Return to Video

Why specializing early doesn't always mean career success

  • 0:02 - 0:05
    So I'd like to talk about
    the development of human potential,
  • 0:05 - 0:10
    and I'd like to start with maybe the most
    impactful modern story of development.
  • 0:10 - 0:13
    Many of you here have probably heard
    of the 10,000 hours rule.
  • 0:14 - 0:16
    Maybe you even model
    your own life after it.
  • 0:16 - 0:18
    Basically it's the idea
    that to become great in anything,
  • 0:18 - 0:22
    it takes 10,000 hours
    of focused practice,
  • 0:22 - 0:24
    so you'd better get started
    as early as possible.
  • 0:24 - 0:27
    The poster child
    for this story is Tiger Woods.
  • 0:28 - 0:31
    His father famously gave him
    a putter when he was seven months old.
  • 0:31 - 0:35
    At 10 months, he started
    imitating his father's swing.
  • 0:35 - 0:38
    At two, you can go on YouTube
    and see him on national television.
  • 0:38 - 0:40
    Fast-forward to the age of 21,
  • 0:40 - 0:42
    he's the greatest golfer in the world.
  • 0:42 - 0:44
    Quintessential 10,000 hours story.
  • 0:44 - 0:46
    Another that features a number
    of bestselling books
  • 0:46 - 0:48
    is that of the three Polgar sisters,
  • 0:48 - 0:51
    whose father decided to teach
    them chess in a very technical manner
  • 0:51 - 0:53
    from a very early age.
  • 0:53 - 0:54
    And really he wanted to show
  • 0:54 - 0:56
    that with a head start
    in focused practice,
  • 0:56 - 0:58
    any child could become
    a genius in anything.
  • 0:59 - 1:00
    And in fact,
  • 1:00 - 1:03
    two of his daughters went on
    to become grandmaster chess players.
  • 1:03 - 1:06
    So when I became the science writer
    at "Sports Illustrated" magazine,
  • 1:06 - 1:07
    I got curious.
  • 1:07 - 1:09
    If this 10,000 hours rule is correct,
  • 1:09 - 1:12
    then we should see that elite
    athletes get a head start
  • 1:12 - 1:14
    in so-called "deliberate practice."
  • 1:14 - 1:15
    This is coached,
  • 1:15 - 1:16
    error-correction focused practice,
  • 1:16 - 1:18
    not just playing around.
  • 1:18 - 1:19
    And in fact,
  • 1:19 - 1:21
    when scientists study elite athletes,
  • 1:21 - 1:24
    they see that they spend
    more time in deliberate practice --
  • 1:24 - 1:25
    not a big surprise.
  • 1:25 - 1:28
    When they actually track athletes
    over the course of their development,
  • 1:28 - 1:29
    the pattern looks like this:
  • 1:29 - 1:33
    the future elites actually spend
    less time early on in deliberate practice
  • 1:33 - 1:35
    in their eventual sport.
  • 1:35 - 1:38
    They tend to have what scientists
    call a "sampling period,"
  • 1:38 - 1:40
    where they try a variety
    of physical activities,
  • 1:40 - 1:42
    they gain broad, general skills,
  • 1:42 - 1:44
    they learn about
    their interests and abilities
  • 1:44 - 1:48
    and delay specializing until later
    than peers who plateau at lower levels.
  • 1:49 - 1:51
    And so when I saw that I said,
  • 1:51 - 1:54
    "Gosh, that doesn't really comport
    with the 10,000 hours rule, does it?"
  • 1:54 - 1:56
    So I started to wonder about other domains
  • 1:56 - 2:00
    that we associate with obligatory,
    early specialization,
  • 2:00 - 2:01
    like music.
  • 2:01 - 2:03
    Turns out the pattern's often similar.
  • 2:03 - 2:05
    This is research from
    a world-class music academy,
  • 2:05 - 2:08
    and what I want to draw
    your attention to is this:
  • 2:08 - 2:12
    the exceptional musicians didn't start
    spending more time in deliberate practice
  • 2:12 - 2:13
    than the average musicians
  • 2:13 - 2:14
    until their third instrument.
  • 2:14 - 2:16
    They, too, tended to have
    a sampling period.
  • 2:16 - 2:19
    Even musicians we think of
    as famously precocious,
  • 2:19 - 2:20
    like Yo-Yo Ma.
  • 2:20 - 2:21
    He had a sampling period,
  • 2:21 - 2:24
    he just went through it more rapidly
    than most musicians do.
  • 2:24 - 2:27
    Nonetheless, this research
    is almost entirely ignored,
  • 2:27 - 2:29
    and much more impactful
  • 2:29 - 2:32
    is the first page of the book
    "Battle Hymn of the Tiger Mother,"
  • 2:32 - 2:35
    where the author recounts
    assigning her daughter violin.
  • 2:35 - 2:37
    Nobody seems to remember
    the part later in the book
  • 2:37 - 2:40
    where her daughter turns to her
    and says, "You picked it, not me,"
  • 2:40 - 2:41
    and largely quits.
  • 2:41 - 2:45
    So having seen this sort of surprising
    pattern in sports and music,
  • 2:45 - 2:47
    I started to wonder about domains
    that effect even more people,
  • 2:47 - 2:49
    like education.
  • 2:49 - 2:50
    An economist found a natural experiment
  • 2:50 - 2:53
    in the higher-ed systems
    of England and Scotland.
  • 2:53 - 2:55
    In the period he studied
    the systems were very similar
  • 2:55 - 2:56
    except in England,
  • 2:56 - 2:59
    students had to specialize
    in their mid-teen years
  • 2:59 - 3:01
    to pick a specific course
    of study to apply to,
  • 3:01 - 3:02
    whereas in Scotland,
  • 3:02 - 3:05
    they could keep trying things
    in the university if they wanted to.
  • 3:05 - 3:06
    And his question was:
  • 3:06 - 3:08
    who wins the trade-off,
  • 3:08 - 3:10
    the early of the late specializers?
  • 3:10 - 3:13
    And what he saw was that the early
    specializers jump out to an income lead
  • 3:13 - 3:16
    because they have more
    domain-specific skills.
  • 3:16 - 3:18
    The late specializers
    get to try more different things,
  • 3:18 - 3:19
    and when they do pick,
  • 3:19 - 3:20
    they have better fit,
  • 3:20 - 3:22
    or what economists call "match quality."
  • 3:22 - 3:25
    And so their growth rates are faster.
  • 3:25 - 3:26
    By six years out,
  • 3:26 - 3:27
    they erase that income gap.
  • 3:28 - 3:31
    Meanwhile, the early specializers
    start quitting their career tracks
  • 3:31 - 3:32
    in much higher numbers,
  • 3:32 - 3:35
    essentially because they were
    made to choose so early
  • 3:35 - 3:36
    that they more often made poor choices.
  • 3:36 - 3:39
    So the late specializers
    lose in the short term
  • 3:39 - 3:40
    and win the long run.
  • 3:40 - 3:42
    I think if we thought about
    career choice like dating,
  • 3:42 - 3:45
    we might not pressure people
    to settle down quite so quickly.
  • 3:45 - 3:46
    So this got me interested --
  • 3:46 - 3:48
    seeing this pattern again --
  • 3:48 - 3:50
    in exploring the developmental backgrounds
  • 3:50 - 3:52
    of people whose work I had long admired.
  • 3:52 - 3:53
    Like Duke Ellington,
  • 3:53 - 3:55
    who shunned music lessons
    as a kid to focus on baseball
  • 3:55 - 3:56
    and painting and drawing.
  • 3:56 - 3:58
    Or Maryam Mirzakhani,
  • 3:58 - 4:00
    who wasn't interested
    in math as a girl --
  • 4:00 - 4:01
    dreamed of becoming a novelist --
  • 4:01 - 4:04
    and went on to become
    the first and so far only woman
  • 4:04 - 4:05
    to win the Fields Medal,
  • 4:05 - 4:07
    the most prestigious prize
    in the world in math.
  • 4:07 - 4:09
    Or Vincent Van Gogh
    had five different careers,
  • 4:09 - 4:11
    each of which he deemed his true calling
  • 4:11 - 4:13
    before flaming out spectacularly.
  • 4:13 - 4:18
    And in his late 20s picked up a book
    called "The Guide to the ABCs of Drawing."
  • 4:18 - 4:19
    That worked out OK.
  • 4:20 - 4:23
    Claude Shannon was an electrical engineer
    at the University of Michigan
  • 4:23 - 4:26
    who took a philosophy course
    just to fulfill a requirement,
  • 4:26 - 4:30
    and in it, he learned about
    a near century-old system of logic
  • 4:30 - 4:33
    by which true and false statements
    could be coded as ones and zeros
  • 4:33 - 4:35
    and solved like math problems.
  • 4:35 - 4:37
    This led to the development
    of binary code,
  • 4:37 - 4:40
    which underlies all of our
    digital computers today.
  • 4:40 - 4:42
    Finally, my own sort of role model,
  • 4:42 - 4:43
    Frances Hesselbein --
  • 4:43 - 4:44
    this is me with her --
  • 4:44 - 4:48
    she took her first professional
    job at the age of 54
  • 4:48 - 4:50
    and went on to become
    the CEO of the Girl Scouts,
  • 4:50 - 4:51
    which she saved.
  • 4:51 - 4:53
    She tripled minority membership,
  • 4:53 - 4:56
    added 130,000 volunteers,
  • 4:56 - 4:59
    and this is one of the proficiency badges
    that came out of her tenure --
  • 4:59 - 5:01
    it's binary code for girls
    learning about computers.
  • 5:02 - 5:04
    Today, Frances runs a leadership institute
  • 5:04 - 5:06
    where she works every
    weekday in Manhattan,
  • 5:06 - 5:07
    and she's only 104,
  • 5:07 - 5:09
    so who knows what's next.
  • 5:09 - 5:10
    (Laughter)
  • 5:11 - 5:14
    We never really hear developmental
    stories like this, do we?
  • 5:14 - 5:15
    We don't hear about the research
  • 5:15 - 5:18
    that found that Nobel laureate scientists
    are 22 times more likely
  • 5:18 - 5:20
    to have a hobby outside of work
  • 5:20 - 5:21
    as are typical scientists.
  • 5:21 - 5:22
    We never hear that.
  • 5:22 - 5:25
    Even when the performers
    or the work is very famous,
  • 5:25 - 5:27
    we don't hear these
    developmental stories.
  • 5:27 - 5:29
    For example, here's
    an athlete I've followed.
  • 5:29 - 5:30
    Here he is at age six,
  • 5:30 - 5:31
    wearing a Scottish rugby kit.
  • 5:31 - 5:32
    He tried some tennis,
  • 5:32 - 5:33
    some skiing,
  • 5:33 - 5:34
    wrestling.
  • 5:34 - 5:38
    His mother was actually a tennis coach
    but she declined to coach him
  • 5:38 - 5:40
    because he wouldn't return balls normally.
  • 5:40 - 5:42
    He did some basketball,
    table tennis, swimming.
  • 5:42 - 5:46
    When his coaches wanted to move
    him up a level to play with older boys,
  • 5:46 - 5:49
    he declined because he just wanted
    to talk about pro wrestling
  • 5:49 - 5:50
    after practice with his friends.
  • 5:50 - 5:52
    And he kept trying more sports:
  • 5:52 - 5:54
    handball, volleyball, soccer,
    badminton, skateboarding --
  • 5:54 - 5:56
    so who is this dabbler?
  • 5:57 - 5:58
    This is Roger Federer.
  • 5:59 - 6:02
    Every bit as famous
    as an adult as Tiger Woods,
  • 6:02 - 6:05
    and yet even tennis enthusiasts
    don't usually know anything
  • 6:05 - 6:07
    about his developmental story.
  • 6:07 - 6:09
    Why is that even though it's the norm?
  • 6:09 - 6:12
    I think it's partly because
    the Tiger story is very dramatic.
  • 6:12 - 6:15
    But also because it seems
    like this tidy narrative
  • 6:15 - 6:17
    that we can extrapolate to anything
  • 6:17 - 6:19
    that we want to be good
    at in our own lives.
  • 6:19 - 6:21
    But that I think is a problem,
  • 6:21 - 6:24
    because it turns out that in many ways
    golf is a uniquely horrible model
  • 6:24 - 6:27
    of almost everything
    that humans want to learn.
  • 6:27 - 6:28
    (Laughter)
  • 6:28 - 6:31
    Golf is the epitome of what
    the psychologist Robin Hogarth called
  • 6:31 - 6:33
    a "kind" learning environment.
  • 6:33 - 6:36
    Kind learning environments
    have next steps and goals that are clear,
  • 6:36 - 6:38
    rules that are clear and never change --
  • 6:38 - 6:41
    when you do something you get feedback
    that is quick and accurate;
  • 6:41 - 6:43
    work next year will look
    like work last year.
  • 6:43 - 6:44
    Chess:
  • 6:44 - 6:46
    also a kind learning environment.
  • 6:46 - 6:50
    The grandmasters' advantage is based
    on knowledge of recurring patterns,
  • 6:50 - 6:52
    which is also why
    it's so easy to automate.
  • 6:52 - 6:55
    On the other end of the spectrum
    are "wicked" learning environments,
  • 6:55 - 6:57
    where next steps and goals
    may not be clear.
  • 6:57 - 6:59
    Rules may change.
  • 6:59 - 7:01
    You may or may not get feedback
    when you do something.
  • 7:01 - 7:02
    It may be delayed,
  • 7:02 - 7:03
    it may be inaccurate
  • 7:03 - 7:06
    and work next year may not
    look like work last year.
  • 7:06 - 7:08
    So which one of these
    sounds like the world
  • 7:08 - 7:10
    we're increasingly living in?
  • 7:11 - 7:13
    In fact, our need to think
    in an adaptable manner
  • 7:13 - 7:15
    and to keep track of interconnecting parts
  • 7:15 - 7:17
    has fundamentally changed our perception
  • 7:17 - 7:19
    so that when you look at this diagram,
  • 7:19 - 7:23
    the central circle on the right
    probably looks larger to you
  • 7:23 - 7:25
    because your brain is drawn
    to the relationship of the parts
  • 7:25 - 7:26
    in the whole,
  • 7:26 - 7:29
    whereas someone who hasn't been
    exposed to modern work
  • 7:29 - 7:32
    with its requirement for adaptable,
    conceptual thought,
  • 7:32 - 7:35
    will see correctly that the central
    circles are the same size.
  • 7:35 - 7:38
    So here we are in the wicked work world,
  • 7:38 - 7:42
    and there, sometimes
    hyperspecialization can backfire badly.
  • 7:42 - 7:43
    For example,
  • 7:43 - 7:44
    in research in a dozen countries
  • 7:44 - 7:47
    that matched people
    for their parents' years of education,
  • 7:47 - 7:48
    their test scores,
  • 7:48 - 7:50
    their own years of education,
  • 7:50 - 7:52
    the difference was some got
    career-focused education
  • 7:52 - 7:55
    and some got broader, general education.
  • 7:55 - 7:57
    The pattern was those who got
    the career-focused education
  • 7:57 - 8:00
    are more likely to be hired
    right out of training,
  • 8:00 - 8:02
    more likely to make more money right away,
  • 8:02 - 8:04
    but so much less adaptable
    in a changing work world
  • 8:04 - 8:07
    that they spend so much less time
    in the workforce overall
  • 8:07 - 8:10
    that they win in the short term
    and lose in the long run.
  • 8:10 - 8:13
    Or consider a famous,
    20-year study of experts
  • 8:13 - 8:16
    making geopolitical
    and economic predictions.
  • 8:16 - 8:20
    The worst forecasters
    were the most specialized experts.
  • 8:20 - 8:23
    Those who'd spent their entire careers
    studying one or two problems
  • 8:23 - 8:26
    and came to see the whole world
    through one lens or mental model.
  • 8:26 - 8:28
    Some of them actually got worse
  • 8:28 - 8:30
    as they accumulated
    experience and credentials.
  • 8:31 - 8:35
    The best forecasters were simply
    bright people with wide-ranging interests.
  • 8:36 - 8:37
    Now in some domains,
  • 8:37 - 8:38
    like medicine,
  • 8:38 - 8:41
    increasing specialization has been
    both inevitable and beneficial.
  • 8:41 - 8:42
    No question about it.
  • 8:42 - 8:44
    And yet it's been a double-edged sword.
  • 8:44 - 8:45
    A few years ago,
  • 8:45 - 8:48
    one of the most popular surgeries
    in the world for knee pain
  • 8:48 - 8:50
    was tested in a placebo-controlled trial.
  • 8:50 - 8:52
    Some of the patients got "sham surgery."
  • 8:52 - 8:54
    That means the surgeons make an incision,
  • 8:54 - 8:56
    they bang around like
    they're doing something,
  • 8:56 - 8:58
    then they sew the patient back up.
  • 8:58 - 8:59
    That performed just as a well.
  • 8:59 - 9:02
    And yet surgeons who specialize
    in the procedure continue to do it
  • 9:02 - 9:03
    by the millions.
  • 9:04 - 9:08
    So if hyperspecialization isn't always
    the trick in a wicked world, what is?
  • 9:08 - 9:10
    That can be difficult to talk about
  • 9:10 - 9:12
    because it doesn't
    always look like this path.
  • 9:12 - 9:14
    Sometimes it looks like
    meandering or zigzagging
  • 9:14 - 9:16
    or keeping a broader view.
  • 9:16 - 9:17
    It can look like getting behind.
  • 9:17 - 9:20
    But I want to talk about what
    some of those tricks might be.
  • 9:20 - 9:23
    If we look at research
    on technological innovation,
  • 9:23 - 9:24
    it shows that increasingly,
  • 9:24 - 9:27
    the most impactful patents
    are not authored by individuals
  • 9:27 - 9:29
    who drill deeper, deeper, deeper
    into one area of technology,
  • 9:29 - 9:32
    as classified by the US Patent Office,
  • 9:32 - 9:35
    but rather by teams
    that include individuals
  • 9:35 - 9:38
    who have worked across a large number
    of different technology classes
  • 9:38 - 9:40
    and often merge things
    from different domains.
  • 9:40 - 9:42
    Someone whose work I've admired
  • 9:42 - 9:44
    who was sort of
    on the forefront of this --
  • 9:44 - 9:46
    a Japanese man named Gunpei Yokoi.
  • 9:46 - 9:48
    Yokoi didn't score well
    on his electronics exams at school,
  • 9:48 - 9:52
    so he had to settle for a low-tier job
    as a machine maintenance worker
  • 9:52 - 9:53
    at a playing card company in Kyoto.
  • 9:54 - 9:57
    He realized he wasn't equipped
    to work on the cutting edge,
  • 9:57 - 10:00
    but that there was so much
    information easily available
  • 10:00 - 10:03
    that maybe he could combine things
    that were already well-known
  • 10:03 - 10:05
    in ways that specialists
    were too narrow to see.
  • 10:05 - 10:09
    So he combined some well-known technology
    from the calculator industry
  • 10:09 - 10:12
    with some well-known technology
    from the credit card industry
  • 10:12 - 10:13
    and made handheld games.
  • 10:13 - 10:14
    And they were a hit.
  • 10:14 - 10:17
    And it turned this playing card company,
  • 10:17 - 10:20
    which was founded in a wooden
    storefront in the 19th century,
  • 10:20 - 10:22
    into a toy and game operation.
  • 10:22 - 10:23
    You may have heard of it;
  • 10:23 - 10:24
    it's called Nintendo.
  • 10:24 - 10:26
    Yokoi's creative philosophy translated
  • 10:26 - 10:29
    to "lateral thinking
    with withered technology;"
  • 10:29 - 10:32
    taking well-known technology
    and using it in new ways.
  • 10:32 - 10:34
    And his magnum opus was this:
  • 10:34 - 10:35
    the Game Boy.
  • 10:35 - 10:37
    Technological joke in every way.
  • 10:38 - 10:41
    And it came out at the same time
    as color competitors from Saga and Atari
  • 10:41 - 10:43
    and it blew them away
  • 10:43 - 10:46
    because Yokoi knew what his
    customers cared about wasn't color.
  • 10:46 - 10:48
    It was durability,
  • 10:48 - 10:49
    portability,
  • 10:49 - 10:50
    affordability,
  • 10:50 - 10:51
    battery life --
  • 10:51 - 10:52
    game selection.
  • 10:52 - 10:55
    This is mine that I found
    in my parents' basement --
  • 10:55 - 10:56
    (Laughter)
  • 10:56 - 10:57
    seen better days.
  • 10:57 - 10:59
    But you can see the red light is on.
  • 10:59 - 11:01
    I flipped it on and played some Tetris,
  • 11:01 - 11:03
    which I thought was especially impressive
  • 11:03 - 11:05
    because the batteries had expired
    in 2007 and 2013.
  • 11:05 - 11:07
    (Laughter)
  • 11:08 - 11:11
    So this breadth advantage holds
    in more subjective realms as well.
  • 11:11 - 11:15
    In a fascinating study of what leads
    some comic book creators
  • 11:15 - 11:17
    to be more likely to make
    blockbuster comics,
  • 11:17 - 11:19
    a pair of researchers found
  • 11:19 - 11:22
    that it was neither the number of years
    of experience in the field
  • 11:22 - 11:25
    nor the resources of the publisher
  • 11:25 - 11:28
    nor the number of previous comics made.
  • 11:28 - 11:32
    It was the number of different genres
    that a creator had worked across.
  • 11:32 - 11:33
    And interestingly,
  • 11:33 - 11:37
    a broad individual
    could not be entirely replaced
  • 11:37 - 11:39
    by a team of specialists.
  • 11:39 - 11:42
    We probably don't make as many
    of those people as we could
  • 11:42 - 11:43
    because early on,
  • 11:43 - 11:45
    they just look like they're behind
  • 11:45 - 11:49
    and we don't tend to incentivize anything
    that doesn't look like a head start
  • 11:49 - 11:50
    or specialization.
  • 11:50 - 11:53
    In fact, I think in the well-meaning
    drive for a head start,
  • 11:53 - 11:56
    we often even counterproductively
    short circuit even the way we learn
  • 11:56 - 11:58
    new material at a fundamental level.
  • 11:59 - 12:00
    In a study last year,
  • 12:00 - 12:03
    seventh-grade math classrooms in the US
  • 12:03 - 12:05
    were randomly assigned
    to different types of learning.
  • 12:05 - 12:08
    Some got what's called "blocked practice."
  • 12:08 - 12:10
    That's like, you get problem type A,
  • 12:10 - 12:11
    AAAAA,
  • 12:11 - 12:12
    BBBBB,
  • 12:12 - 12:13
    and so on.
  • 12:13 - 12:14
    Progress is fast;
  • 12:14 - 12:15
    kids are happy;
  • 12:15 - 12:16
    everything's great.
  • 12:16 - 12:20
    Other classrooms got assigned
    to what's called "interleaved practice."
  • 12:21 - 12:23
    That's like if you took
    all the problem types
  • 12:23 - 12:24
    and threw them in a hat
  • 12:24 - 12:25
    and drew them out at random.
  • 12:25 - 12:26
    Progress is slower;
  • 12:26 - 12:28
    kids are more frustrated.
  • 12:28 - 12:31
    But instead of learning
    how to execute procedures,
  • 12:31 - 12:34
    they're learning how to match
    a strategy to a type of problem.
  • 12:35 - 12:36
    And when the test comes around,
  • 12:36 - 12:40
    the interleaved group blew
    the block practice group away.
  • 12:40 - 12:41
    It wasn't even close.
  • 12:42 - 12:45
    Now I found a lot of this research
    deeply counterintuitive.
  • 12:45 - 12:47
    The idea that a head start,
  • 12:47 - 12:49
    whether in picking a career
    or a course of study
  • 12:49 - 12:51
    or just in learning new material,
  • 12:51 - 12:54
    can sometimes undermine
    long-term development.
  • 12:54 - 12:58
    And naturally, I think there are as many
    ways to succeed as there are people,
  • 12:58 - 13:02
    but I think we tend only to incentivize
    and encourage the Tiger path,
  • 13:02 - 13:04
    when increasingly in a wicked world,
  • 13:04 - 13:07
    we need people who travel
    the Roger path as well.
  • 13:07 - 13:09
    Or as the eminent physicist
    and mathematician
  • 13:09 - 13:13
    and wonderful writer
    Freeman Dyson put it --
  • 13:13 - 13:16
    and Dyson passed away yesterday,
  • 13:16 - 13:18
    so I hope I'm doing
    his words honor here.
  • 13:18 - 13:19
    As he said,
  • 13:19 - 13:21
    "For a healthy ecosystem,
  • 13:21 - 13:23
    we need both birds and frogs.
  • 13:23 - 13:24
    Frogs are down in the mud,
  • 13:24 - 13:26
    seeing all the granular details.
  • 13:26 - 13:29
    The birds are soaring up above
    not seeing those details,
  • 13:29 - 13:31
    but integrating
    the knowledge of the frogs."
  • 13:31 - 13:32
    And we need both.
  • 13:33 - 13:34
    The problem, Dyson said,
  • 13:34 - 13:37
    is that we're telling
    everyone to become frogs.
  • 13:37 - 13:38
    And I think,
  • 13:38 - 13:40
    in a wicked world,
  • 13:40 - 13:42
    that's increasingly shortsighted.
  • 13:42 - 13:43
    Thank you very much.
  • 13:43 - 13:46
    (Applause)
Title:
Why specializing early doesn't always mean career success
Speaker:
David Epstein
Description:

more » « less
Video Language:
English
Team:
closed TED
Project:
TEDTalks
Duration:
14:00

English subtitles

Revisions Compare revisions