WEBVTT

00:00:01.623 --> 00:00:04.633
So I'd like to talk about
the development of human potential,

00:00:04.633 --> 00:00:09.747
and I'd like to start with maybe the most
impactful modern story of development.

00:00:09.747 --> 00:00:13.275
Many of you here have probably heard
of the 10,000 hours rule.

00:00:13.551 --> 00:00:15.724
Maybe you even model
your own life after it.

00:00:15.724 --> 00:00:18.458
Basically it's the idea
that to become great in anything,

00:00:18.458 --> 00:00:21.548
it takes 10,000 hours
of focused practice,

00:00:21.548 --> 00:00:23.877
so you'd better get started
as early as possible.

00:00:23.925 --> 00:00:27.290
The poster child
for this story is Tiger Woods.

00:00:27.688 --> 00:00:30.950
His father famously gave him
a putter when he was seven months old.

00:00:31.440 --> 00:00:34.544
At 10 months, he started
imitating his father's swing.

00:00:35.170 --> 00:00:38.291
At two, you can go on YouTube
and see him on national television.

00:00:38.467 --> 00:00:40.347
Fast-forward to the age of 21,

00:00:40.347 --> 00:00:42.161
he's the greatest golfer in the world.

00:00:42.161 --> 00:00:43.829
Quintessential 10,000 hours story.

00:00:43.829 --> 00:00:46.233
Another that features a number
of bestselling books

00:00:46.233 --> 00:00:48.186
is that of the three Polgar sisters,

00:00:48.186 --> 00:00:51.344
whose father decided to teach
them chess in a very technical manner

00:00:51.344 --> 00:00:52.619
from a very early age.

00:00:52.619 --> 00:00:53.958
And really he wanted to show

00:00:53.958 --> 00:00:56.000
that with a head start
in focused practice,

00:00:56.000 --> 00:00:58.207
any child could become
a genius in anything.

00:00:58.529 --> 00:00:59.528
And in fact,

00:00:59.528 --> 00:01:02.577
two of his daughters went on
to become grandmaster chess players.

00:01:02.577 --> 00:01:06.111
So when I became the science writer
at "Sports Illustrated" magazine,

00:01:06.111 --> 00:01:07.360
I got curious.

00:01:07.452 --> 00:01:09.386
If this 10,000 hours rule is correct,

00:01:09.386 --> 00:01:11.980
then we should see that elite
athletes get a head start

00:01:11.980 --> 00:01:13.797
in so-called "deliberate practice."

00:01:13.797 --> 00:01:14.800
This is coached,

00:01:14.800 --> 00:01:16.483
error-correction focused practice,

00:01:16.483 --> 00:01:17.933
not just playing around.

00:01:17.933 --> 00:01:18.933
And in fact,

00:01:18.933 --> 00:01:20.700
when scientists study elite athletes,

00:01:20.700 --> 00:01:23.612
they see that they spend
more time in deliberate practice ...

00:01:23.612 --> 00:01:24.807
not a big surprise.

00:01:24.807 --> 00:01:28.146
When they actually track athletes
over the course of their development,

00:01:28.146 --> 00:01:29.485
the pattern looks like this:

00:01:29.485 --> 00:01:33.125
the future elites actually spend
less time early on in deliberate practice

00:01:33.125 --> 00:01:34.569
in their eventual sport.

00:01:34.713 --> 00:01:37.979
They tend to have what scientists
call a "sampling period,"

00:01:37.979 --> 00:01:40.221
where they try a variety
of physical activities,

00:01:40.221 --> 00:01:42.099
they gain broad, general skills,

00:01:42.099 --> 00:01:44.266
they learn about
their interests and abilities

00:01:44.266 --> 00:01:48.450
and delay specializing until later
than peers who plateau at lower levels.

00:01:49.057 --> 00:01:51.057
And so when I saw that I said,

00:01:51.057 --> 00:01:54.434
"Gosh, that doesn't really comport
with the 10,000 hours rule, does it?"

00:01:54.434 --> 00:01:56.468
So I started to wonder about other domains

00:01:56.468 --> 00:01:59.719
that we associate with obligatory,
early specialization,

00:01:59.719 --> 00:02:00.758
like music.

00:02:00.989 --> 00:02:02.915
Turns out the pattern's often similar.

00:02:02.915 --> 00:02:05.407
This is research from
a world-class music academy,

00:02:05.407 --> 00:02:07.746
and what I want to draw
your attention to is this:

00:02:07.746 --> 00:02:11.500
the exceptional musicians didn't start
spending more time in deliberate practice

00:02:11.500 --> 00:02:12.756
than the average musicians

00:02:12.756 --> 00:02:14.286
until their third instrument.

00:02:14.286 --> 00:02:16.335
They, too, tended to have
a sampling period.

00:02:16.335 --> 00:02:18.845
Even musicians we think of
as famously precocious,

00:02:18.845 --> 00:02:19.945
like Yo-Yo Ma.

00:02:20.108 --> 00:02:21.306
He had a sampling period,

00:02:21.306 --> 00:02:24.132
he just went through it more rapidly
than most musicians do.

00:02:24.167 --> 00:02:27.407
Nonetheless, this research
is almost entirely ignored,

00:02:27.407 --> 00:02:28.670
and much more impactful

00:02:28.670 --> 00:02:31.720
is the first page of the book 
"Battle Hymn of the Tiger Mother,"

00:02:31.720 --> 00:02:34.640
where the author recounts 
assigning her daughter violin.

00:02:34.864 --> 00:02:37.240
Nobody seems to remember
the part later in the book

00:02:37.240 --> 00:02:40.332
where her daughter turns to her
and says, "You picked it, not me,"

00:02:40.332 --> 00:02:41.331
and largely quits.

00:02:41.331 --> 00:02:44.519
So having seen this sort of surprising
pattern in sports and music,

00:02:44.519 --> 00:02:47.498
I started to wonder about domains
that affect even more people,

00:02:47.498 --> 00:02:48.501
like education.

00:02:48.501 --> 00:02:50.368
An economist found a natural experiment

00:02:50.368 --> 00:02:52.738
in the higher-ed systems
of England and Scotland.

00:02:52.738 --> 00:02:55.468
In the period he studied
the systems were very similar

00:02:55.468 --> 00:02:56.470
except in England,

00:02:56.470 --> 00:02:58.955
students had to specialize
in their mid-teen years

00:02:58.955 --> 00:03:01.185
to pick a specific course
of study to apply to,

00:03:01.185 --> 00:03:02.192
whereas in Scotland,

00:03:02.192 --> 00:03:05.285
they could keep trying things
in the university if they wanted to.

00:03:05.285 --> 00:03:06.312
And his question was:

00:03:06.312 --> 00:03:07.969
who wins the trade-off,

00:03:07.969 --> 00:03:09.997
the early of the late specializers?

00:03:09.997 --> 00:03:13.468
And what he saw was that the early
specializers jump out to an income lead

00:03:13.468 --> 00:03:15.606
because they have more
domain-specific skills.

00:03:15.606 --> 00:03:18.181
The late specializers get to try
more different things,

00:03:18.181 --> 00:03:19.230
and when they do pick,

00:03:19.230 --> 00:03:20.230
they have better fit,

00:03:20.230 --> 00:03:22.299
or what economists call "match quality."

00:03:22.299 --> 00:03:24.933
And so their growth rates are faster.

00:03:24.933 --> 00:03:26.125
By six years out,

00:03:26.125 --> 00:03:27.410
they erase that income gap.

00:03:27.776 --> 00:03:30.960
Meanwhile, the early specializers
start quitting their career tracks

00:03:30.960 --> 00:03:32.109
in much higher numbers,

00:03:32.109 --> 00:03:34.588
essentially because they were
made to choose so early

00:03:34.588 --> 00:03:36.444
that they more often made poor choices.

00:03:36.444 --> 00:03:38.644
So the late specializers lose
in the short term

00:03:38.644 --> 00:03:39.644
and win the long run.

00:03:39.644 --> 00:03:42.175
I think if we thought about
career choice like dating,

00:03:42.175 --> 00:03:45.030
we might not pressure people
to settle down quite so quickly.

00:03:45.030 --> 00:03:46.369
So this got me interested --

00:03:46.369 --> 00:03:47.710
seeing this pattern again --

00:03:47.710 --> 00:03:49.710
in exploring the developmental backgrounds

00:03:49.710 --> 00:03:51.621
of people whose work I had long admired.

00:03:51.621 --> 00:03:52.618
Like Duke Ellington,

00:03:52.618 --> 00:03:55.194
who shunned music lessons
as a kid to focus on baseball

00:03:55.194 --> 00:03:56.445
and painting and drawing.

00:03:56.445 --> 00:03:57.686
Or Maryam Mirzakhani,

00:03:57.686 --> 00:03:59.642
who wasn't interested
in math as a girl --

00:03:59.642 --> 00:04:01.277
dreamed of becoming a novelist --

00:04:01.277 --> 00:04:03.758
and went on to become the first
and so far only woman

00:04:03.758 --> 00:04:04.903
to win the Fields Medal,

00:04:04.903 --> 00:04:07.146
the most prestigious prize
in the world in math.

00:04:07.146 --> 00:04:08.196
Or Vincent Van Gogh --

00:04:08.196 --> 00:04:09.490
had five different careers,

00:04:09.490 --> 00:04:11.360
each of which he deemed
his true calling

00:04:11.360 --> 00:04:13.179
before flaming out spectacularly.

00:04:13.275 --> 00:04:17.541
And in his late 20s picked up a book
called "The Guide to the ABCs of Drawing."

00:04:18.140 --> 00:04:19.404
That worked out OK.

00:04:19.896 --> 00:04:23.232
Claude Shannon was an electrical engineer
at the University of Michigan

00:04:23.232 --> 00:04:26.310
who took a philosophy course
just to fulfill a requirement,

00:04:26.310 --> 00:04:29.663
and in it, he learned about 
a near century-old system of logic

00:04:29.663 --> 00:04:32.801
by which true and false statements
could be coded as ones and zeros

00:04:32.801 --> 00:04:34.630
and solved like math problems.

00:04:34.788 --> 00:04:37.206
This led to the development
of binary code,

00:04:37.206 --> 00:04:39.959
which underlies all of our
digital computers today.

00:04:40.199 --> 00:04:41.919
Finally, my own sort of role model,

00:04:41.919 --> 00:04:42.933
Frances Hesselbein --

00:04:42.933 --> 00:04:44.331
this is me with her --

00:04:44.331 --> 00:04:47.549
she took her first professional
job at the age of 54

00:04:47.549 --> 00:04:49.881
and went on to become 
the CEO of the Girl Scouts,

00:04:49.881 --> 00:04:50.937
which she saved.

00:04:50.937 --> 00:04:52.656
She tripled minority membership,

00:04:52.656 --> 00:04:55.533
added 130,000 volunteers,

00:04:55.533 --> 00:04:58.967
and this is one of the proficiency badges
that came out of her tenure --

00:04:58.967 --> 00:05:01.410
it's binary code for girls
learning about computers.

00:05:01.558 --> 00:05:03.562
Today, Frances runs a leadership institute

00:05:03.562 --> 00:05:05.988
where she works every
weekday in Manhattan,

00:05:05.988 --> 00:05:07.420
and she's only 104,

00:05:07.420 --> 00:05:09.230
so who knows what's next.

00:05:09.230 --> 00:05:10.230
(Laughter)

00:05:10.754 --> 00:05:13.564
We never really hear developmental
stories like this, do we?

00:05:13.564 --> 00:05:15.087
We don't hear about the research

00:05:15.087 --> 00:05:18.264
that found that Nobel laureate scientists
are 22 times more likely

00:05:18.264 --> 00:05:19.817
to have a hobby outside of work

00:05:19.817 --> 00:05:21.111
as are typical scientists.

00:05:21.111 --> 00:05:22.110
We never hear that.

00:05:22.110 --> 00:05:24.541
Even when the performers
or the work is very famous,

00:05:24.541 --> 00:05:26.508
we don't hear these
developmental stories.

00:05:26.508 --> 00:05:28.602
For example, here's
an athlete I've followed.

00:05:28.602 --> 00:05:29.949
Here he is at age six,

00:05:29.949 --> 00:05:31.335
wearing a Scottish rugby kit.

00:05:31.335 --> 00:05:32.344
He tried some tennis,

00:05:32.344 --> 00:05:33.339
some skiing,

00:05:33.339 --> 00:05:34.338
wrestling.

00:05:34.338 --> 00:05:37.530
His mother was actually a tennis coach
but she declined to coach him

00:05:37.530 --> 00:05:40.161
because he wouldn't return balls normally.

00:05:40.161 --> 00:05:42.348
He did some basketball,
table tennis, swimming.

00:05:42.348 --> 00:05:45.676
When his coaches wanted to move
him up a level to play with older boys,

00:05:45.676 --> 00:05:48.576
he declined because he just wanted
to talk about pro wrestling

00:05:48.576 --> 00:05:50.103
after practice with his friends.

00:05:50.103 --> 00:05:51.585
And he kept trying more sports:

00:05:51.585 --> 00:05:54.294
handball, volleyball, soccer,
badminton, skateboarding --

00:05:54.294 --> 00:05:56.273
so who is this dabbler?

00:05:56.674 --> 00:05:58.368
This is Roger Federer.

00:05:58.624 --> 00:06:01.984
Every bit as famous
as an adult as Tiger Woods,

00:06:01.984 --> 00:06:05.085
and yet even tennis enthusiasts
don't usually know anything

00:06:05.085 --> 00:06:06.694
about his developmental story.

00:06:06.694 --> 00:06:08.985
Why is that even though it's the norm?

00:06:09.293 --> 00:06:12.148
I think it's partly because the Tiger
story is very dramatic.

00:06:12.488 --> 00:06:14.923
But also because it seems
like this tidy narrative

00:06:14.923 --> 00:06:16.605
that we can extrapolate to anything

00:06:16.605 --> 00:06:19.008
that we want to be good
at in our own lives.

00:06:19.265 --> 00:06:20.965
But that I think is a problem,

00:06:20.965 --> 00:06:24.340
because it turns out that in many ways
golf is a uniquely horrible model

00:06:24.340 --> 00:06:26.552
of almost everything
that humans want to learn.

00:06:26.552 --> 00:06:27.854
(Laughter)

00:06:28.108 --> 00:06:31.152
Golf is the epitome of what
the psychologist Robin Hogarth called

00:06:31.152 --> 00:06:32.585
a "kind" learning environment.

00:06:32.585 --> 00:06:35.784
Kind learning environments
have next steps and goals that are clear,

00:06:35.784 --> 00:06:37.838
rules that are clear and never change --

00:06:37.838 --> 00:06:41.021
when you do something you get feedback
that is quick and accurate;

00:06:41.021 --> 00:06:43.179
work next year will look
like work last year.

00:06:43.363 --> 00:06:44.413
Chess:

00:06:44.413 --> 00:06:46.010
also a kind learning environment.

00:06:46.010 --> 00:06:49.648
The grandmasters' advantage is based
on knowledge of recurring patterns,

00:06:49.648 --> 00:06:51.694
which is also why
it's so easy to automate.

00:06:51.694 --> 00:06:54.921
On the other end of the spectrum
are "wicked" learning environments,

00:06:54.921 --> 00:06:57.035
where next steps and goals
may not be clear.

00:06:57.300 --> 00:06:58.690
Rules may change.

00:06:58.925 --> 00:07:01.451
You may or may not get feedback
when you do something.

00:07:01.451 --> 00:07:02.447
It may be delayed,

00:07:02.447 --> 00:07:03.464
it may be inaccurate

00:07:03.464 --> 00:07:06.059
and work next year may not
look like work last year.

00:07:06.165 --> 00:07:08.207
So which one of these
sounds like the world

00:07:08.207 --> 00:07:10.173
we're increasingly living in?

00:07:10.503 --> 00:07:12.927
In fact, our need to think
in an adaptable manner

00:07:12.927 --> 00:07:15.003
and to keep track of interconnecting parts

00:07:15.003 --> 00:07:17.467
has fundamentally changed our perception

00:07:17.467 --> 00:07:19.289
so that when you look at this diagram,

00:07:19.289 --> 00:07:22.575
the central circle on the right
probably looks larger to you

00:07:22.575 --> 00:07:25.382
because your brain is drawn
to the relationship of the parts

00:07:25.382 --> 00:07:26.422
in the whole,

00:07:26.422 --> 00:07:28.986
whereas someone who hasn't been
exposed to modern work

00:07:28.986 --> 00:07:31.563
with its requirement for adaptable,
conceptual thought,

00:07:31.563 --> 00:07:34.731
will see correctly that the central
circles are the same size.

00:07:35.200 --> 00:07:38.169
So here we are in the wicked work world,

00:07:38.169 --> 00:07:41.584
and there, sometimes
hyperspecialization can backfire badly.

00:07:41.704 --> 00:07:42.706
For example,

00:07:42.706 --> 00:07:44.234
in research in a dozen countries

00:07:44.234 --> 00:07:46.948
that matched people
for their parent's years of education,

00:07:46.948 --> 00:07:48.054
their test scores,

00:07:48.054 --> 00:07:49.522
their own years of education,

00:07:49.522 --> 00:07:52.329
the difference was some got
career-focused education

00:07:52.329 --> 00:07:54.515
and some got broader, general education.

00:07:54.515 --> 00:07:57.230
The pattern was those who got
the career-focused education

00:07:57.230 --> 00:07:59.566
are more likely to be hired
right out of training,

00:07:59.566 --> 00:08:01.565
more likely to make more money right away,

00:08:01.565 --> 00:08:03.949
but so much less adaptable
in a changing work world

00:08:03.949 --> 00:08:06.884
that they spend so much less time
in the workforce overall

00:08:06.884 --> 00:08:09.545
that they win in the short term
and lose in the long run.

00:08:09.810 --> 00:08:13.346
Or consider a famous,
20-year study of experts

00:08:13.346 --> 00:08:15.900
making geopolitical
and economic predictions.

00:08:16.037 --> 00:08:19.769
The worst forecasters
were the most specialized experts.

00:08:20.245 --> 00:08:23.386
Those who'd spent their entire careers
studying one or two problems

00:08:23.386 --> 00:08:26.430
and came to see the whole world
through one lens or mental model.

00:08:26.430 --> 00:08:27.926
Some of them actually got worse

00:08:27.926 --> 00:08:30.116
as they accumulated
experience and credentials.

00:08:30.594 --> 00:08:35.289
The best forecasters were simply
bright people with wide-ranging interests.

00:08:35.862 --> 00:08:36.906
Now in some domains,

00:08:36.906 --> 00:08:37.968
like medicine,

00:08:37.968 --> 00:08:41.060
increasing specialization has been
both inevitable and beneficial.

00:08:41.060 --> 00:08:42.064
No question about it.

00:08:42.064 --> 00:08:43.920
And yet it's been a double-edged sword.

00:08:43.920 --> 00:08:44.916
A few years ago,

00:08:44.916 --> 00:08:47.726
one of the most popular surgeries
in the world for knee pain

00:08:47.726 --> 00:08:49.681
was tested in a placebo-controlled trial.

00:08:49.681 --> 00:08:51.851
Some of the patients got sham surgery.

00:08:51.851 --> 00:08:53.804
That means the surgeons make an incision,

00:08:53.804 --> 00:08:55.943
they bang around like
they're doing something,

00:08:55.943 --> 00:08:57.565
then they sew the patient back up.

00:08:57.565 --> 00:08:59.004
That performed just as a well.

00:08:59.004 --> 00:09:02.116
And yet surgeons who specialize
in the procedure continue to do it

00:09:02.116 --> 00:09:03.242
by the millions.

00:09:04.065 --> 00:09:08.183
So if hyperspecialization isn't always
the trick in a wicked world, what is?

00:09:08.332 --> 00:09:09.996
That can be difficult to talk about

00:09:09.996 --> 00:09:12.146
because it doesn't
always look like this path.

00:09:12.146 --> 00:09:14.381
Sometimes it looks like
meandering or zigzagging

00:09:14.381 --> 00:09:15.651
or keeping a broader view.

00:09:15.651 --> 00:09:17.273
It can look like getting behind.

00:09:17.416 --> 00:09:20.230
But I want to talk about what
some of those tricks might be.

00:09:20.230 --> 00:09:22.610
If we look at research
on technological innovation,

00:09:22.610 --> 00:09:23.901
it shows that increasingly,

00:09:23.901 --> 00:09:26.610
the most impactful patents
are not authored by individuals

00:09:26.610 --> 00:09:29.491
who drill deeper, deeper, deeper
into one area of technology,

00:09:29.491 --> 00:09:31.532
as classified by the US Patent Office,

00:09:31.532 --> 00:09:34.726
but rather by teams
that include individuals

00:09:34.726 --> 00:09:38.016
who have worked across a large number
of different technology classes

00:09:38.016 --> 00:09:40.162
and often merge things
from different domains.

00:09:40.162 --> 00:09:41.653
Someone whose work I've admired

00:09:41.653 --> 00:09:43.657
who was sort of
on the forefront of this --

00:09:43.657 --> 00:09:45.605
a Japanese man named Gunpei Yokoi.

00:09:45.605 --> 00:09:48.405
Yokoi didn't score well
on his electronics exams at school,

00:09:48.405 --> 00:09:51.687
so he had to settle for a low-tier job
as a machine maintenance worker

00:09:51.687 --> 00:09:53.491
at a playing card company in Kyoto.

00:09:53.676 --> 00:09:56.640
He realized he wasn't equipped
to work on the cutting edge,

00:09:56.640 --> 00:09:59.702
but that there was so much
information easily available

00:09:59.702 --> 00:10:02.657
that maybe he could combine things
that were already well-known

00:10:02.657 --> 00:10:05.030
in ways that specialists
were too narrow to see.

00:10:05.370 --> 00:10:08.856
So he combined some well-known technology
from the calculator industry

00:10:08.856 --> 00:10:11.745
with some well-known technology
from the credit card industry

00:10:11.745 --> 00:10:13.197
and made handheld games.

00:10:13.197 --> 00:10:14.486
And they were a hit.

00:10:14.486 --> 00:10:16.790
And it turned this playing card company,

00:10:16.790 --> 00:10:20.327
which was founded in a wooden
storefront in the 19th century,

00:10:20.327 --> 00:10:22.047
into a toy and game operation.

00:10:22.047 --> 00:10:23.242
You may have heard of it;

00:10:23.242 --> 00:10:24.445
It's called Nintendo.

00:10:24.445 --> 00:10:26.374
Yokoi's creative philosophy translated

00:10:26.374 --> 00:10:29.110
to "lateral thinking 
with withered technology;"

00:10:29.110 --> 00:10:31.715
taking well-known technology
and using it in new ways.

00:10:31.836 --> 00:10:33.978
And his magnum opus was this:

00:10:33.978 --> 00:10:35.073
the Game Boy.

00:10:35.073 --> 00:10:37.390
Technological joke in every way.

00:10:37.559 --> 00:10:41.441
And it came out at the same time
as color competitors from Saga and Atari

00:10:41.441 --> 00:10:43.130
and it blew them away

00:10:43.130 --> 00:10:46.417
because Yokoi knew what his
customers cared about wasn't color.

00:10:46.417 --> 00:10:47.813
It was durability,

00:10:47.813 --> 00:10:48.942
portability,

00:10:48.942 --> 00:10:50.081
affordability,

00:10:50.081 --> 00:10:51.078
battery life --

00:10:51.078 --> 00:10:52.133
game selection.

00:10:52.136 --> 00:10:54.613
This is mine that I found
in my parents' basement --

00:10:54.613 --> 00:10:55.797
(Laughter)

00:10:55.797 --> 00:10:57.239
seen better days.

00:10:57.375 --> 00:10:59.088
But you can see the red light is on.

00:10:59.088 --> 00:11:00.948
I flipped it on and played some Tetris,

00:11:00.948 --> 00:11:02.905
which I thought was especially impressive

00:11:02.905 --> 00:11:05.288
because the batteries had expired
in 2007 and 2013.

00:11:05.288 --> 00:11:06.652
(Laughter)

00:11:07.601 --> 00:11:11.213
So this breadth advantage holds
in more subjective realms as well.

00:11:11.213 --> 00:11:14.598
In a fascinating study of what leads
some comic book creators

00:11:14.598 --> 00:11:17.462
to be more likely to make
blockbuster comics,

00:11:17.462 --> 00:11:18.755
a pair of researchers found

00:11:18.755 --> 00:11:22.434
that it was neither the number of years
of experience in the field

00:11:22.434 --> 00:11:25.423
nor the resources of the publisher,

00:11:25.423 --> 00:11:27.526
nor the number of previous comics made.

00:11:27.662 --> 00:11:31.973
It was the number of different genres
that a creator had worked across.

00:11:31.973 --> 00:11:33.387
And interestingly,

00:11:33.387 --> 00:11:37.108
a broad individual
could not be entirely replaced

00:11:37.108 --> 00:11:38.786
by a team of specialists.

00:11:39.240 --> 00:11:42.148
We probably don't make as many
of those people as we could

00:11:42.148 --> 00:11:43.409
because early on,

00:11:43.409 --> 00:11:45.057
they just look like they're behind

00:11:45.057 --> 00:11:48.673
and we don't tend to incentivize anything
that doesn't look like a head start

00:11:48.673 --> 00:11:49.816
or specialization.

00:11:49.816 --> 00:11:52.807
In fact, I think in the well-meaning
drive for a head start,

00:11:52.807 --> 00:11:56.158
we often even counterproductively
short circuit even the way we learn

00:11:56.158 --> 00:11:58.364
new material at a fundamental level.

00:11:58.579 --> 00:11:59.611
In a study last year,

00:11:59.611 --> 00:12:02.514
seventh-grade math classrooms in the US

00:12:02.514 --> 00:12:05.413
were randomly assigned
to different types of learning.

00:12:05.413 --> 00:12:07.928
Some got what's called "blocked practice."

00:12:08.051 --> 00:12:09.811
That's like, you get problem type A,

00:12:09.811 --> 00:12:10.931
AAAAA,

00:12:10.931 --> 00:12:11.932
BBBBB,

00:12:11.835 --> 00:12:12.835
and so on.

00:12:12.835 --> 00:12:14.232
Progress is fast;

00:12:14.232 --> 00:12:15.427
kids are happy;

00:12:15.427 --> 00:12:16.460
everything's great.

00:12:16.460 --> 00:12:20.210
Other classrooms got assigned
to what's called "interleaved practice."

00:12:20.545 --> 00:12:22.642
That's like if you took
all the problem types

00:12:22.642 --> 00:12:23.742
and threw them in a hat

00:12:23.742 --> 00:12:25.074
and drew them out at random.

00:12:25.074 --> 00:12:26.300
Progress is slower;

00:12:26.300 --> 00:12:28.029
kids are more frustrated.

00:12:28.274 --> 00:12:30.975
But instead of learning
how to execute procedures,

00:12:30.975 --> 00:12:34.401
they're learning how to match
a strategy to a type of problem.

00:12:34.645 --> 00:12:36.369
And when the test comes around,

00:12:36.369 --> 00:12:39.697
the interleaved group blew
the block practice group away.

00:12:40.006 --> 00:12:41.233
It wasn't even close.

00:12:41.825 --> 00:12:45.070
Now I found a lot of this research
deeply counterintuitive.

00:12:45.419 --> 00:12:46.778
The idea that a head start,

00:12:46.778 --> 00:12:49.027
whether in picking a career
or a course of study

00:12:49.027 --> 00:12:50.713
or just in learning new material,

00:12:50.713 --> 00:12:53.579
can sometimes undermine
long-term development.

00:12:53.579 --> 00:12:57.704
And naturally, I think there are as many
ways to succeed as there are people,

00:12:57.704 --> 00:13:02.086
but I think we tend only to incentivize
and encourage the Tiger path,

00:13:02.086 --> 00:13:03.805
when increasingly in a wicked world,

00:13:03.805 --> 00:13:06.590
we need people who travel
the Roger path as well.

00:13:06.713 --> 00:13:09.295
Or as the eminent physicist
and mathematician

00:13:09.295 --> 00:13:12.842
and wonderful writer
Freeman Dyson put it --

00:13:12.842 --> 00:13:15.845
and Dyson passed away yesterday,

00:13:15.845 --> 00:13:18.240
so I hope I'm doing
his words honor here.

00:13:18.247 --> 00:13:19.248
As he said,

00:13:19.248 --> 00:13:20.574
"For a healthy ecosystem,

00:13:20.574 --> 00:13:22.565
we need both birds and frogs.

00:13:23.020 --> 00:13:24.256
Frogs are down in the mud,

00:13:24.256 --> 00:13:26.175
seeing all the granular details.

00:13:26.399 --> 00:13:29.108
The birds are soaring up above
not seeing those details,

00:13:29.108 --> 00:13:31.157
but integrating
the knowledge of the frogs."

00:13:31.157 --> 00:13:32.461
And we need both.

00:13:32.515 --> 00:13:34.400
The problem, Dyson said,

00:13:34.400 --> 00:13:36.996
is that we're telling
everyone to become frogs.

00:13:36.996 --> 00:13:38.159
And I think,

00:13:38.159 --> 00:13:39.680
in a wicked world,

00:13:39.680 --> 00:13:41.753
that's increasingly shortsighted.

00:13:42.014 --> 00:13:43.174
Thank you very much.

00:13:43.357 --> 00:13:46.317
(Applause)