,0000,,who have worked across a large number\Nof different technology classes
Dialogue: 0,0:09:38.02,0:09:40.21,Default,,0000,0000,0000,,and often merge things\Nfrom different domains.
Dialogue: 0,0:09:40.23,0:09:43.66,Default,,0000,0000,0000,,Someone whose work I've admired\Nwho was sort of on the forefront of this
Dialogue: 0,0:09:43.69,0:09:45.58,Default,,0000,0000,0000,,is a Japanese man named Gunpei Yokoi.
Dialogue: 0,0:09:45.60,0:09:48.38,Default,,0000,0000,0000,,Yokoi didn't score well\Non his electronics exams at school,
Dialogue: 0,0:09:48.40,0:09:51.70,Default,,0000,0000,0000,,so he had to settle for a low-tier job\Nas a machine maintenance worker
Dialogue: 0,0:09:51.72,0:09:53.55,Default,,0000,0000,0000,,at a playing card company in Kyoto.
Dialogue: 0,0:09:53.57,0:09:56.62,Default,,0000,0000,0000,,He realized he wasn't equipped\Nto work on the cutting edge,
Dialogue: 0,0:09:56.64,0:09:59.56,Default,,0000,0000,0000,,but that there was so much\Ninformation easily available
Dialogue: 0,0:09:59.59,0:10:02.56,Default,,0000,0000,0000,,that maybe he could combine things\Nthat were already well-known
Dialogue: 0,0:10:02.59,0:10:05.16,Default,,0000,0000,0000,,in ways that specialists\Nwere too narrow to see.
Dialogue: 0,0:10:05.18,0:10:08.68,Default,,0000,0000,0000,,So he combined some well-known technology\Nfrom the calculator industry
Dialogue: 0,0:10:08.70,0:10:11.62,Default,,0000,0000,0000,,with some well-known technology\Nfrom the credit card industry
Dialogue: 0,0:10:11.64,0:10:13.08,Default,,0000,0000,0000,,and made handheld games.
Dialogue: 0,0:10:13.11,0:10:14.46,Default,,0000,0000,0000,,And they were a hit.
Dialogue: 0,0:10:14.49,0:10:16.71,Default,,0000,0000,0000,,And it turned this playing card company,
Dialogue: 0,0:10:16.73,0:10:20.30,Default,,0000,0000,0000,,which was founded in a wooden\Nstorefront in the 19th century,
Dialogue: 0,0:10:20.33,0:10:22.08,Default,,0000,0000,0000,,into a toy and game operation.
Dialogue: 0,0:10:22.11,0:10:24.33,Default,,0000,0000,0000,,You may have heard of it;\Nit's called Nintendo.
Dialogue: 0,0:10:24.36,0:10:25.66,Default,,0000,0000,0000,,Yokoi's creative philosophy
Dialogue: 0,0:10:25.68,0:10:28.86,Default,,0000,0000,0000,,translated to "lateral thinking\Nwith withered technology,"
Dialogue: 0,0:10:28.88,0:10:31.81,Default,,0000,0000,0000,,taking well-known technology\Nand using it in new ways.
Dialogue: 0,0:10:31.84,0:10:33.78,Default,,0000,0000,0000,,And his magnum opus was this:
Dialogue: 0,0:10:33.80,0:10:34.98,Default,,0000,0000,0000,,the Game Boy.
Dialogue: 0,0:10:35.00,0:10:37.44,Default,,0000,0000,0000,,Technological joke in every way.
Dialogue: 0,0:10:37.46,0:10:41.28,Default,,0000,0000,0000,,And it came out at the same time\Nas color competitors from Saga and Atari,
Dialogue: 0,0:10:41.30,0:10:42.96,Default,,0000,0000,0000,,and it blew them away,
Dialogue: 0,0:10:42.99,0:10:45.63,Default,,0000,0000,0000,,because Yokoi knew\Nwhat his customers cared about
Dialogue: 0,0:10:45.65,0:10:46.80,Default,,0000,0000,0000,,wasn't color.
Dialogue: 0,0:10:46.83,0:10:50.79,Default,,0000,0000,0000,,It was durability, portability,\Naffordability, battery life,
Dialogue: 0,0:10:50.81,0:10:52.11,Default,,0000,0000,0000,,game selection.
Dialogue: 0,0:10:52.14,0:10:54.59,Default,,0000,0000,0000,,This is mine that I found\Nin my parents' basement.
Dialogue: 0,0:10:54.61,0:10:55.77,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:10:55.80,0:10:57.35,Default,,0000,0000,0000,,It's seen better days.
Dialogue: 0,0:10:57.38,0:10:59.12,Default,,0000,0000,0000,,But you can see the red light is on.
Dialogue: 0,0:10:59.14,0:11:01.04,Default,,0000,0000,0000,,I flipped it on and played some Tetris,
Dialogue: 0,0:11:01.06,0:11:03.04,Default,,0000,0000,0000,,which I thought was especially impressive
Dialogue: 0,0:11:03.07,0:11:05.53,Default,,0000,0000,0000,,because the batteries had expired\Nin 2007 and 2013.
Dialogue: 0,0:11:05.56,0:11:06.90,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:11:07.49,0:11:11.08,Default,,0000,0000,0000,,So this breadth advantage holds\Nin more subjective realms as well.
Dialogue: 0,0:11:11.10,0:11:14.57,Default,,0000,0000,0000,,In a fascinating study of what leads\Nsome comic book creators
Dialogue: 0,0:11:14.60,0:11:17.44,Default,,0000,0000,0000,,to be more likely to make\Nblockbuster comics,
Dialogue: 0,0:11:17.46,0:11:18.77,Default,,0000,0000,0000,,a pair of researchers found
Dialogue: 0,0:11:18.80,0:11:22.33,Default,,0000,0000,0000,,that it was neither the number of years\Nof experience in the field
Dialogue: 0,0:11:22.35,0:11:25.22,Default,,0000,0000,0000,,nor the resources of the publisher
Dialogue: 0,0:11:25.24,0:11:27.46,Default,,0000,0000,0000,,nor the number of previous comics made.
Dialogue: 0,0:11:27.48,0:11:31.95,Default,,0000,0000,0000,,It was the number of different genres\Nthat a creator had worked across.
Dialogue: 0,0:11:31.97,0:11:33.30,Default,,0000,0000,0000,,And interestingly,
Dialogue: 0,0:11:33.32,0:11:36.97,Default,,0000,0000,0000,,a broad individual\Ncould not be entirely replaced
Dialogue: 0,0:11:36.99,0:11:38.79,Default,,0000,0000,0000,,by a team of specialists.
Dialogue: 0,0:11:39.15,0:11:42.12,Default,,0000,0000,0000,,We probably don't make as many\Nof those people as we could
Dialogue: 0,0:11:42.15,0:11:44.96,Default,,0000,0000,0000,,because early on,\Nthey just look like they're behind
Dialogue: 0,0:11:44.98,0:11:48.68,Default,,0000,0000,0000,,and we don't tend to incentivize anything\Nthat doesn't look like a head start
Dialogue: 0,0:11:48.70,0:11:49.88,Default,,0000,0000,0000,,or specialization.
Dialogue: 0,0:11:49.90,0:11:52.75,Default,,0000,0000,0000,,In fact, I think in the well-meaning\Ndrive for a head start,
Dialogue: 0,0:11:52.77,0:11:55.62,Default,,0000,0000,0000,,we often even counterproductively\Nshort-circuit even the way
Dialogue: 0,0:11:55.65,0:11:56.95,Default,,0000,0000,0000,,we learn new material,
Dialogue: 0,0:11:56.97,0:11:58.56,Default,,0000,0000,0000,,at a fundamental level.
Dialogue: 0,0:11:58.58,0:12:02.42,Default,,0000,0000,0000,,In a study last year,\Nseventh-grade math classrooms in the US
Dialogue: 0,0:12:02.45,0:12:05.32,Default,,0000,0000,0000,,were randomly assigned\Nto different types of learning.
Dialogue: 0,0:12:05.35,0:12:07.92,Default,,0000,0000,0000,,Some got what's called "blocked practice."
Dialogue: 0,0:12:07.95,0:12:09.69,Default,,0000,0000,0000,,That's like, you get problem type A,
Dialogue: 0,0:12:09.72,0:12:12.62,Default,,0000,0000,0000,,AAAAA, BBBBB, and so on.
Dialogue: 0,0:12:12.65,0:12:14.07,Default,,0000,0000,0000,,Progress is fast,
Dialogue: 0,0:12:14.10,0:12:15.25,Default,,0000,0000,0000,,kids are happy,
Dialogue: 0,0:12:15.27,0:12:16.44,Default,,0000,0000,0000,,everything's great.
Dialogue: 0,0:12:16.46,0:12:20.50,Default,,0000,0000,0000,,Other classrooms got assigned\Nto what's called "interleaved practice."
Dialogue: 0,0:12:20.52,0:12:23.78,Default,,0000,0000,0000,,That's like if you took all the problem\Ntypes and threw them in a hat
Dialogue: 0,0:12:23.80,0:12:25.15,Default,,0000,0000,0000,,and drew them out at random.
Dialogue: 0,0:12:25.17,0:12:28.10,Default,,0000,0000,0000,,Progress is slower,\Nkids are more frustrated.
Dialogue: 0,0:12:28.12,0:12:30.78,Default,,0000,0000,0000,,But instead of learning\Nhow to execute procedures,
Dialogue: 0,0:12:30.81,0:12:34.62,Default,,0000,0000,0000,,they're learning how to match\Na strategy to a type of problem.
Dialogue: 0,0:12:34.64,0:12:36.24,Default,,0000,0000,0000,,And when the test comes around,
Dialogue: 0,0:12:36.26,0:12:39.70,Default,,0000,0000,0000,,the interleaved group blew\Nthe block practice group away.
Dialogue: 0,0:12:39.72,0:12:41.13,Default,,0000,0000,0000,,It wasn't even close.
Dialogue: 0,0:12:41.82,0:12:45.44,Default,,0000,0000,0000,,Now, I found a lot of this research\Ndeeply counterintuitive,
Dialogue: 0,0:12:45.47,0:12:46.82,Default,,0000,0000,0000,,the idea that a head start,
Dialogue: 0,0:12:46.84,0:12:49.12,Default,,0000,0000,0000,,whether in picking a career\Nor a course of study
Dialogue: 0,0:12:49.14,0:12:50.76,Default,,0000,0000,0000,,or just in learning new material,
Dialogue: 0,0:12:50.79,0:12:53.48,Default,,0000,0000,0000,,can sometimes undermine\Nlong-term development.
Dialogue: 0,0:12:53.50,0:12:56.29,Default,,0000,0000,0000,,And naturally, I think there are\Nas many ways to succeed
Dialogue: 0,0:12:56.31,0:12:57.68,Default,,0000,0000,0000,,as there are people.
Dialogue: 0,0:12:57.70,0:13:01.92,Default,,0000,0000,0000,,But I think we tend only to incentivize\Nand encourage the Tiger path,
Dialogue: 0,0:13:01.95,0:13:03.74,Default,,0000,0000,0000,,when increasingly, in a wicked world,
Dialogue: 0,0:13:03.76,0:13:06.69,Default,,0000,0000,0000,,we need people who travel\Nthe Roger path as well.
Dialogue: 0,0:13:06.71,0:13:09.27,Default,,0000,0000,0000,,Or as the eminent physicist\Nand mathematician
Dialogue: 0,0:13:09.30,0:13:12.72,Default,,0000,0000,0000,,and wonderful writer,\NFreeman Dyson, put it --
Dialogue: 0,0:13:12.74,0:13:15.64,Default,,0000,0000,0000,,and Dyson passed away yesterday,
Dialogue: 0,0:13:15.66,0:13:17.94,Default,,0000,0000,0000,,so I hope I'm doing\Nhis words honor here --
Dialogue: 0,0:13:17.96,0:13:22.85,Default,,0000,0000,0000,,as he said: for a healthy ecosystem,\Nwe need both birds and frogs.
Dialogue: 0,0:13:22.88,0:13:24.18,Default,,0000,0000,0000,,Frogs are down in the mud,
Dialogue: 0,0:13:24.20,0:13:26.30,Default,,0000,0000,0000,,seeing all the granular details.
Dialogue: 0,0:13:26.33,0:13:29.08,Default,,0000,0000,0000,,The birds are soaring up above\Nnot seeing those details
Dialogue: 0,0:13:29.11,0:13:31.16,Default,,0000,0000,0000,,but integrating\Nthe knowledge of the frogs.
Dialogue: 0,0:13:31.18,0:13:32.49,Default,,0000,0000,0000,,And we need both.
Dialogue: 0,0:13:32.52,0:13:34.21,Default,,0000,0000,0000,,The problem, Dyson said,
Dialogue: 0,0:13:34.23,0:13:36.91,Default,,0000,0000,0000,,is that we're telling everyone\Nto become frogs.
Dialogue: 0,0:13:36.93,0:13:38.14,Default,,0000,0000,0000,,And I think,
Dialogue: 0,0:13:38.16,0:13:39.61,Default,,0000,0000,0000,,in a wicked world,
Dialogue: 0,0:13:39.64,0:13:41.79,Default,,0000,0000,0000,,that's increasingly shortsighted.
Dialogue: 0,0:13:41.81,0:13:43.10,Default,,0000,0000,0000,,Thank you very much.
Dialogue: 0,0:13:43.13,0:13:46.09,Default,,0000,0000,0000,,(Applause)