8-1-1:The mathematics of love
The mathematics of love
by Hannah Fry
Today I want to talk to you about the mathematics of love. Now, I think that we can all agree that mathematicians are famously excellent at finding love. But it's not just because of our dashing personalities, superior conversational skills and excellent pencil cases. It's also because we've actually done an awful lot of work into the maths of how to find the perfect partner.
Now, in my favorite paper on the subject, which is entitled, "Why I Don't Have a Girlfriend" -- (Laughter) -- Peter Backus tries to rate his chances of finding love. Now, Peter's not a very greedy man. Of all of the available women in the U.K., all Peter's looking for is somebody who lives near him, somebody in the right age range, somebody with a university degree, somebody he's likely to get on well with, somebody who's likely to be attractive, somebody who's likely to find him attractive. (Laughter) And comes up with an estimate of 26 women in the whole of the UK. It's not looking very good, is it Peter? Now, just to put that into perspective, that's about 400 times fewer than the best estimates of how many intelligent extraterrestrial life forms there are. And it also gives Peter a 1 in 285,000 chance of bumping into any one of these special ladies on a given night out. I'd like to think that's why mathematicians don't really bother going on nights out anymore.
The thing is that I personally don't subscribe to such a pessimistic view. Because I know, just as well as all of you do, that love doesn't really work like that. Human emotion isn't neatly ordered and rational and easily predictable. But I also know that that doesn't mean that mathematics hasn't got something that it can offer us because, love, as with most of life, is full of patterns and mathematics is, ultimately, all about the study of patterns. Patterns from predicting the weather to the fluctuations in the stock market, to the movement of the planets or the growth of cities. And if we're being honest, none of those things are exactly neatly ordered and easily predictable, either. Because I believe that mathematics is so powerful that it has the potential to offer us a new way of looking at almost anything. Even something as mysterious as love. And so, to try to persuade you of how totally amazing, excellent and relevant mathematics is, I want to give you my top three mathematically verifiable tips for love.
Okay, so Top Tip #1: How to win at online dating. So my favorite online dating website is OkCupid, not least because it was started by a group of mathematicians. Now, because they're mathematicians, they have been collecting data on everybody who uses their site for almost a decade. And they've been trying to search for patterns in the way that we talk about ourselves and the way that we interact with each other on an online dating website. And they've come up with some seriously interesting findings. But my particular favorite is that it turns out that on an online dating website, how attractive you are does not dictate how popular you are, and actually, having people think that you're ugly can work to your advantage. Let me show you how this works. In a thankfully voluntary section of OkCupid, you are allowed to rate how attractive you think people are on a scale between 1 and 5. Now, if we compare this score, the average score, to how many messages a selection of people receive, you can begin to get a sense of how attractiveness links to popularity on an online dating website.
This is the graph that the OkCupid guys have come up with. And the important thing to notice is that it's not totally true that the more attractive you are, the more messages you get. But the question arises then of what is it about people up here who are so much more popular than people down here, even though they have the same score of attractiveness? And the reason why is that it's not just straightforward looks that are important. So let me try to illustrate their findings with an example. So if you take someone like Portia de Rossi, for example, everybody agrees that Portia de Rossi is a very beautiful woman. Nobody thinks that she's ugly, but she's not a supermodel, either. If you compare Portia de Rossi to someone like Sarah Jessica Parker, now, a lot of people, myself included, I should say, think that Sarah Jessica Parker is seriously fabulous and possibly one of the most beautiful creatures to have ever have walked on the face of the Earth. But some other people, i.e., most of the Internet, seem to think that she looks a bit like a horse. (Laughter) Now, I think that if you ask people how attractive they thought Sarah Jessica Parker or Portia de Rossi were, and you ask them to give them a score between 1 and 5, I reckon that they'd average out to have roughly the same score. But the way that people would vote would be very different. So Portia's scores would all be clustered around the 4 because everybody agrees that she's very beautiful, whereas Sarah Jessica Parker completely divides opinion. There'd be a huge spread in her scores. And actually it's this spread that counts. It's this spread that makes you more popular on an online Internet dating website. So what that means then is that if some people think that you're attractive, you're actually better off having some other people think that you're a massive minger. That's much better than everybody just thinking that you're the cute girl next door.
Now, I think this begins makes a bit more sense when you think in terms of the people who are sending these messages. So let's say that you think somebody's attractive, but you suspect that other people won't necessarily be that interested. That means there's less competition for you and it's an extra incentive for you to get in touch. Whereas compare that to if you think somebody is attractive but you suspect that everybody is going to think they're attractive. Well, why would you bother humiliating yourself, let's be honest? Here's where the really interesting part comes. Because when people choose the pictures that they use on an online dating website, they often try to minimize the things that they think some people will find unattractive. The classic example is people who are, perhaps, a little bit overweight deliberately choosing a very cropped photo, or bald men, for example, deliberately choosing pictures where they're wearing hats. But actually this is the opposite of what you should do if you want to be successful. You should really, instead, play up to whatever it is that makes you different, even if you think that some people will find it unattractive. Because the people who fancy you are just going to fancy you anyway, and the unimportant losers who don't, well, they only play up to your advantage.
Okay, Top Tip #2: How to pick the perfect partner. So let's imagine then that you're a roaring success on the dating scene. But the question arises of how do you then convert that success into longer-term happiness and in particular, how do you decide when is the right time to settle down? Now generally, it's not advisable to just cash in and marry the first person who comes along and shows you any interest at all. But, equally, you don't really want to leave it too long if you want to maximize your chance of long-term happiness. As my favorite author, Jane Austen, puts it, "An unmarried woman of seven and twenty can never hope to feel or inspire affection again." (Laughter) Thanks a lot, Jane. What do you know about love?
So the question is then, how do you know when is the right time to settle down given all the people that you can date in your lifetime? Thankfully, there's a rather delicious bit of mathematics that we can use to help us out here, called optimal stopping theory. So let's imagine then, that you start dating when you're 15 and ideally, you'd like to be married by the time that you're 35. And there's a number of people that you could potentially date across your lifetime, and they'll be at varying levels of goodness. Now the rules are that once you cash in and get married, you can't look ahead to see what you could have had, and equally, you can't go back and change your mind. In my experience at least, I find that typically people don't much like being recalled years after being passed up for somebody else, or that's just me.
So the math says then that what you should do in the first 37 percent of your dating window, you should just reject everybody as serious marriage potential. (Laughter) And then, you should pick the next person that comes along that is better than everybody that you've seen before. So here's the example. Now if you do this, it can be mathematically proven, in fact, that this is the best possible way of maximizing your chances of finding the perfect partner. Now unfortunately, I have to tell you that this method does come with some risks. For instance, imagine if your perfect partner appeared during your first 37 percent. Now, unfortunately, you'd have to reject them. (Laughter) Now, if you're following the maths, I'm afraid no one else comes along that's better than anyone you've seen before, so you have to go on rejecting everyone and die alone. (Laughter) Probably surrounded by cats nibbling at your remains.
Okay, another risk is, let's imagine, instead, that the first people that you dated in your first 37 percent are just incredibly dull, boring, terrible people. Now, that's okay, because you're in your rejection phase, so thats fine, you can reject them. But then imagine, the next person to come along is just marginally less boring, dull and terrible than everybody that you've seen before. Now, if you are following the maths, I'm afraid you have to marry them and end up in a relationship which is, frankly, suboptimal. Sorry about that. But I do think that there's an opportunity here for Hallmark to cash in on and really cater for this market. A Valentine's Day card like this. (Laughter) "My darling husband, you are marginally less terrible than the first 37 percent of people I dated." It's actually more romantic than I normally manage.
Okay, so this method doesn't give you a 100 percent success rate, but there's no other possible strategy that can do any better. And actually, in the wild, there are certain types of fish which follow and employ this exact strategy. So they reject every possible suitor that turns up in the first 37 percent of the mating season, and then they pick the next fish that comes along after that window that's, I don't know, bigger and burlier than all of the fish that they've seen before. I also think that subconsciously, humans, we do sort of do this anyway. We give ourselves a little bit of time to play the field, get a feel for the marketplace or whatever when we're young. And then we only start looking seriously at potential marriage candidates once we hit our mid-to-late 20s. I think this is conclusive proof, if ever it were needed, that everybody's brains are prewired to be just a little bit mathematical.
Okay, so that was Top Tip #2. Now, Top Tip #3: How to avoid divorce. Okay, so let's imagine then that you picked your perfect partner and you're settling into a lifelong relationship with them. Now, I like to think that everybody would ideally like to avoid divorce, apart from, I don't know, Piers Morgan's wife, maybe? But it's a sad fact of modern life that 1 in 2 marriages in the States ends in divorce, with the rest of the world not being far behind. Now, you can be forgiven, perhaps for thinking that the arguments that precede a marital breakup are not an ideal candidate for mathematical investigation. For one thing, it's very hard to know what you should be measuring or what you should be quantifying. But this didn't stop a psychologist, John Gottman, who did exactly that. Gottman observed hundreds of couples having a conversation and recorded, well, everything you can think of. So he recorded what was said in the conversation, he recorded their skin conductivity, he recorded their facial expressions, their heart rates, their blood pressure, basically everything apart from whether or not the wife was actually always right, which incidentally she totally is. But what Gottman and his team found was that one of the most important predictors for whether or not a couple is going to get divorced was how positive or negative each partner was being in the conversation.
Now, couples that were very low-risk scored a lot more positive points on Gottman's scale than negative. Whereas bad relationships, by which I mean, probably going to get divorced, they found themselves getting into a spiral of negativity. Now just by using these very simple ideas, Gottman and his group were able to predict whether a given couple was going to get divorced with a 90 percent accuracy. But it wasn't until he teamed up with a mathematician, James Murray, that they really started to understand what causes these negativity spirals and how they occur. And the results that they found I think are just incredibly impressively simple and interesting. So these equations, they predict how the wife or husband is going to respond in their next turn of the conversation, how positive or negative they're going to be. And these equations, they depend on the mood of the person when they're on their own, the mood of the person when they're with their partner, but most importantly, they depend on how much the husband and wife influence one another.
Now, I think it's important to point out at this stage, that these exact equations have also been shown to be perfectly able at describing what happens between two countries in an arms race. (Laughter) So that -- an arguing couple spiraling into negativity and teetering on the brink of divorce -- is actually mathematically equivalent to the beginning of a nuclear war. (Laughter)
But the really important term in this equation is the influence that people have on one another, and in particular, something called the negativity threshold. Now, the negativity threshold, you can think of as how annoying the husband can be before the wife starts to get really pissed off, and vice versa. Now, I always thought that good marriages were about compromise and understanding and allowing the person to have the space to be themselves. So I would have thought that perhaps the most successful relationships were ones where there was a really high negativity threshold. Where couples let things go and only brought things up if they really were a big deal. But actually, the mathematics and subsequent findings by the team have shown the exact opposite is true. The best couples, or the most successful couples, are the ones with a really low negativity threshold. These are the couples that don't let anything go unnoticed and allow each other some room to complain. These are the couples that are continually trying to repair their own relationship, that have a much more positive outlook on their marriage. Couples that don't let things go and couples that don't let trivial things end up being a really big deal.
Now of course, it takes bit more than just a low negativity threshold and not compromising to have a successful relationship. But I think that it's quite interesting to know that there is really mathematical evidence to say that you should never let the sun go down on your anger.
So those are my top three tips of how maths can help you with love and relationships. But I hope that aside from their use as tips, they also give you a little bit of insight into the power of mathematics. Because for me, equations and symbols aren't just a thing. They're a voice that speaks out about the incredible richness of nature and the startling simplicity in the patterns that twist and turn and warp and evolve all around us, from how the world works to how we behave. So I hope that perhaps, for just a couple of you, a little bit of insight into the mathematics of love can persuade you to have a little bit more love for mathematics. Thank you. (Applause)
8-1-2:Can we build AI without losing control over it?
00:01
I'm going to talk about a failure of intuition that many of us suffer from. It's really a failure to detect a certain kind of danger. I'm going to describe a scenario that I think is both terrifying and likely to occur, and that's not a good combination, as it turns out.And yet rather than be scared, most of you will feel that what I'm talking about is kind of cool.
00:25
I'm going to describe how the gains we make in artificial intelligence could ultimately destroy us. And in fact, I think it's very difficult to see how they won't destroy us or inspire us to destroy ourselves. And yet if you're anything like me, you'll find that it's fun to think about these things. And that response is part of the problem. OK? That response should worry you. And if I were to convince you in this talk that we were likely to suffer a global famine, either because of climate change or some other catastrophe,and that your grandchildren, or their grandchildren, are very likely to live like this, you wouldn't think, "Interesting. I like this TED Talk."
01:09
Famine isn't fun. Death by science fiction, on the other hand, is fun, and one of the things that worries me most about the development of AI at this point is that we seem unable to marshal an appropriate emotional response to the dangers that lie ahead.I am unable to marshal this response, and I'm giving this talk.
01:30
It's as though we stand before two doors. Behind door number one, we stop making progress in building intelligent machines. Our computer hardware and software just stops getting better for some reason. Now take a moment to consider why this might happen. I mean, given how valuable intelligence and automation are, we will continue to improve our technology if we are at all able to. What could stop us from doing this? A full-scale nuclear war? A global pandemic? An asteroid impact? Justin Bieber becoming president of the United States?
02:08
(Laughter)
02:12
The point is, something would have to destroy civilization as we know it. You have to imagine how bad it would have to be to prevent us from making improvements in our technology permanently, generation after generation. Almost by definition, this is the worst thing that's ever happened in human history.
02:32
So the only alternative, and this is what lies behind door number two, is that we continue to improve our intelligent machines year after year after year. At a certain point, we will build machines that are smarter than we are, and once we have machines that are smarter than we are, they will begin to improve themselves. And then we risk what the mathematician IJ Good called an "intelligence explosion," that the process could get away from us.
02:58
Now, this is often caricatured, as I have here, as a fear that armies of malicious robots will attack us. But that isn't the most likely scenario. It's not that our machines will become spontaneously malevolent. The concern is really that we will build machines that are so much more competent than we are that the slightest divergence between their goals and our own could destroy us.
03:23
Just think about how we relate to ants. We don't hate them. We don't go out of our way to harm them. In fact, sometimes we take pains not to harm them. We step over them on the sidewalk. But whenever their presence seriously conflicts with one of our goals,let's say when constructing a building like this one, we annihilate them without a qualm. The concern is that we will one day build machines that, whether they're conscious or not, could treat us with similar disregard.
03:53
Now, I suspect this seems far-fetched to many of you. I bet there are those of you who doubt that superintelligent AI is possible,much less inevitable. But then you must find something wrong with one of the following assumptions. And there are only three of them.
04:11
Intelligence is a matter of information processing in physical systems. Actually, this is a little bit more than an assumption. We have already built narrow intelligence into our machines, and many of these machines perform at a level of superhuman intelligence already. And we know that mere matter can give rise to what is called "general intelligence," an ability to think flexibly across multiple domains, because our brains have managed it. Right? I mean, there's just atoms in here, and as long as we continue to build systems of atoms that display more and more intelligent behavior, we will eventually, unless we are interrupted, we will eventually build general intelligence into our machines.
04:59
It's crucial to realize that the rate of progress doesn't matter, because any progress is enough to get us into the end zone. We don't need Moore's law to continue. We don't need exponential progress. We just need to keep going.
05:13
The second assumption is that we will keep going. We will continue to improve our intelligent machines. And given the value of intelligence -- I mean, intelligence is either the source of everything we value or we need it to safeguard everything we value. It is our most valuable resource. So we want to do this. We have problems that we desperately need to solve. We want to cure diseases like Alzheimer's and cancer. We want to understand economic systems. We want to improve our climate science. So we will do this, if we can. The train is already out of the station, and there's no brake to pull.
05:53
Finally, we don't stand on a peak of intelligence, or anywhere near it, likely. And this really is the crucial insight. This is what makes our situation so precarious, and this is what makes our intuitions about risk so unreliable.
06:11
Now, just consider the smartest person who has ever lived. On almost everyone's shortlist here is John von Neumann. I mean, the impression that von Neumann made on the people around him, and this included the greatest mathematicians and physicists of his time, is fairly well-documented. If only half the stories about him are half true, there's no question he's one of the smartest people who has ever lived. So consider the spectrum of intelligence. Here we have John von Neumann. And then we have you and me.And then we have a chicken.
06:45
(Laughter)
06:47
Sorry, a chicken.
06:48
(Laughter)
06:49
There's no reason for me to make this talk more depressing than it needs to be.
06:53
(Laughter)
06:56
It seems overwhelmingly likely, however, that the spectrum of intelligence extends much further than we currently conceive, and if we build machines that are more intelligent than we are, they will very likely explore this spectrum in ways that we can't imagine,and exceed us in ways that we can't imagine.
07:15
And it's important to recognize that this is true by virtue of speed alone. Right? So imagine if we just built a superintelligent AI that was no smarter than your average team of researchers at Stanford or MIT. Well, electronic circuits function about a million times faster than biochemical ones, so this machine should think about a million times faster than the minds that built it. So you set it running for a week, and it will perform 20,000 years of human-level intellectual work, week after week after week. How could we even understand, much less constrain, a mind making this sort of progress?
07:56
The other thing that's worrying, frankly, is that, imagine the best case scenario. So imagine we hit upon a design of superintelligent AI that has no safety concerns. We have the perfect design the first time around. It's as though we've been handed an oracle that behaves exactly as intended. Well, this machine would be the perfect labor-saving device. It can design the machine that can build the machine that can do any physical work, powered by sunlight, more or less for the cost of raw materials. So we're talking about the end of human drudgery. We're also talking about the end of most intellectual work.
08:37
So what would apes like ourselves do in this circumstance? Well, we'd be free to play Frisbee and give each other massages. Add some LSD and some questionable wardrobe choices, and the whole world could be like Burning Man.
08:50
(Laughter)
08:54
Now, that might sound pretty good, but ask yourself what would happen under our current economic and political order? It seems likely that we would witness a level of wealth inequality and unemployment that we have never seen before. Absent a willingness to immediately put this new wealth to the service of all humanity, a few trillionaires could grace the covers of our business magazineswhile the rest of the world would be free to starve.
09:22
And what would the Russians or the Chinese do if they heard that some company in Silicon Valley was about to deploy a superintelligent AI? This machine would be capable of waging war, whether terrestrial or cyber, with unprecedented power. This is a winner-take-all scenario. To be six months ahead of the competition here is to be 500,000 years ahead, at a minimum. So it seems that even mere rumors of this kind of breakthrough could cause our species to go berserk.
09:54
Now, one of the most frightening things, in my view, at this moment, are the kinds of things that AI researchers say when they want to be reassuring. And the most common reason we're told not to worry is time. This is all a long way off, don't you know. This is probably 50 or 100 years away. One researcher has said, "Worrying about AI safety is like worrying about overpopulation on Mars."This is the Silicon Valley version of "don't worry your pretty little head about it."
10:26
(Laughter)
10:27
No one seems to notice that referencing the time horizon is a total non sequitur. If intelligence is just a matter of information processing, and we continue to improve our machines, we will produce some form of superintelligence. And we have no idea how long it will take us to create the conditions to do that safely. Let me say that again. We have no idea how long it will take us to create the conditions to do that safely.
11:00
And if you haven't noticed, 50 years is not what it used to be. This is 50 years in months. This is how long we've had the iPhone.This is how long "The Simpsons" has been on television. Fifty years is not that much time to meet one of the greatest challenges our species will ever face. Once again, we seem to be failing to have an appropriate emotional response to what we have every reason to believe is coming.
11:26
The computer scientist Stuart Russell has a nice analogy here. He said, imagine that we received a message from an alien civilization, which read: "People of Earth, we will arrive on your planet in 50 years. Get ready." And now we're just counting down the months until the mothership lands? We would feel a little more urgency than we do.
11:52
Another reason we're told not to worry is that these machines can't help but share our values because they will be literally extensions of ourselves. They'll be grafted onto our brains, and we'll essentially become their limbic systems. Now take a moment to consider that the safest and only prudent path forward, recommended, is to implant this technology directly into our brains.Now, this may in fact be the safest and only prudent path forward, but usually one's safety concerns about a technology have to be pretty much worked out before you stick it inside your head.
12:24
(Laughter)
12:26
The deeper problem is that building superintelligent AI on its own seems likely to be easier than building superintelligent AI and having the completed neuroscience that allows us to seamlessly integrate our minds with it. And given that the companies and governments doing this work are likely to perceive themselves as being in a race against all others, given that to win this race is to win the world, provided you don't destroy it in the next moment, then it seems likely that whatever is easier to do will get done first.
12:58
Now, unfortunately, I don't have a solution to this problem, apart from recommending that more of us think about it. I think we need something like a Manhattan Project on the topic of artificial intelligence. Not to build it, because I think we'll inevitably do that, but to understand how to avoid an arms race and to build it in a way that is aligned with our interests. When you're talking about superintelligent AI that can make changes to itself, it seems that we only have one chance to get the initial conditions right, and even then we will need to absorb the economic and political consequences of getting them right.
13:33
But the moment we admit that information processing is the source of intelligence, that some appropriate computational system is what the basis of intelligence is, and we admit that we will improve these systems continuously, and we admit that the horizon of cognition very likely far exceeds what we currently know, then we have to admit that we are in the process of building some sort of god. Now would be a good time to make sure it's a god we can live with.
14:08
Thank you very much.
14:09
(Applause)
8-1-3:Are athletes really getting faster, better, stronger?
The Olympic motto is "Citius, Altius, Fortius." Faster, Higher, Stronger. And athletes have fulfilled that motto rapidly. The winner of the 2012 Olympic marathon ran two hours and eight minutes. Had he been racing against the winner of the 1904 Olympic marathon, he would have won by nearly an hour and a half. Now we all have this feeling that we're somehow just getting better as a human race, inexorably progressing, but it's not like we've evolved into a new species in a century. So what's going on here? I want to take a look at what's really behind this march of athletic progress.
00:39
In 1936, Jesse Owens held the world record in the 100 meters. Had Jesse Owens been racing last year in the world championships of the 100 meters, when Jamaican sprinter Usain Bolt finished, Owens would have still had 14 feet to go. That's a lot in sprinter land. To give you a sense of how much it is, I want to share with you a demonstration conceived by sports scientist Ross Tucker.Now picture the stadium last year at the world championships of the 100 meters: thousands of fans waiting with baited breath to see Usain Bolt, the fastest man in history; flashbulbs popping as the nine fastest men in the world coil themselves into their blocks.And I want you to pretend that Jesse Owens is in that race. Now close your eyes for a second and picture the race. Bang! The gun goes off. An American sprinter jumps out to the front. Usain Bolt starts to catch him. Usain Bolt passes him, and as the runners come to the finish, you'll hear a beep as each man crosses the line. (Beeps) That's the entire finish of the race. You can open your eyes now. That first beep was Usain Bolt. That last beep was Jesse Owens. Listen to it again. (Beeps) When you think of it like that, it's not that big a difference, is it? And then consider that Usain Bolt started by propelling himself out of blocks down a specially fabricated carpet designed to allow him to travel as fast as humanly possible. Jesse Owens, on the other hand, ran on cinders, the ash from burnt wood, and that soft surface stole far more energy from his legs as he ran. Rather than blocks, Jesse Owens had a gardening trowel that he had to use to dig holes in the cinders to start from. Biomechanical analysis of the speed of Owens' joints shows that had been running on the same surface as Bolt, he wouldn't have been 14 feet behind, he would have been within one stride. Rather than the last beep, Owens would have been the second beep. Listen to it again. (Beeps) That's the difference track surface technology has made, and it's done it throughout the running world.
02:45
Consider a longer event. In 1954, Sir Roger Bannister became the first man to run under four minutes in the mile. Nowadays, college kids do that every year. On rare occasions, a high school kid does it. As of the end of last year, 1,314 men had run under four minutes in the mile, but like Jesse Owens, Sir Roger Bannister ran on soft cinders that stole far more energy from his legs than the synthetic tracks of today. So I consulted biomechanics experts to find out how much slower it is to run on cinders than synthetic tracks, and their consensus that it's one and a half percent slower. So if you apply a one and a half percent slowdown conversion to every man who ran his sub-four mile on a synthetic track, this is what happens. Only 530 are left. If you look at it from that perspective, fewer than ten new men per [year] have joined the sub-four mile club since Sir Roger Bannister. Now, 530 is a lot more than one, and that's partly because there are many more people training today and they're training more intelligently.Even college kids are professional in their training compared to Sir Roger Bannister, who trained for 45 minutes at a time while he ditched gynecology lectures in med school. And that guy who won the 1904 Olympic marathon in three in a half hours, that guy was drinking rat poison and brandy while he ran along the course. That was his idea of a performance-enhancing drug. (Laughter)
04:09
Clearly, athletes have gotten more savvy about performance-enhancing drugs as well, and that's made a difference in some sports at some times, but technology has made a difference in all sports, from faster skis to lighter shoes. Take a look at the record for the 100-meter freestyle swim. The record is always trending downward, but it's punctuated by these steep cliffs. This first cliff, in 1956, is the introduction of the flip turn. Rather than stopping and turning around, athletes could somersault under the water and get going right away in the opposite direction. This second cliff, the introduction of gutters on the side of the pool that allows water to splash off, rather than becoming turbulence that impedes the swimmers as they race. This final cliff, the introduction of full-bodyand low-friction swimsuits.
04:53
Throughout sports, technology has changed the face of performance. In 1972, Eddy Merckx set the record for the longest distance cycled in one hour at 30 miles, 3,774 feet. Now that record improved and improved as bicycles improved and became more aerodynamic all the way until 1996, when it was set at 35 miles, 1,531 feet, nearly five miles farther than Eddy Merckx cycled in 1972. But then in 2000, the International Cycling Union decreed that anyone who wanted to hold that record had to do so with essentially the same equipment that Eddy Merckx used in 1972. Where does the record stand today? 30 miles, 4,657 feet, a grand total of 883 feet farther than Eddy Merckx cycled more than four decades ago. Essentially the entire improvement in this recordwas due to technology.
05:51
Still, technology isn't the only thing pushing athletes forward. While indeed we haven't evolved into a new species in a century, the gene pool within competitive sports most certainly has changed. In the early half of the 20th century, physical education instructors and coaches had the idea that the average body type was the best for all athletic endeavors: medium height, medium weight, no matter the sport. And this showed in athletes' bodies. In the 1920s, the average elite high-jumper and average elite shot-putter were the same exact size. But as that idea started to fade away, as sports scientists and coaches realized that rather than the average body type, you want highly specialized bodies that fit into certain athletic niches, a form of artificial selection took place, a self-sorting for bodies that fit certain sports, and athletes' bodies became more different from one another. Today, rather than the same size as the average elite high jumper, the average elite shot-putter is two and a half inches taller and 130 pounds heavier.And this happened throughout the sports world.
06:51
In fact, if you plot on a height versus mass graph one data point for each of two dozen sports in the first half of the 20th century, it looks like this. There's some dispersal, but it's kind of grouped around that average body type. Then that idea started to go away,and at the same time, digital technology -- first radio, then television and the Internet -- gave millions, or in some cases billions, of people a ticket to consume elite sports performance. The financial incentives and fame and glory afforded elite athletes skyrocketed, and it tipped toward the tiny upper echelon of performance. It accelerated the artificial selection for specialized bodies. And if you plot a data point for these same two dozen sports today, it looks like this. The athletes' bodies have gottenmuch more different from one another. And because this chart looks like the charts that show the expanding universe, with the galaxies flying away from one another, the scientists who discovered it call it "The Big Bang of Body Types."
07:46
In sports where height is prized, like basketball, the tall athletes got taller. In 1983, the National Basketball Association signed a groundbreaking agreement making players partners in the league, entitled to shares of ticket revenues and television contracts.Suddenly, anybody who could be an NBA player wanted to be, and teams started scouring the globe for the bodies that could help them win championships. Almost overnight, the proportion of men in the NBA who are at least seven feet tall doubled to 10 percent. Today, one in 10 men in the NBA is at least seven feet tall, but a seven-foot-tall man is incredibly rare in the general population -- so rare that if you know an American man between the ages of 20 and 40 who is at least seven feet tall, there's a 17 percent chance he's in the NBA right now. (Laughter) That is, find six honest seven footers, one is in the NBA right now. And that's not the only way that NBA players' bodies are unique. This is Leonardo da Vinci's "Vitruvian Man," the ideal proportions, with arm span equal to height. My arm span is exactly equal to my height. Yours is probably very nearly so. But not the average NBA player.The average NBA player is a shade under 6'7", with arms that are seven feet long. Not only are NBA players ridiculously tall, they are ludicrously long. Had Leonardo wanted to draw the Vitruvian NBA Player, he would have needed a rectangle and an ellipse, not a circle and a square.
09:15
So in sports where large size is prized, the large athletes have gotten larger. Conversely, in sports where diminutive stature is an advantage, the small athletes got smaller. The average elite female gymnast shrunk from 5'3" to 4'9" on average over the last 30 years, all the better for their power-to-weight ratio and for spinning in the air. And while the large got larger and the small got smaller, the weird got weirder. The average length of the forearm of a water polo player in relation to their total arm got longer, all the better for a forceful throwing whip. And as the large got larger, small got smaller, and the weird weirder. In swimming, the ideal body type is a long torso and short legs. It's like the long hull of a canoe for speed over the water. And the opposite is advantageous in running. You want long legs and a short torso. And this shows in athletes' bodies today. Here you see Michael Phelps, the greatest swimmer in history, standing next to Hicham El Guerrouj, the world record holder in the mile. These men are seven inches different in height, but because of the body types advantaged in their sports, they wear the same length pants. Seven inches difference in height, these men have the same length legs.
10:25
Now in some cases, the search for bodies that could push athletic performance forward ended up introducing into the competitive world populations of people that weren't previously competing at all, like Kenyan distance runners. We think of Kenyans as being great marathoners. Kenyans think of the Kalenjin tribe as being great marathoners. The Kalenjin make up just 12 percent of the Kenyan population but the vast majority of elite runners. And they happen, on average, to have a certain unique physiology: legs that are very long and very thin at their extremity, and this is because they have their ancestry at very low latitude in a very hot and dry climate, and an evolutionary adaptation to that is limbs that are very long and very thin at the extremity for cooling purposes.It's the same reason that a radiator has long coils, to increase surface area compared to volume to let heat out, and because the leg is like a pendulum, the longer and thinner it is at the extremity, the more energy-efficient it is to swing. To put Kalenjin running success in perspective, consider that 17 American men in history have run faster than two hours and 10 minutes in the marathon.That's a four-minute-and-58-second-per-mile pace. Thirty-two Kalenjin men did that last October. (Laughter) That's from a source population the size of metropolitan Atlanta.
11:44
Still, even changing technology and the changing gene pool in sports don't account for all of the changes in performance. Athletes have a different mindset than they once did. Have you ever seen in a movie when someone gets an electrical shock and they're thrown across a room? There's no explosion there. What's happening when that happens is that the electrical impulse is causingall their muscle fibers to twitch at once, and they're throwing themselves across the room. They're essentially jumping. That's the power that's contained in the human body. But normally we can't access nearly all of it. Our brain acts as a limiter, preventing us from accessing all of our physical resources, because we might hurt ourselves, tearing tendons or ligaments. But the more we learn about how that limiter functions, the more we learn how we can push it back just a bit, in some cases by convincing the brainthat the body won't be in mortal danger by pushing harder. Endurance and ultra-endurance sports serve as a great example. Ultra-endurance was once thought to be harmful to human health, but now we realize that we have all these traits that are perfect for ultra-endurance: no body fur and a glut of sweat glands that keep us cool while running; narrow waists and long legs compared to our frames; large surface area of joints for shock absorption. We have an arch in our foot that acts like a spring, short toes that are better for pushing off than for grasping tree limbs, and when we run, we can turn our torso and our shoulders like this while keeping our heads straight. Our primate cousins can't do that. They have to run like this. And we have big old butt muscles that keep us upright while running. Have you ever looked at an ape's butt? They have no buns because they don't run upright. And as athletes have realized that we're perfectly suited for ultra-endurance, they've taken on feats that would have been unthinkable before, athletes like Spanish endurance racer Kílian Jornet. Here's Kílian running up the Matterhorn. (Laughter) With a sweatshirt there tied around his waist. It's so steep he can't even run here. He's pulling up on a rope. This is a vertical ascent of more than 8,000 feet, and Kílian went up and down in under three hours. Amazing. And talented though he is, Kílian is not a physiological freak. Now that he has done this, other athletes will follow, just as other athletes followed after Sir Roger Bannister ran under four minutes in the mile.
14:04
Changing technology, changing genes, and a changing mindset. Innovation in sports, whether that's new track surfaces or new swimming techniques, the democratization of sport, the spread to new bodies and to new populations around the world, and imagination in sport, an understanding of what the human body is truly capable of, have conspired to make athletes stronger,faster, bolder, and better than ever.
14:30
Thank you very much.
14:32
(Applause)