[Script Info]
Title: 
[Events]
Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text
Dialogue: 0,0:00:00.25,0:00:02.52,Default,,0000,0000,0000,,Today, actually, is\Na very special day for me,
Dialogue: 0,0:00:02.54,0:00:04.66,Default,,0000,0000,0000,,because it is my birthday.
Dialogue: 0,0:00:04.68,0:00:08.66,Default,,0000,0000,0000,,(Applause)
Dialogue: 0,0:00:08.68,0:00:12.12,Default,,0000,0000,0000,,And so, thanks to all of you\Nfor joining the party.
Dialogue: 0,0:00:12.15,0:00:13.31,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:00:13.34,0:00:18.12,Default,,0000,0000,0000,,But every time you throw a party,\Nthere's someone there to spoil it. Right?
Dialogue: 0,0:00:18.15,0:00:19.22,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:00:19.24,0:00:20.60,Default,,0000,0000,0000,,And I'm a physicist,
Dialogue: 0,0:00:20.63,0:00:24.78,Default,,0000,0000,0000,,and this time I brought\Nanother physicist along to do so.
Dialogue: 0,0:00:24.81,0:00:29.37,Default,,0000,0000,0000,,His name is Albert Einstein --\Nalso Albert -- and he's the one who said
Dialogue: 0,0:00:29.39,0:00:34.22,Default,,0000,0000,0000,,that the person who has not made\Nhis great contributions to science
Dialogue: 0,0:00:34.25,0:00:35.81,Default,,0000,0000,0000,,by the age of 30
Dialogue: 0,0:00:35.83,0:00:37.23,Default,,0000,0000,0000,,will never do so.
Dialogue: 0,0:00:37.25,0:00:38.26,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:00:38.29,0:00:40.63,Default,,0000,0000,0000,,Now, you don't need to check Wikipedia
Dialogue: 0,0:00:40.65,0:00:42.22,Default,,0000,0000,0000,,that I'm beyond 30.
Dialogue: 0,0:00:42.24,0:00:43.66,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:00:43.68,0:00:47.29,Default,,0000,0000,0000,,So, effectively, what\Nhe is telling me, and us,
Dialogue: 0,0:00:47.32,0:00:49.86,Default,,0000,0000,0000,,is that when it comes to my science,
Dialogue: 0,0:00:49.88,0:00:51.09,Default,,0000,0000,0000,,I'm deadwood.
Dialogue: 0,0:00:52.08,0:00:57.66,Default,,0000,0000,0000,,Well, luckily, I had my share\Nof luck within my career.
Dialogue: 0,0:00:58.13,0:01:01.95,Default,,0000,0000,0000,,Around age 28, I became\Nvery interested in networks,
Dialogue: 0,0:01:01.98,0:01:06.05,Default,,0000,0000,0000,,and a few years later, we managed\Nto publish a few key papers
Dialogue: 0,0:01:06.08,0:01:10.18,Default,,0000,0000,0000,,that reported the discovery\Nof scale-free networks
Dialogue: 0,0:01:10.20,0:01:14.78,Default,,0000,0000,0000,,and really gave birth to a new discipline\Nthat we call network science today.
Dialogue: 0,0:01:14.80,0:01:18.48,Default,,0000,0000,0000,,And if you really care about it,\Nyou can get a PhD now in network science
Dialogue: 0,0:01:18.50,0:01:20.53,Default,,0000,0000,0000,,in Budapest, in Boston,
Dialogue: 0,0:01:20.56,0:01:22.86,Default,,0000,0000,0000,,and you can study it all over the world.
Dialogue: 0,0:01:23.47,0:01:25.06,Default,,0000,0000,0000,,A few years later,
Dialogue: 0,0:01:25.08,0:01:28.32,Default,,0000,0000,0000,,when I moved to Harvard\Nfirst as a sabbatical,
Dialogue: 0,0:01:28.34,0:01:31.43,Default,,0000,0000,0000,,I became interested\Nin another type of network:
Dialogue: 0,0:01:31.46,0:01:34.48,Default,,0000,0000,0000,,that time, the networks within ourselves,
Dialogue: 0,0:01:34.51,0:01:38.23,Default,,0000,0000,0000,,how the genes and the proteins\Nand the metabolites link to each other
Dialogue: 0,0:01:38.26,0:01:40.75,Default,,0000,0000,0000,,and how they connect to disease.
Dialogue: 0,0:01:41.37,0:01:45.96,Default,,0000,0000,0000,,And that interest led\Nto a major explosion within medicine,
Dialogue: 0,0:01:45.98,0:01:49.96,Default,,0000,0000,0000,,including the Network Medicine\NDivision at Harvard,
Dialogue: 0,0:01:49.99,0:01:53.38,Default,,0000,0000,0000,,that has more than 300 researchers\Nwho are using this perspective
Dialogue: 0,0:01:53.41,0:01:56.30,Default,,0000,0000,0000,,to treat patients and develop new cures.
Dialogue: 0,0:01:57.46,0:01:59.23,Default,,0000,0000,0000,,And a few years ago,
Dialogue: 0,0:01:59.25,0:02:01.78,Default,,0000,0000,0000,,I thought that I would take\Nthis idea of networks
Dialogue: 0,0:02:01.80,0:02:03.57,Default,,0000,0000,0000,,and the expertise we had in networks
Dialogue: 0,0:02:03.59,0:02:04.98,Default,,0000,0000,0000,,in a different area,
Dialogue: 0,0:02:05.01,0:02:06.99,Default,,0000,0000,0000,,that is, to understand success.
Dialogue: 0,0:02:07.70,0:02:08.91,Default,,0000,0000,0000,,And why did we do that?
Dialogue: 0,0:02:08.94,0:02:11.22,Default,,0000,0000,0000,,Well, we thought that, to some degree,
Dialogue: 0,0:02:11.24,0:02:14.62,Default,,0000,0000,0000,,our success is determined\Nby the networks we're part of --
Dialogue: 0,0:02:14.64,0:02:18.49,Default,,0000,0000,0000,,that our networks can push us forward,\Nthey can pull us back.
Dialogue: 0,0:02:18.92,0:02:23.05,Default,,0000,0000,0000,,And I was curious if we could use\Nthe knowledge and big data and expertise
Dialogue: 0,0:02:23.08,0:02:24.48,Default,,0000,0000,0000,,where we develop the networks
Dialogue: 0,0:02:24.50,0:02:27.80,Default,,0000,0000,0000,,to really quantify\Nhow these things happen.
Dialogue: 0,0:02:28.40,0:02:29.75,Default,,0000,0000,0000,,This is a result from that.
Dialogue: 0,0:02:29.77,0:02:32.72,Default,,0000,0000,0000,,What you see here is a network\Nof galleries in museums
Dialogue: 0,0:02:32.74,0:02:34.37,Default,,0000,0000,0000,,that connect to each other.
Dialogue: 0,0:02:34.81,0:02:38.86,Default,,0000,0000,0000,,And through this map\Nthat we mapped out last year,
Dialogue: 0,0:02:38.88,0:02:43.73,Default,,0000,0000,0000,,we are able to predict very accurately\Nthe success of an artist
Dialogue: 0,0:02:43.76,0:02:47.78,Default,,0000,0000,0000,,if you give me the first five exhibits\Nthat he or she had in their career.
Dialogue: 0,0:02:49.40,0:02:52.11,Default,,0000,0000,0000,,Well, as we thought about success,
Dialogue: 0,0:02:52.13,0:02:55.20,Default,,0000,0000,0000,,we realized that success\Nis not only about networks;
Dialogue: 0,0:02:55.22,0:02:57.62,Default,,0000,0000,0000,,there are so many\Nother dimensions to that.
Dialogue: 0,0:02:58.14,0:03:01.39,Default,,0000,0000,0000,,And one of the things\Nwe need for success, obviously,
Dialogue: 0,0:03:01.42,0:03:02.59,Default,,0000,0000,0000,,is performance.
Dialogue: 0,0:03:02.61,0:03:06.11,Default,,0000,0000,0000,,So let's define what's the difference\Nbetween performance and success.
Dialogue: 0,0:03:06.46,0:03:08.46,Default,,0000,0000,0000,,Well, performance is what you do:
Dialogue: 0,0:03:08.49,0:03:11.52,Default,,0000,0000,0000,,how fast you run,\Nwhat kind of paintings you paint,
Dialogue: 0,0:03:11.54,0:03:13.42,Default,,0000,0000,0000,,what kind of papers you publish.
Dialogue: 0,0:03:13.84,0:03:16.45,Default,,0000,0000,0000,,However, in our working definition,
Dialogue: 0,0:03:16.47,0:03:20.68,Default,,0000,0000,0000,,success is about what the community\Nnotices from what you did,
Dialogue: 0,0:03:20.70,0:03:22.31,Default,,0000,0000,0000,,from your performance:
Dialogue: 0,0:03:22.34,0:03:26.47,Default,,0000,0000,0000,,How does it acknowledge it,\Nand how does it reward you for it?
Dialogue: 0,0:03:26.49,0:03:27.68,Default,,0000,0000,0000,,In other terms,
Dialogue: 0,0:03:27.70,0:03:32.30,Default,,0000,0000,0000,,your performance is about you,\Nbut your success is about all of us.
Dialogue: 0,0:03:33.39,0:03:36.73,Default,,0000,0000,0000,,And this was a very\Nimportant shift for us,
Dialogue: 0,0:03:36.75,0:03:40.77,Default,,0000,0000,0000,,because the moment we defined success\Nas being a collective measure
Dialogue: 0,0:03:40.80,0:03:42.90,Default,,0000,0000,0000,,that the community provides to us,
Dialogue: 0,0:03:42.93,0:03:44.44,Default,,0000,0000,0000,,it became measurable,
Dialogue: 0,0:03:44.46,0:03:48.97,Default,,0000,0000,0000,,because if it's in the community,\Nthere are multiple data points about that.
Dialogue: 0,0:03:48.100,0:03:54.28,Default,,0000,0000,0000,,So we go to school,\Nwe exercise, we practice,
Dialogue: 0,0:03:54.30,0:03:57.29,Default,,0000,0000,0000,,because we believe\Nthat performance leads to success.
Dialogue: 0,0:03:57.83,0:03:59.85,Default,,0000,0000,0000,,But the way we actually\Nstarted to explore,
Dialogue: 0,0:03:59.87,0:04:03.40,Default,,0000,0000,0000,,we realized that performance and success\Nare very, very different animals
Dialogue: 0,0:04:03.42,0:04:05.87,Default,,0000,0000,0000,,when it comes to\Nthe mathematics of the problem.
Dialogue: 0,0:04:06.43,0:04:07.86,Default,,0000,0000,0000,,And let me illustrate that.
Dialogue: 0,0:04:08.33,0:04:13.28,Default,,0000,0000,0000,,So what you see here is\Nthe fastest man on earth, Usain Bolt.
Dialogue: 0,0:04:13.83,0:04:17.74,Default,,0000,0000,0000,,And of course, he wins most of\Nthe competitions that he enters.
Dialogue: 0,0:04:18.39,0:04:21.57,Default,,0000,0000,0000,,And we know he's the fastest on earth\Nbecause we have a chronometer
Dialogue: 0,0:04:21.59,0:04:22.75,Default,,0000,0000,0000,,to measure his speed.
Dialogue: 0,0:04:22.78,0:04:26.90,Default,,0000,0000,0000,,Well, what is interesting about him\Nis that when he wins,
Dialogue: 0,0:04:26.92,0:04:32.42,Default,,0000,0000,0000,,he doesn't do so by really significantly\Noutrunning his competition.
Dialogue: 0,0:04:32.44,0:04:36.96,Default,,0000,0000,0000,,He's running at most a percent faster\Nthan the one who loses the race.
Dialogue: 0,0:04:37.63,0:04:41.27,Default,,0000,0000,0000,,And not only does he run only\None percent faster than the second one,
Dialogue: 0,0:04:41.29,0:04:44.14,Default,,0000,0000,0000,,but he doesn't run\N10 times faster than I do --
Dialogue: 0,0:04:44.17,0:04:46.35,Default,,0000,0000,0000,,and I'm not a good runner,\Ntrust me on that.
Dialogue: 0,0:04:46.37,0:04:47.57,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:04:47.59,0:04:51.09,Default,,0000,0000,0000,,And every time we are able\Nto measure performance,
Dialogue: 0,0:04:51.12,0:04:53.17,Default,,0000,0000,0000,,we notice something very interesting;
Dialogue: 0,0:04:53.19,0:04:55.70,Default,,0000,0000,0000,,that is, performance is bounded.
Dialogue: 0,0:04:55.73,0:04:59.48,Default,,0000,0000,0000,,What it means is that there are\Nno huge variations in human performance.
Dialogue: 0,0:04:59.51,0:05:02.94,Default,,0000,0000,0000,,It varies only in a narrow range,
Dialogue: 0,0:05:02.96,0:05:06.24,Default,,0000,0000,0000,,and we do need the chronometer\Nto measure the differences.
Dialogue: 0,0:05:06.27,0:05:09.44,Default,,0000,0000,0000,,This is not to say that we cannot\Nsee the good from the best ones,
Dialogue: 0,0:05:09.46,0:05:12.19,Default,,0000,0000,0000,,but the best ones\Nare very hard to distinguish.
Dialogue: 0,0:05:12.22,0:05:15.21,Default,,0000,0000,0000,,And the problem with that\Nis that most of us work in areas
Dialogue: 0,0:05:15.23,0:05:19.15,Default,,0000,0000,0000,,where we do not have a chronometer\Nto gauge our performance.
Dialogue: 0,0:05:19.18,0:05:20.74,Default,,0000,0000,0000,,Alright, performance is bounded,
Dialogue: 0,0:05:20.77,0:05:24.30,Default,,0000,0000,0000,,there are no huge differences between us\Nwhen it comes to our performance.
Dialogue: 0,0:05:24.32,0:05:25.48,Default,,0000,0000,0000,,How about success?
Dialogue: 0,0:05:25.100,0:05:28.92,Default,,0000,0000,0000,,Well, let's switch to\Na different topic, like books.
Dialogue: 0,0:05:28.95,0:05:33.96,Default,,0000,0000,0000,,One measure of success for writers is\Nhow many people read your work.
Dialogue: 0,0:05:34.66,0:05:39.07,Default,,0000,0000,0000,,And so when my previous book\Ncame out in 2009,
Dialogue: 0,0:05:39.10,0:05:40.100,Default,,0000,0000,0000,,I was in Europe talking with my editor,
Dialogue: 0,0:05:41.02,0:05:43.48,Default,,0000,0000,0000,,and I was interested:\NWho is the competition?
Dialogue: 0,0:05:44.25,0:05:46.99,Default,,0000,0000,0000,,And I had some fabulous ones.
Dialogue: 0,0:05:47.01,0:05:48.18,Default,,0000,0000,0000,,That week --
Dialogue: 0,0:05:48.20,0:05:49.23,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:05:49.25,0:05:52.81,Default,,0000,0000,0000,,Dan Brown came out with "The Lost Symbol,"
Dialogue: 0,0:05:52.83,0:05:55.82,Default,,0000,0000,0000,,and "The Last Song" also came out,
Dialogue: 0,0:05:55.84,0:05:57.27,Default,,0000,0000,0000,,Nicholas Sparks.
Dialogue: 0,0:05:57.29,0:06:00.28,Default,,0000,0000,0000,,And when you just look at the list,
Dialogue: 0,0:06:00.30,0:06:03.76,Default,,0000,0000,0000,,you realize, you know, performance-wise,\Nthere's hardly any difference
Dialogue: 0,0:06:03.78,0:06:05.38,Default,,0000,0000,0000,,between these books or mine.
Dialogue: 0,0:06:05.40,0:06:06.58,Default,,0000,0000,0000,,Right?
Dialogue: 0,0:06:06.60,0:06:11.27,Default,,0000,0000,0000,,So maybe if Nicholas Sparks's team\Nworks a little harder,
Dialogue: 0,0:06:11.30,0:06:13.02,Default,,0000,0000,0000,,he could easily be number one,
Dialogue: 0,0:06:13.04,0:06:15.94,Default,,0000,0000,0000,,because it's almost by accident\Nwho ended up at the top.
Dialogue: 0,0:06:16.49,0:06:19.64,Default,,0000,0000,0000,,So I said, let's look at the numbers --\NI'm a data person, right?
Dialogue: 0,0:06:19.66,0:06:23.98,Default,,0000,0000,0000,,So let's see what were\Nthe sales for Nicholas Sparks.
Dialogue: 0,0:06:24.00,0:06:26.06,Default,,0000,0000,0000,,And it turns out that\Nthat opening weekend,
Dialogue: 0,0:06:26.08,0:06:29.06,Default,,0000,0000,0000,,Nicholas Sparks sold more than\Na hundred thousand copies,
Dialogue: 0,0:06:29.08,0:06:30.79,Default,,0000,0000,0000,,which is an amazing number.
Dialogue: 0,0:06:30.81,0:06:34.21,Default,,0000,0000,0000,,You can actually get to the top\Nof the "New York Times" best-seller list
Dialogue: 0,0:06:34.23,0:06:36.34,Default,,0000,0000,0000,,by selling 10,000 copies a week,
Dialogue: 0,0:06:36.36,0:06:40.12,Default,,0000,0000,0000,,so he tenfold overcame\Nwhat he needed to be number one.
Dialogue: 0,0:06:40.14,0:06:41.57,Default,,0000,0000,0000,,Yet he wasn't number one.
Dialogue: 0,0:06:41.60,0:06:42.90,Default,,0000,0000,0000,,Why?
Dialogue: 0,0:06:42.93,0:06:47.00,Default,,0000,0000,0000,,Because there was Dan Brown,\Nwho sold 1.2 million copies that weekend.
Dialogue: 0,0:06:47.03,0:06:49.16,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:06:49.19,0:06:53.16,Default,,0000,0000,0000,,And the reason I like this number\Nis because it shows that, really,
Dialogue: 0,0:06:53.18,0:06:56.91,Default,,0000,0000,0000,,when it comes to success, it's unbounded,
Dialogue: 0,0:06:56.94,0:07:02.80,Default,,0000,0000,0000,,that the best doesn't only get\Nslightly more than the second best
Dialogue: 0,0:07:02.82,0:07:05.52,Default,,0000,0000,0000,,but gets orders of magnitude more,
Dialogue: 0,0:07:05.54,0:07:08.34,Default,,0000,0000,0000,,because success is a collective measure.
Dialogue: 0,0:07:08.36,0:07:12.74,Default,,0000,0000,0000,,We give it to them, rather than\Nwe earn it through our performance.
Dialogue: 0,0:07:12.76,0:07:18.14,Default,,0000,0000,0000,,So one of things we realized is that\Nperformance, what we do, is bounded,
Dialogue: 0,0:07:18.16,0:07:20.84,Default,,0000,0000,0000,,but success, which is\Ncollective, is unbounded,
Dialogue: 0,0:07:20.87,0:07:22.18,Default,,0000,0000,0000,,which makes you wonder:
Dialogue: 0,0:07:22.20,0:07:25.12,Default,,0000,0000,0000,,How do you get these\Nhuge differences in success
Dialogue: 0,0:07:25.14,0:07:28.04,Default,,0000,0000,0000,,when you have such tiny\Ndifferences in performance?
Dialogue: 0,0:07:28.54,0:07:32.32,Default,,0000,0000,0000,,And recently, I published a book\Nthat I devoted to that very question.
Dialogue: 0,0:07:32.35,0:07:35.19,Default,,0000,0000,0000,,And they didn't give me enough time\Nto go over all of that,
Dialogue: 0,0:07:35.21,0:07:37.28,Default,,0000,0000,0000,,so I'm going to go back\Nto the question of,
Dialogue: 0,0:07:37.31,0:07:40.44,Default,,0000,0000,0000,,alright, you have success;\Nwhen should that appear?
Dialogue: 0,0:07:40.46,0:07:44.22,Default,,0000,0000,0000,,So let's go back to the party spoiler\Nand ask ourselves:
Dialogue: 0,0:07:45.22,0:07:48.55,Default,,0000,0000,0000,,Why did Einstein make\Nthis ridiculous statement,
Dialogue: 0,0:07:48.58,0:07:51.73,Default,,0000,0000,0000,,that only before 30\Nyou could actually be creative?
Dialogue: 0,0:07:51.76,0:07:56.44,Default,,0000,0000,0000,,Well, because he looked around himself\Nand he saw all these fabulous physicists
Dialogue: 0,0:07:56.46,0:07:59.05,Default,,0000,0000,0000,,that created quantum mechanics\Nand modern physics,
Dialogue: 0,0:07:59.07,0:08:02.81,Default,,0000,0000,0000,,and they were all in their 20s\Nand early 30s when they did so.
Dialogue: 0,0:08:03.73,0:08:04.95,Default,,0000,0000,0000,,And it's not only him.
Dialogue: 0,0:08:04.97,0:08:06.60,Default,,0000,0000,0000,,It's not only observational bias,
Dialogue: 0,0:08:06.62,0:08:10.62,Default,,0000,0000,0000,,because there's actually\Na whole field of genius research
Dialogue: 0,0:08:10.64,0:08:12.90,Default,,0000,0000,0000,,that has documented the fact that,
Dialogue: 0,0:08:12.92,0:08:16.08,Default,,0000,0000,0000,,if we look at the people\Nwe admire from the past
Dialogue: 0,0:08:16.11,0:08:19.46,Default,,0000,0000,0000,,and then look at what age\Nthey made their biggest contribution,
Dialogue: 0,0:08:19.49,0:08:21.58,Default,,0000,0000,0000,,whether that's music,\Nwhether that's science,
Dialogue: 0,0:08:21.61,0:08:23.23,Default,,0000,0000,0000,,whether that's engineering,
Dialogue: 0,0:08:23.25,0:08:29.37,Default,,0000,0000,0000,,most of them tend to do so\Nin their 20s, 30s, early 40s at most.
Dialogue: 0,0:08:29.91,0:08:32.70,Default,,0000,0000,0000,,But there's a problem\Nwith this genius research.
Dialogue: 0,0:08:33.20,0:08:36.48,Default,,0000,0000,0000,,Well, first of all, it created\Nthe impression to us
Dialogue: 0,0:08:36.50,0:08:39.98,Default,,0000,0000,0000,,that creativity equals youth,
Dialogue: 0,0:08:40.00,0:08:41.61,Default,,0000,0000,0000,,which is painful, right?
Dialogue: 0,0:08:41.64,0:08:43.59,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:08:43.61,0:08:47.70,Default,,0000,0000,0000,,And it also has an observational bias,
Dialogue: 0,0:08:47.72,0:08:52.69,Default,,0000,0000,0000,,because it only looks at geniuses\Nand doesn't look at ordinary scientists
Dialogue: 0,0:08:52.71,0:08:54.68,Default,,0000,0000,0000,,and doesn't look at all of us and ask,
Dialogue: 0,0:08:54.70,0:08:57.88,Default,,0000,0000,0000,,is it really true that creativity\Nvanishes as we age?
Dialogue: 0,0:08:58.38,0:09:00.26,Default,,0000,0000,0000,,So that's exactly what we tried to do,
Dialogue: 0,0:09:00.28,0:09:04.09,Default,,0000,0000,0000,,and this is important for that\Nto actually have references.
Dialogue: 0,0:09:04.11,0:09:06.75,Default,,0000,0000,0000,,So let's look at an ordinary\Nscientist like myself,
Dialogue: 0,0:09:06.78,0:09:08.30,Default,,0000,0000,0000,,and let's look at my career.
Dialogue: 0,0:09:08.32,0:09:11.52,Default,,0000,0000,0000,,So what you see here is all the papers\Nthat I've published
Dialogue: 0,0:09:11.55,0:09:16.66,Default,,0000,0000,0000,,from my very first paper, in 1989;\NI was still in Romania when I did so,
Dialogue: 0,0:09:16.69,0:09:18.28,Default,,0000,0000,0000,,till kind of this year.
Dialogue: 0,0:09:18.94,0:09:21.46,Default,,0000,0000,0000,,And vertically, you see\Nthe impact of the paper,
Dialogue: 0,0:09:21.48,0:09:22.88,Default,,0000,0000,0000,,that is, how many citations,
Dialogue: 0,0:09:22.91,0:09:26.90,Default,,0000,0000,0000,,how many other papers\Nhave been written that cited that work.
Dialogue: 0,0:09:27.40,0:09:28.70,Default,,0000,0000,0000,,And when you look at that,
Dialogue: 0,0:09:28.72,0:09:31.53,Default,,0000,0000,0000,,you see that my career\Nhas roughly three different stages.
Dialogue: 0,0:09:31.56,0:09:33.99,Default,,0000,0000,0000,,I had the first 10 years\Nwhere I had to work a lot
Dialogue: 0,0:09:34.02,0:09:35.29,Default,,0000,0000,0000,,and I don't achieve much.
Dialogue: 0,0:09:35.32,0:09:37.44,Default,,0000,0000,0000,,No one seems to care\Nabout what I do, right?
Dialogue: 0,0:09:37.46,0:09:39.14,Default,,0000,0000,0000,,There's hardly any impact.
Dialogue: 0,0:09:39.16,0:09:40.57,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:09:40.59,0:09:43.48,Default,,0000,0000,0000,,That time, I was doing material science,
Dialogue: 0,0:09:43.50,0:09:47.19,Default,,0000,0000,0000,,and then I kind of discovered\Nfor myself networks
Dialogue: 0,0:09:47.22,0:09:49.16,Default,,0000,0000,0000,,and then started publishing in networks.
Dialogue: 0,0:09:49.19,0:09:52.26,Default,,0000,0000,0000,,And that led from one high-impact\Npaper to the other one.
Dialogue: 0,0:09:52.29,0:09:55.39,Default,,0000,0000,0000,,And it really felt good.\NThat was that stage of my career.
Dialogue: 0,0:09:55.41,0:09:56.70,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:09:56.72,0:09:59.93,Default,,0000,0000,0000,,So the question is,\Nwhat happens right now?
Dialogue: 0,0:10:00.59,0:10:03.83,Default,,0000,0000,0000,,And we don't know, because there\Nhasn't been enough time passed yet
Dialogue: 0,0:10:03.85,0:10:06.84,Default,,0000,0000,0000,,to actually figure out how much impact\Nthose papers will get;
Dialogue: 0,0:10:06.86,0:10:08.09,Default,,0000,0000,0000,,it takes time to acquire.
Dialogue: 0,0:10:08.11,0:10:09.68,Default,,0000,0000,0000,,Well, when you look at the data,
Dialogue: 0,0:10:09.70,0:10:12.56,Default,,0000,0000,0000,,it seems to be that Einstein,\Nthe genius research, is right,
Dialogue: 0,0:10:12.58,0:10:14.39,Default,,0000,0000,0000,,and I'm at that stage of my career.
Dialogue: 0,0:10:14.42,0:10:16.73,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:10:16.75,0:10:22.72,Default,,0000,0000,0000,,So we said, OK, let's figure out\Nhow does this really happen,
Dialogue: 0,0:10:22.75,0:10:24.53,Default,,0000,0000,0000,,first in science.
Dialogue: 0,0:10:24.55,0:10:28.18,Default,,0000,0000,0000,,And in order not to have\Nthe selection bias,
Dialogue: 0,0:10:28.21,0:10:29.54,Default,,0000,0000,0000,,to look only at geniuses,
Dialogue: 0,0:10:29.57,0:10:33.28,Default,,0000,0000,0000,,we ended up reconstructing the career\Nof every single scientist
Dialogue: 0,0:10:33.31,0:10:35.81,Default,,0000,0000,0000,,from 1900 till today
Dialogue: 0,0:10:35.83,0:10:39.54,Default,,0000,0000,0000,,and finding for all scientists\Nwhat was their personal best,
Dialogue: 0,0:10:39.57,0:10:42.38,Default,,0000,0000,0000,,whether they got the Nobel Prize\Nor they never did,
Dialogue: 0,0:10:42.40,0:10:45.81,Default,,0000,0000,0000,,or no one knows what they did,\Neven their personal best.
Dialogue: 0,0:10:45.84,0:10:47.75,Default,,0000,0000,0000,,And that's what you see in this slide.
Dialogue: 0,0:10:47.78,0:10:49.35,Default,,0000,0000,0000,,Each line is a career,
Dialogue: 0,0:10:49.37,0:10:52.38,Default,,0000,0000,0000,,and when you have a light blue dot\Non the top of that career,
Dialogue: 0,0:10:52.40,0:10:54.44,Default,,0000,0000,0000,,it says that was their personal best.
Dialogue: 0,0:10:54.46,0:10:55.62,Default,,0000,0000,0000,,And the question is,
Dialogue: 0,0:10:55.64,0:10:59.21,Default,,0000,0000,0000,,when did they actually make\Ntheir biggest discovery?
Dialogue: 0,0:10:59.23,0:11:00.40,Default,,0000,0000,0000,,To quantify that,
Dialogue: 0,0:11:00.42,0:11:03.80,Default,,0000,0000,0000,,we look at what's the probability\Nthat you make your biggest discovery,
Dialogue: 0,0:11:03.82,0:11:06.50,Default,,0000,0000,0000,,let's say, one, two, three\Nor 10 years into your career?
Dialogue: 0,0:11:06.52,0:11:07.100,Default,,0000,0000,0000,,We're not looking at real age.
Dialogue: 0,0:11:08.02,0:11:10.16,Default,,0000,0000,0000,,We're looking at\Nwhat we call "academic age."
Dialogue: 0,0:11:10.18,0:11:13.43,Default,,0000,0000,0000,,Your academic age starts\Nwhen you publish your first papers.
Dialogue: 0,0:11:13.46,0:11:15.23,Default,,0000,0000,0000,,I know some of you are still babies.
Dialogue: 0,0:11:15.26,0:11:16.66,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:11:16.68,0:11:19.38,Default,,0000,0000,0000,,So let's look at the probability
Dialogue: 0,0:11:19.41,0:11:21.48,Default,,0000,0000,0000,,that you publish\Nyour highest-impact paper.
Dialogue: 0,0:11:21.50,0:11:24.57,Default,,0000,0000,0000,,And what you see is, indeed,\Nthe genius research is right.
Dialogue: 0,0:11:24.59,0:11:27.62,Default,,0000,0000,0000,,Most scientists tend to publish\Ntheir highest-impact paper
Dialogue: 0,0:11:27.64,0:11:30.54,Default,,0000,0000,0000,,in the first 10, 15 years in their career,
Dialogue: 0,0:11:30.56,0:11:33.70,Default,,0000,0000,0000,,and it tanks after that.
Dialogue: 0,0:11:33.72,0:11:38.83,Default,,0000,0000,0000,,It tanks so fast that I'm about --\NI'm exactly 30 years into my career,
Dialogue: 0,0:11:38.85,0:11:42.39,Default,,0000,0000,0000,,and the chance that I will publish a paper\Nthat would have a higher impact
Dialogue: 0,0:11:42.42,0:11:44.36,Default,,0000,0000,0000,,than anything that I did before
Dialogue: 0,0:11:44.38,0:11:45.73,Default,,0000,0000,0000,,is less than one percent.
Dialogue: 0,0:11:45.76,0:11:48.81,Default,,0000,0000,0000,,I am in that stage of my career,\Naccording to this data.
Dialogue: 0,0:11:49.65,0:11:51.49,Default,,0000,0000,0000,,But there's a problem with that.
Dialogue: 0,0:11:51.52,0:11:55.19,Default,,0000,0000,0000,,We're not doing controls properly.
Dialogue: 0,0:11:55.21,0:11:56.63,Default,,0000,0000,0000,,So the control would be,
Dialogue: 0,0:11:56.66,0:12:01.26,Default,,0000,0000,0000,,what would a scientist look like\Nwho makes random contribution to science?
Dialogue: 0,0:12:01.29,0:12:04.28,Default,,0000,0000,0000,,Or what is the productivity\Nof the scientist?
Dialogue: 0,0:12:04.30,0:12:06.31,Default,,0000,0000,0000,,When do they write papers?
Dialogue: 0,0:12:06.34,0:12:08.78,Default,,0000,0000,0000,,So we measured the productivity,
Dialogue: 0,0:12:08.80,0:12:10.86,Default,,0000,0000,0000,,and amazingly, the productivity,
Dialogue: 0,0:12:10.88,0:12:15.01,Default,,0000,0000,0000,,your likelihood of writing a paper\Nin year one, 10 or 20 in your career,
Dialogue: 0,0:12:15.03,0:12:18.64,Default,,0000,0000,0000,,is indistinguishable from the likelihood\Nof having the impact
Dialogue: 0,0:12:18.66,0:12:20.44,Default,,0000,0000,0000,,in that part of your career.
Dialogue: 0,0:12:21.03,0:12:22.81,Default,,0000,0000,0000,,And to make a long story short,
Dialogue: 0,0:12:22.83,0:12:27.06,Default,,0000,0000,0000,,after lots of statistical tests,\Nthere's only one explanation for that,
Dialogue: 0,0:12:27.08,0:12:29.98,Default,,0000,0000,0000,,that really, the way we scientists work
Dialogue: 0,0:12:30.00,0:12:33.64,Default,,0000,0000,0000,,is that every single paper we write,\Nevery project we do,
Dialogue: 0,0:12:33.66,0:12:37.82,Default,,0000,0000,0000,,has exactly the same chance\Nof being our personal best.
Dialogue: 0,0:12:37.84,0:12:42.80,Default,,0000,0000,0000,,That is, discovery is like\Na lottery ticket.
Dialogue: 0,0:12:42.82,0:12:45.17,Default,,0000,0000,0000,,And the more lottery tickets we buy,
Dialogue: 0,0:12:45.20,0:12:46.70,Default,,0000,0000,0000,,the higher our chances.
Dialogue: 0,0:12:46.73,0:12:48.29,Default,,0000,0000,0000,,And it happens to be so
Dialogue: 0,0:12:48.31,0:12:51.03,Default,,0000,0000,0000,,that most scientists buy\Nmost of their lottery tickets
Dialogue: 0,0:12:51.05,0:12:53.51,Default,,0000,0000,0000,,in the first 10, 15 years of their career,
Dialogue: 0,0:12:53.54,0:12:56.95,Default,,0000,0000,0000,,and after that,\Ntheir productivity decreases.
Dialogue: 0,0:12:57.41,0:12:59.50,Default,,0000,0000,0000,,They're not buying\Nany more lottery tickets.
Dialogue: 0,0:12:59.52,0:13:02.96,Default,,0000,0000,0000,,So it looks as if\Nthey would not be creative.
Dialogue: 0,0:13:02.99,0:13:04.99,Default,,0000,0000,0000,,In reality, they stopped trying.
Dialogue: 0,0:13:05.51,0:13:09.42,Default,,0000,0000,0000,,So when we actually put the data together,\Nthe conclusion is very simple:
Dialogue: 0,0:13:09.45,0:13:11.78,Default,,0000,0000,0000,,success can come at any time.
Dialogue: 0,0:13:11.80,0:13:15.54,Default,,0000,0000,0000,,It could be your very first\Nor very last paper of your career.
Dialogue: 0,0:13:15.56,0:13:19.85,Default,,0000,0000,0000,,It's totally random\Nin the space of the projects.
Dialogue: 0,0:13:19.87,0:13:21.80,Default,,0000,0000,0000,,It is the productivity that changes.
Dialogue: 0,0:13:21.83,0:13:23.08,Default,,0000,0000,0000,,Let me illustrate that.
Dialogue: 0,0:13:23.10,0:13:26.37,Default,,0000,0000,0000,,Here is Frank Wilczek,\Nwho got the Nobel Prize in Physics
Dialogue: 0,0:13:26.40,0:13:30.50,Default,,0000,0000,0000,,for the very first paper he ever wrote\Nin his career as a graduate student.
Dialogue: 0,0:13:30.52,0:13:31.53,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:13:31.55,0:13:34.77,Default,,0000,0000,0000,,More interesting is John Fenn,
Dialogue: 0,0:13:34.80,0:13:39.39,Default,,0000,0000,0000,,who, at age 70, was forcefully retired\Nby Yale University.
Dialogue: 0,0:13:39.42,0:13:41.47,Default,,0000,0000,0000,,They shut his lab down,
Dialogue: 0,0:13:41.50,0:13:45.16,Default,,0000,0000,0000,,and at that moment, he moved\Nto Virginia Commonwealth University,
Dialogue: 0,0:13:45.19,0:13:46.97,Default,,0000,0000,0000,,opened another lab,
Dialogue: 0,0:13:46.100,0:13:50.03,Default,,0000,0000,0000,,and it is there, at age 72,\Nthat he published a paper
Dialogue: 0,0:13:50.06,0:13:53.90,Default,,0000,0000,0000,,for which, 15 years later, he got\Nthe Nobel Prize for Chemistry.
Dialogue: 0,0:13:54.94,0:13:57.98,Default,,0000,0000,0000,,And you think, OK,\Nwell, science is special,
Dialogue: 0,0:13:58.01,0:14:01.47,Default,,0000,0000,0000,,but what about other areas\Nwhere we need to be creative?
Dialogue: 0,0:14:01.49,0:14:06.43,Default,,0000,0000,0000,,So let me take another\Ntypical example: entrepreneurship.
Dialogue: 0,0:14:06.83,0:14:08.41,Default,,0000,0000,0000,,Silicon Valley,
Dialogue: 0,0:14:08.44,0:14:10.50,Default,,0000,0000,0000,,the land of the youth, right?
Dialogue: 0,0:14:10.53,0:14:12.12,Default,,0000,0000,0000,,And indeed, when you look at it,
Dialogue: 0,0:14:12.15,0:14:16.79,Default,,0000,0000,0000,,you realize that the biggest awards,\Nthe TechCrunch Awards and other awards,
Dialogue: 0,0:14:16.81,0:14:18.98,Default,,0000,0000,0000,,are all going to people
Dialogue: 0,0:14:19.01,0:14:24.02,Default,,0000,0000,0000,,whose average age\Nis late 20s, very early 30s.
Dialogue: 0,0:14:24.46,0:14:30.07,Default,,0000,0000,0000,,You look at who the VCs give the money to,\Nsome of the biggest VC firms --
Dialogue: 0,0:14:30.09,0:14:32.33,Default,,0000,0000,0000,,all people in their early 30s.
Dialogue: 0,0:14:32.95,0:14:34.22,Default,,0000,0000,0000,,Which, of course, we know;
Dialogue: 0,0:14:34.24,0:14:38.69,Default,,0000,0000,0000,,there is this ethos in Silicon Valley\Nthat youth equals success.
Dialogue: 0,0:14:39.65,0:14:41.84,Default,,0000,0000,0000,,Not when you look at the data,
Dialogue: 0,0:14:41.86,0:14:44.16,Default,,0000,0000,0000,,because it's not only\Nabout forming a company --
Dialogue: 0,0:14:44.19,0:14:47.33,Default,,0000,0000,0000,,forming a company is like productivity,\Ntrying, trying, trying --
Dialogue: 0,0:14:47.35,0:14:50.84,Default,,0000,0000,0000,,when you look at which\Nof these individuals actually put out
Dialogue: 0,0:14:50.86,0:14:53.64,Default,,0000,0000,0000,,a successful company, a successful exit.
Dialogue: 0,0:14:53.67,0:14:57.39,Default,,0000,0000,0000,,And recently, some of our colleagues\Nlooked at exactly that question.
Dialogue: 0,0:14:57.41,0:15:00.57,Default,,0000,0000,0000,,And it turns out that yes,\Nthose in the 20s and 30s
Dialogue: 0,0:15:00.59,0:15:03.94,Default,,0000,0000,0000,,put out a huge number of companies,\Nform lots of companies,
Dialogue: 0,0:15:03.96,0:15:05.49,Default,,0000,0000,0000,,but most of them go bust.
Dialogue: 0,0:15:06.09,0:15:10.28,Default,,0000,0000,0000,,And when you look at the successful exits,\Nwhat you see in this particular plot,
Dialogue: 0,0:15:10.31,0:15:14.00,Default,,0000,0000,0000,,the older you are, the more likely that\Nyou will actually hit the stock market
Dialogue: 0,0:15:14.03,0:15:16.34,Default,,0000,0000,0000,,or the sell the company successfully.
Dialogue: 0,0:15:16.85,0:15:19.96,Default,,0000,0000,0000,,This is so strong, actually,\Nthat if you are in the 50s,
Dialogue: 0,0:15:19.98,0:15:23.57,Default,,0000,0000,0000,,you are twice as likely\Nto actually have a successful exit
Dialogue: 0,0:15:23.60,0:15:25.49,Default,,0000,0000,0000,,than if you are in your 30s.
Dialogue: 0,0:15:26.61,0:15:30.94,Default,,0000,0000,0000,,(Applause)
Dialogue: 0,0:15:31.64,0:15:34.65,Default,,0000,0000,0000,,So in the end, what is it\Nthat we see, actually?
Dialogue: 0,0:15:34.68,0:15:38.76,Default,,0000,0000,0000,,What we see is that creativity has no age.
Dialogue: 0,0:15:38.78,0:15:40.99,Default,,0000,0000,0000,,Productivity does, right?
Dialogue: 0,0:15:41.42,0:15:45.56,Default,,0000,0000,0000,,Which is telling me that\Nat the end of the day,
Dialogue: 0,0:15:45.58,0:15:47.58,Default,,0000,0000,0000,,if you keep trying --
Dialogue: 0,0:15:47.61,0:15:50.01,Default,,0000,0000,0000,,(Laughter)
Dialogue: 0,0:15:50.03,0:15:53.61,Default,,0000,0000,0000,,you could still succeed\Nand succeed over and over.
Dialogue: 0,0:15:53.63,0:15:56.02,Default,,0000,0000,0000,,So my conclusion is very simple:
Dialogue: 0,0:15:56.04,0:15:58.14,Default,,0000,0000,0000,,I am off the stage, back in my lab.
Dialogue: 0,0:15:58.16,0:15:59.33,Default,,0000,0000,0000,,Thank you.
Dialogue: 0,0:15:59.36,0:16:02.67,Default,,0000,0000,0000,,(Applause)