0:00:00.249,0:00:02.515
Today, actually, is[br]a very special day for me,

0:00:02.539,0:00:04.660
because it is my birthday.

0:00:04.684,0:00:08.657
(Applause)

0:00:08.681,0:00:12.122
And so, thanks to all of you[br]for joining the party.

0:00:12.146,0:00:13.313
(Laughter)

0:00:13.337,0:00:18.123
But every time you throw a party,[br]there's someone there to spoil it. Right?

0:00:18.147,0:00:19.219
(Laughter)

0:00:19.243,0:00:20.602
And I'm a physicist,

0:00:20.626,0:00:24.783
and this time I brought[br]another physicist along to do so.

0:00:24.807,0:00:29.369
His name is Albert Einstein --[br]also Albert -- and he's the one who said

0:00:29.393,0:00:34.223
that the person who has not made[br]his great contributions to science

0:00:34.247,0:00:35.806
by the age of 30

0:00:35.830,0:00:37.226
will never do so.

0:00:37.250,0:00:38.262
(Laughter)

0:00:38.286,0:00:40.626
Now, you don't need to check Wikipedia

0:00:40.650,0:00:42.221
that I'm beyond 30.

0:00:42.245,0:00:43.661
(Laughter)

0:00:43.685,0:00:47.291
So, effectively, what[br]he is telling me, and us,

0:00:47.315,0:00:49.859
is that when it comes to my science,

0:00:49.883,0:00:51.086
I'm deadwood.

0:00:52.078,0:00:57.664
Well, luckily, I had my share[br]of luck within my career.

0:00:58.132,0:01:01.954
Around age 28, I became[br]very interested in networks,

0:01:01.978,0:01:06.054
and a few years later, we managed[br]to publish a few key papers

0:01:06.078,0:01:10.175
that reported the discovery[br]of scale-free networks

0:01:10.199,0:01:14.777
and really gave birth to a new discipline[br]that we call network science today.

0:01:14.801,0:01:18.479
And if you really care about it,[br]you can get a PhD now in network science

0:01:18.503,0:01:20.531
in Budapest, in Boston,

0:01:20.555,0:01:22.863
and you can study it all over the world.

0:01:23.466,0:01:25.061
A few years later,

0:01:25.085,0:01:28.315
when I moved to Harvard[br]first as a sabbatical,

0:01:28.339,0:01:31.431
I became interested[br]in another type of networks,

0:01:31.455,0:01:34.482
that time, the networks within ourselves,

0:01:34.506,0:01:38.232
how the genes and the proteins[br]and the metabolites link to each other

0:01:38.256,0:01:40.749
and how they connect to disease.

0:01:41.368,0:01:45.960
And that interest led[br]to a major explosion within medicine,

0:01:45.984,0:01:49.963
including the Network Medicine[br]Division at Harvard,

0:01:49.987,0:01:53.382
that has more than 300 researchers[br]who are using this perspective

0:01:53.406,0:01:56.303
to treat patients and develop new cures.

0:01:57.457,0:01:59.227
And a few years ago,

0:01:59.251,0:02:01.777
I thought that I would take[br]this idea of networks

0:02:01.801,0:02:03.567
and the expertise we had in networks

0:02:03.591,0:02:04.983
in a different area,

0:02:05.007,0:02:06.989
that is, to understand success.

0:02:07.704,0:02:08.914
And why did we do that?

0:02:08.938,0:02:11.219
Well, we thought that, to some degree,

0:02:11.243,0:02:14.620
our success is determined[br]by the networks we're part of --

0:02:14.644,0:02:18.491
that our networks can push us forward,[br]they can pull us back.

0:02:18.925,0:02:23.053
And I was curious if we could use[br]the knowledge and big data and expertise

0:02:23.077,0:02:24.480
where we develop the networks

0:02:24.504,0:02:27.800
to really quantify[br]how these things happen.

0:02:28.404,0:02:29.746
This is a result from that.

0:02:29.770,0:02:32.717
What you see here is a network[br]of galleries in museums

0:02:32.741,0:02:34.373
that connect to each other.

0:02:34.806,0:02:38.861
And through this map[br]that we mapped out last year,

0:02:38.885,0:02:43.733
we are able to predict very accurately[br]the success of an artist

0:02:43.757,0:02:47.778
if you give me the first five exhibits[br]that he or she had in their career.

0:02:49.404,0:02:52.110
Well, as we thought about success,

0:02:52.134,0:02:55.201
we realized that success[br]is not only about networks;

0:02:55.225,0:02:57.621
there are so many[br]other dimensions to that.

0:02:58.145,0:03:01.392
And one of the things[br]we need for success, obviously,

0:03:01.416,0:03:02.586
is performance.

0:03:02.610,0:03:06.114
So let's define what's the difference[br]between performance and success.

0:03:06.465,0:03:08.462
Well, performance is what you do:

0:03:08.486,0:03:11.518
how fast you run,[br]what kind of paintings you paint,

0:03:11.542,0:03:13.423
what kind of papers you publish.

0:03:13.835,0:03:16.449
However, in our working definition,

0:03:16.473,0:03:20.678
success is about what the community[br]notices from what you did,

0:03:20.702,0:03:22.314
from your performance:

0:03:22.338,0:03:26.470
How does it acknowledge it,[br]and how does it reward you for it?

0:03:26.494,0:03:27.676
In other terms,

0:03:27.700,0:03:32.296
your performance is about you,[br]but your success is about all of us.

0:03:33.392,0:03:36.726
And this was a very[br]important shift for us,

0:03:36.750,0:03:40.774
because the moment we defined success[br]as being a collective measure

0:03:40.798,0:03:42.904
that the community provides to us,

0:03:42.928,0:03:44.438
it became measurable,

0:03:44.462,0:03:48.972
because if it's in the community,[br]there are multiple data points about that.

0:03:48.996,0:03:54.276
So we go to school,[br]we exercise, we practice,

0:03:54.300,0:03:57.291
because we believe[br]that performance leads to success.

0:03:57.832,0:03:59.847
But the way we actually[br]started to explore,

0:03:59.871,0:04:03.398
we realized that performance and success[br]are very, very different animals

0:04:03.422,0:04:05.866
when it comes to[br]the mathematics of the problem.

0:04:06.429,0:04:07.861
And let me illustrate that.

0:04:08.329,0:04:13.276
So what you see here is[br]the fastest man on earth, Usain Bolt.

0:04:13.832,0:04:17.742
And of course, he wins most of[br]the competitions that he enters.

0:04:18.393,0:04:21.568
And we know he's the fastest on earth[br]because we have a chronometer

0:04:21.592,0:04:22.752
to measure his speed.

0:04:22.776,0:04:26.895
Well, what is interesting about him[br]is that when he wins,

0:04:26.919,0:04:32.421
he doesn't do so by really significantly[br]outrunning his competition.

0:04:32.445,0:04:36.964
He's running at most a percent faster[br]than the one who loses the race.

0:04:37.631,0:04:41.269
And not only does he run only[br]one percent faster than the second one,

0:04:41.293,0:04:44.142
but he doesn't run[br]10 times faster than I do --

0:04:44.166,0:04:46.347
and I'm not a good runner,[br]trust me on that.

0:04:46.371,0:04:47.568
(Laughter)

0:04:47.592,0:04:51.094
And every time we are able[br]to measure performance,

0:04:51.118,0:04:53.168
we notice something very interesting;

0:04:53.192,0:04:55.703
that is, performance is bounded.

0:04:55.727,0:04:59.484
What it means is that there are[br]no huge variations in human performance.

0:04:59.508,0:05:02.940
It varies only in a narrow range,

0:05:02.964,0:05:06.243
and we do need the chronometer[br]to measure the differences.

0:05:06.267,0:05:09.435
This is not to say that we cannot[br]see the good from the best ones,

0:05:09.459,0:05:12.192
but the best ones[br]are very hard to distinguish.

0:05:12.216,0:05:15.208
And the problem with that[br]is that most of us work in areas

0:05:15.232,0:05:19.154
where we do not have a chronometer[br]to gauge our performance.

0:05:19.178,0:05:20.742
Alright, performance is bounded,

0:05:20.766,0:05:24.298
there are no huge differences between us[br]when it comes to our performance.

0:05:24.322,0:05:25.479
How about success?

0:05:25.995,0:05:28.925
Well, let's switch to[br]a different topic, like books.

0:05:28.949,0:05:33.964
One measure of success for writers is[br]how many people read your work.

0:05:34.662,0:05:39.072
And so when my previous book[br]came out in 2009,

0:05:39.096,0:05:40.998
I was in Europe talking with my editor,

0:05:41.022,0:05:43.484
and I was interested:[br]Who is the competition?

0:05:44.253,0:05:46.988
And I had some fabulous ones.

0:05:47.012,0:05:48.181
That week --

0:05:48.205,0:05:49.229
(Laughter)

0:05:49.253,0:05:52.810
Dan Brown came out with "The Lost Symbol,"

0:05:52.834,0:05:55.816
and "The Last Song" also came out.

0:05:55.840,0:05:57.269
Nicholas Sparks.

0:05:57.293,0:06:00.281
And when you just look at the list,

0:06:00.305,0:06:03.758
you realize, you know, performance-wise,[br]there's hardly any difference

0:06:03.782,0:06:05.380
between these books or mine.

0:06:05.404,0:06:06.579
Right?

0:06:06.603,0:06:11.271
So maybe if Nicholas Sparks's team[br]works a little harder,

0:06:11.295,0:06:13.017
he could easily be number one,

0:06:13.041,0:06:15.939
because it's almost by accident[br]who ended up at the top.

0:06:16.486,0:06:19.639
So I said, let's look at the numbers --[br]I'm a data person, right?

0:06:19.663,0:06:23.981
So let's see what were[br]the sales for Nicholas Sparks.

0:06:24.005,0:06:26.059
And it turns out that[br]that opening weekend,

0:06:26.083,0:06:29.058
Nicholas Sparks sold more than[br]a hundred thousand copies,

0:06:29.082,0:06:30.787
which is an amazing number.

0:06:30.811,0:06:34.207
You can actually get to the top[br]of the "New York Times" best seller list

0:06:34.231,0:06:36.341
by selling 10,000 copies a week,

0:06:36.365,0:06:40.117
so he tenfold overcame[br]what he needed to be number one.

0:06:40.141,0:06:41.571
Yet he wasn't number one.

0:06:41.595,0:06:42.903
Why?

0:06:42.927,0:06:47.005
Because there was Dan Brown,[br]who sold 1.2 million copies that weekend.

0:06:47.029,0:06:49.165
(Laughter)

0:06:49.189,0:06:53.160
And the reason I like this number[br]is because it shows that, really,

0:06:53.184,0:06:56.914
when it comes to success, it's unbounded,

0:06:56.938,0:07:02.799
that the best doesn't only get[br]slightly more than the second best,

0:07:02.823,0:07:05.520
but gets orders of magnitude more,

0:07:05.544,0:07:08.338
because success is a collective measure.

0:07:08.362,0:07:12.738
We give it to them, rather than[br]we earn it through our performance.

0:07:12.762,0:07:18.138
So one of things we realized is that[br]performance, what we do, is bounded,

0:07:18.162,0:07:20.844
but success, which is[br]collective, is unbounded,

0:07:20.868,0:07:22.180
which makes you wonder:

0:07:22.204,0:07:25.115
How do you get these[br]huge differences in success

0:07:25.139,0:07:28.045
when you have such tiny[br]differences in performance?

0:07:28.537,0:07:32.324
And recently, I published a book[br]that I devoted to that very question.

0:07:32.348,0:07:35.187
And they didn't give me enough time[br]to go over all of that,

0:07:35.211,0:07:37.282
so I'm going to go back[br]to the question of,

0:07:37.306,0:07:40.441
alright, you have success;[br]when should that appear?

0:07:40.465,0:07:44.223
So let's go back to the party spoiler[br]and ask ourselves:

0:07:45.215,0:07:48.554
Why did Einstein make[br]this ridiculous statement,

0:07:48.578,0:07:51.734
that only before 30[br]you could actually be creative?

0:07:51.758,0:07:56.438
Well, because he looked around himself[br]and he saw all these fabulous physicists

0:07:56.462,0:07:59.049
that created quantum mechanics[br]and modern physics,

0:07:59.073,0:08:02.809
and they were all in their 20s[br]and early 30s when they did so.

0:08:03.730,0:08:04.950
And it's not only him.

0:08:04.974,0:08:06.597
It's not only observational bias,

0:08:06.621,0:08:10.618
because there's actually[br]a whole field of genius research

0:08:10.642,0:08:12.898
that has documented the fact that,

0:08:12.922,0:08:16.082
if we look at the people[br]we admire from the past

0:08:16.106,0:08:19.464
and then look at what age[br]they made their biggest contribution at,

0:08:19.488,0:08:21.584
whether that's music,[br]whether that's science,

0:08:21.608,0:08:23.227
whether that's engineering,

0:08:23.251,0:08:29.374
most of them tend to do so[br]in their 20s, 30s, early 40s at most.

0:08:29.914,0:08:32.705
But there's a problem[br]with this genius research.

0:08:33.197,0:08:36.477
Well, first of all, it created[br]the impression to us

0:08:36.501,0:08:39.980
that creativity equals youth,

0:08:40.004,0:08:41.614
which is painful, right?

0:08:41.638,0:08:43.589
(Laughter)

0:08:43.613,0:08:47.701
And it also has an observational bias,

0:08:47.725,0:08:52.687
because it only looks at geniuses[br]and doesn't look at ordinary scientists

0:08:52.711,0:08:54.676
and doesn't look at all of us and ask,

0:08:54.700,0:08:57.885
is it really true that creativity[br]vanishes as we age?

0:08:58.382,0:09:00.259
So that's exactly what we tried to do,

0:09:00.283,0:09:04.086
and this is important for that[br]to actually have references.

0:09:04.110,0:09:06.753
So let's look at an ordinary[br]scientist like myself,

0:09:06.777,0:09:08.299
and let's look at my career.

0:09:08.323,0:09:11.525
So what you see here is all the papers[br]that I've published

0:09:11.549,0:09:16.664
from my very first paper, in 1989;[br]I was still in Romania when I did so,

0:09:16.688,0:09:18.281
till kind of this year.

0:09:18.940,0:09:21.458
And vertically, you see[br]the impact of the paper,

0:09:21.482,0:09:22.885
that is, how many citations,

0:09:22.909,0:09:26.897
how many other papers[br]have been written that cited that work.

0:09:27.397,0:09:28.697
And when you look at that,

0:09:28.721,0:09:31.534
you see that my career[br]has roughly three different stages.

0:09:31.558,0:09:33.993
I had the first 10 years[br]where I had to work a lot

0:09:34.017,0:09:35.293
and I don't achieve much.

0:09:35.317,0:09:37.435
No one seems to care[br]about what I do, right?

0:09:37.459,0:09:39.140
There's hardly any impact.

0:09:39.164,0:09:40.568
(Laughter)

0:09:40.592,0:09:43.479
That time, I was doing material science,

0:09:43.503,0:09:47.194
and then I kind of discovered[br]for myself networks

0:09:47.218,0:09:49.165
and then started publishing in networks.

0:09:49.189,0:09:52.262
And that led from one high-impact[br]paper to the other one.

0:09:52.286,0:09:55.390
And it really felt good.[br]That was that stage of my career.

0:09:55.414,0:09:56.696
(Laughter)

0:09:56.720,0:09:59.928
So the question is,[br]what happens right now?

0:10:00.587,0:10:03.826
And we don't know, because there[br]hasn't been enough time passed yet

0:10:03.850,0:10:06.837
to actually figure out how much impact[br]those papers will get;

0:10:06.861,0:10:08.088
it takes time to acquire.

0:10:08.112,0:10:09.681
Well, when you look at the data,

0:10:09.705,0:10:12.559
it seems to be that Einstein,[br]the genius research, is right,

0:10:12.583,0:10:14.394
and I'm at that stage of my career.

0:10:14.418,0:10:16.726
(Laughter)

0:10:16.750,0:10:22.724
So we said, OK, let's figure out[br]how does this really happen,

0:10:22.748,0:10:24.526
first in science.

0:10:24.550,0:10:28.182
And in order not to have[br]the selection bias,

0:10:28.206,0:10:29.543
to look only at geniuses,

0:10:29.567,0:10:33.283
we ended up reconstructing the career[br]of every single scientist

0:10:33.307,0:10:35.809
from 1900 till today

0:10:35.833,0:10:39.545
and finding for all scientists[br]what was their personal best,

0:10:39.569,0:10:42.381
whether they got the Nobel Prize[br]or they never did,

0:10:42.405,0:10:45.812
or no one knows what they did,[br]even their personal best.

0:10:45.836,0:10:47.751
And that's what you see in this slide.

0:10:47.775,0:10:49.348
Each line is a career,

0:10:49.372,0:10:52.375
and when you have a light blue dot[br]on the top of that career,

0:10:52.399,0:10:54.439
it says that was their personal best.

0:10:54.463,0:10:55.618
And the question is,

0:10:55.642,0:10:59.210
when did they actually make[br]their biggest discovery?

0:10:59.234,0:11:00.399
To quantify that,

0:11:00.423,0:11:03.799
we look at what's the probability[br]that you make your biggest discovery,

0:11:03.823,0:11:06.495
let's say, one, two, three[br]or 10 years into your career?

0:11:06.519,0:11:07.999
We're not looking at real age.

0:11:08.023,0:11:10.157
We're looking at[br]what we call "academic age."

0:11:10.181,0:11:13.431
Your academic age starts[br]when you publish your first papers.

0:11:13.455,0:11:15.234
I know some of you are still babies.

0:11:15.258,0:11:16.655
(Laughter)

0:11:16.679,0:11:19.385
So let's look at the probability

0:11:19.409,0:11:21.475
that you publish[br]your highest-impact paper.

0:11:21.499,0:11:24.570
And what you see is, indeed,[br]the genius research is right.

0:11:24.594,0:11:27.618
Most scientists tend to publish[br]their highest-impact paper

0:11:27.642,0:11:30.541
in the first 10, 15 years in their career,

0:11:30.565,0:11:33.698
and it tanks after that.

0:11:33.722,0:11:38.829
It tanks so fast that I'm about --[br]I'm exactly 30 years into my career,

0:11:38.853,0:11:42.393
and the chance that I will publish a paper[br]that would have a higher impact

0:11:42.417,0:11:44.357
than anything that I did before

0:11:44.381,0:11:45.734
is less than one percent.

0:11:45.758,0:11:48.807
I am in that stage of my career,[br]according to this data.

0:11:49.648,0:11:51.491
But there's a problem with that.

0:11:51.515,0:11:55.190
We're not doing controls properly.

0:11:55.214,0:11:56.631
So the control would be,

0:11:56.655,0:12:01.262
what would a scientist look like[br]who makes random contribution to science?

0:12:01.286,0:12:04.281
Or what is the productivity[br]of the scientist?

0:12:04.305,0:12:06.311
When do they write papers?

0:12:06.335,0:12:08.779
So we measured the productivity,

0:12:08.803,0:12:10.855
and amazingly, the productivity,

0:12:10.879,0:12:15.010
your likelihood of writing a paper[br]in year one, 10 or 20 in your career

0:12:15.034,0:12:18.640
is indistinguishable from the likelihood[br]of having the impact

0:12:18.664,0:12:20.439
in that part of your career.

0:12:21.026,0:12:22.809
And to make a long story short,

0:12:22.833,0:12:27.061
after lots of statistical tests,[br]there's only one explanation for that,

0:12:27.085,0:12:29.979
that really, the way we scientists work

0:12:30.003,0:12:33.636
is that every single paper we write,[br]every project we do,

0:12:33.660,0:12:37.820
has exactly the same chance[br]of being our personal best.

0:12:37.844,0:12:42.797
That is, discovery is like[br]a lottery ticket.

0:12:42.821,0:12:45.172
And the more lottery tickets we buy,

0:12:45.196,0:12:46.703
the higher our chances.

0:12:46.727,0:12:48.286
And it happens to be so

0:12:48.310,0:12:51.029
that most scientists buy[br]most of their lottery tickets

0:12:51.053,0:12:53.513
in the first 10, 15 years of their career,

0:12:53.537,0:12:56.950
and after that,[br]their productivity decreases.

0:12:57.411,0:12:59.495
They're not buying[br]any more lottery tickets.

0:12:59.519,0:13:02.963
So it looks as if[br]they would not be creative.

0:13:02.987,0:13:04.986
In reality, they stopped trying.

0:13:05.509,0:13:09.424
So when we actually put the data together,[br]the conclusion is very simple:

0:13:09.448,0:13:11.779
success can come at any time.

0:13:11.803,0:13:15.538
It could be your very first[br]or very last paper of your career.

0:13:15.562,0:13:19.850
It's totally random[br]in the space of the projects.

0:13:19.874,0:13:21.805
It is the productivity that changes.

0:13:21.829,0:13:23.081
Let me illustrate that.

0:13:23.105,0:13:26.374
Here is Frank Wilczek,[br]who got the Nobel Prize in Physics

0:13:26.398,0:13:30.499
for the very first paper he ever wrote[br]in his career as a graduate student.

0:13:30.523,0:13:31.530
(Laughter)

0:13:31.554,0:13:34.772
More interesting is John Fenn,

0:13:34.796,0:13:39.394
who, at age 70, was forcefully retired[br]by Yale University.

0:13:39.418,0:13:41.474
They shut his lab down,

0:13:41.498,0:13:45.164
and at that moment, he moved[br]to Virginia Commonwealth University,

0:13:45.188,0:13:46.974
opened another lab,

0:13:46.998,0:13:50.031
and it is there, at age 72,[br]that he published a paper

0:13:50.055,0:13:53.900
for which, 15 years later, he got[br]the Nobel Prize for Chemistry.

0:13:54.940,0:13:57.982
And you think, OK,[br]well, science is special,

0:13:58.006,0:14:01.469
but what about other areas[br]where we need to be creative?

0:14:01.493,0:14:06.429
So let me take another[br]typical example: entrepreneurship.

0:14:06.834,0:14:08.413
Silicon Valley,

0:14:08.437,0:14:10.503
the land of the youth, right?

0:14:10.527,0:14:12.122
And indeed, when you look at it,

0:14:12.146,0:14:16.788
you realize that the biggest awards,[br]the TechCrunch Awards and other awards,

0:14:16.812,0:14:18.985
are all going to people

0:14:19.009,0:14:24.024
whose average age[br]is late 20s, very early 30s.

0:14:24.465,0:14:30.067
You look at who the VCs give the money to,[br]some of the biggest VC firms --

0:14:30.091,0:14:32.332
all people in their early 30s.

0:14:32.951,0:14:34.216
Which, of course, we know;

0:14:34.240,0:14:38.693
there is this ethos in Silicon Valley[br]that youth equals success.

0:14:39.653,0:14:41.836
Not when you look at the data,

0:14:41.860,0:14:44.164
because it's not only[br]about forming a company --

0:14:44.188,0:14:47.328
forming a company is like productivity,[br]trying, trying, trying --

0:14:47.352,0:14:50.836
when you look at which[br]of these individuals actually put out

0:14:50.860,0:14:53.642
a successful company, a successful exit.

0:14:53.666,0:14:57.386
And recently, some of our colleagues[br]looked at exactly that question.

0:14:57.410,0:15:00.566
And it turns out that yes,[br]those in the 20s and 30s

0:15:00.590,0:15:03.938
put out a huge number of companies,[br]form lots of companies,

0:15:03.962,0:15:05.493
but most of them go bust.

0:15:06.089,0:15:10.284
And when you look at the successful exits,[br]what you see in this particular plot,

0:15:10.308,0:15:14.003
the older you are, the more likely that[br]you will actually hit the stock market

0:15:14.027,0:15:16.339
or the sell the company successfully.

0:15:16.847,0:15:19.960
This is so strong, actually,[br]that if you are in the 50s,

0:15:19.984,0:15:23.572
you are twice as likely[br]to actually have a successful exit

0:15:23.596,0:15:25.486
than if you are in your 30s.

0:15:26.613,0:15:30.938
(Applause)

0:15:31.645,0:15:34.654
So in the end, what is it[br]that we see, actually?

0:15:34.678,0:15:38.761
What we see is that creativity has no age.

0:15:38.785,0:15:40.987
Productivity does, right?

0:15:41.424,0:15:45.559
Which is telling me that[br]at the end of the day,

0:15:45.583,0:15:47.583
if you keep trying --

0:15:47.607,0:15:50.010
(Laughter)

0:15:50.034,0:15:53.606
you could still succeed[br]and succeed over and over.

0:15:53.630,0:15:56.021
So my conclusion is very simple:

0:15:56.045,0:15:58.138
I am off the stage, back in my lab.

0:15:58.162,0:15:59.333
Thank you.

0:15:59.357,0:16:02.666
(Applause)