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