The Mathematics of Love | Hannah Fry | TEDxBinghamtonUniversity
-
0:13 - 0:14Thank you very much.
-
0:14 - 0:16So, yes, I'm Hannah Fry,
I am a mathematician, -
0:16 - 0:20and today I want to talk to you
about the mathematics of love. -
0:21 - 0:23Now, I think that we can all agree
-
0:23 - 0:27that mathematicians
are famously excellent at finding love. -
0:28 - 0:31But it's not just
because of our dashing personalities, -
0:31 - 0:35superior conversational skills
and excellent pencil cases. -
0:36 - 0:40It's also because we've actually done
an awful lot of work into the maths -
0:40 - 0:42of how to find the perfect partner.
-
0:42 - 0:46Now, in my favorite paper
on the subject, which is entitled, -
0:46 - 0:49"Why I Don't Have a Girlfriend" -
(Laughter) - -
0:49 - 0:53Peter Backus tries to rate
his chances of finding love. -
0:53 - 0:55Now, Peter's not a very greedy man.
-
0:55 - 0:58Of all of the available women in the U.K.,
-
0:58 - 1:01all Peter's looking for
is somebody who lives near him, -
1:01 - 1:03somebody in the right age range,
-
1:03 - 1:05somebody with a university degree,
-
1:06 - 1:08somebody he's likely to get on well with,
-
1:08 - 1:10somebody who's likely to be attractive,
-
1:10 - 1:13somebody who's likely
to find him attractive. -
1:13 - 1:15(Laughter)
-
1:16 - 1:20And comes up with an estimate
of 26 women in the whole of the UK. -
1:21 - 1:24It's not looking very good, is it Peter?
-
1:24 - 1:26Now, just to put that into perspective,
-
1:26 - 1:29that's about 400 times fewer
than the best estimates -
1:29 - 1:33of how many intelligent
extraterrestrial life forms there are. -
1:33 - 1:38And it also gives Peter
a 1 in 285,000 chance -
1:38 - 1:41of bumping into any one
of these special ladies -
1:41 - 1:42on a given night out.
-
1:42 - 1:44I'd like to think
that's why mathematicians -
1:44 - 1:47don't really bother
going on nights out anymore. -
1:47 - 1:49The thing is that I personally
-
1:49 - 1:52don't subscribe
to such a pessimistic view. -
1:52 - 1:54Because I know,
just as well as all of you do, -
1:54 - 1:57that love doesn't really work like that.
-
1:57 - 2:01Human emotion isn't neatly ordered
and rational and easily predictable. -
2:02 - 2:04But I also know that that doesn't mean
-
2:04 - 2:07that mathematics hasn't got something
that it can offer us -
2:07 - 2:11because, love, as with most of life,
is full of patterns -
2:11 - 2:15and mathematics is, ultimately,
all about the study of patterns. -
2:16 - 2:20Patterns from predicting the weather
to the fluctuations in the stock market, -
2:20 - 2:23to the movement of the planets
or the growth of cities. -
2:23 - 2:26And if we're being honest,
none of those things -
2:26 - 2:30are exactly neatly ordered
and easily predictable, either. -
2:30 - 2:35Because I believe that mathematics
is so powerful that it has the potential -
2:35 - 2:38to offer us a new way of looking
at almost anything. -
2:38 - 2:41Even something as mysterious as love.
-
2:41 - 2:44And so, to try to persuade you
-
2:44 - 2:48of how totally amazing, excellent
and relevant mathematics is, -
2:48 - 2:54I want to give you my top three
mathematically verifiable tips for love. -
2:57 - 2:59Okay, so Top Tip #1:
-
3:01 - 3:04How to win at online dating.
-
3:06 - 3:10So my favorite online dating website
is OkCupid, -
3:10 - 3:13not least because it was started
by a group of mathematicians. -
3:13 - 3:15Now, because they're mathematicians,
-
3:15 - 3:17they have been collecting data
-
3:17 - 3:20on everybody who uses their site
for almost a decade. -
3:20 - 3:22And they've been trying
to search for patterns -
3:22 - 3:24in the way that we talk about ourselves
-
3:24 - 3:26and the way that we interact
with each other -
3:26 - 3:28on an online dating website.
-
3:28 - 3:30And they've come up with some
seriously interesting findings. -
3:30 - 3:32But my particular favorite
-
3:32 - 3:35is that it turns out
that on an online dating website, -
3:35 - 3:40how attractive you are
does not dictate how popular you are, -
3:41 - 3:44and actually, having people think
that you're ugly -
3:44 - 3:47can work to your advantage.
-
3:48 - 3:50Let me show you how this works.
-
3:50 - 3:54In a thankfully voluntary
section of OkCupid, -
3:54 - 3:57you are allowed to rate
how attractive you think people are -
3:57 - 3:59on a scale between 1 and 5.
-
3:59 - 4:03Now, if we compare this score,
the average score, -
4:03 - 4:06to how many messages
a selection of people receive, -
4:06 - 4:07you can begin to get a sense
-
4:07 - 4:11of how attractiveness links to popularity
on an online dating website. -
4:11 - 4:15This is the graph that the OkCupid guy
shave come up with. -
4:15 - 4:19And the important thing to notice
is that it's not totally true -
4:19 - 4:22that the more attractive you are,
the more messages you get. -
4:22 - 4:24OK, there's maybe a bit of a trend there,
-
4:24 - 4:28but it's got an R squared
of absolutely naff all, let's be honest. -
4:28 - 4:32But the question arises then
of what is it about people up here -
4:32 - 4:36who are so much more popular
than people down here, -
4:36 - 4:39even though they have the same
score of attractiveness? -
4:39 - 4:43And the reason why is that it's not just
straight forward looks that are important. -
4:43 - 4:46So let me try to illustrate
their findings with an example. -
4:46 - 4:50So if you take someone like
Portia de Rossi, for example, -
4:50 - 4:54everybody agrees that Portia de Rossi
is a very beautiful woman. -
4:55 - 4:59Nobody thinks that she's ugly,
but she's not a supermodel, either. -
4:59 - 5:03If you compare Portia de Rossi
to someone like Sarah Jessica Parker, -
5:05 - 5:08now, a lot of people,
myself included, I should say, -
5:08 - 5:12think that Sarah Jessica Parker
is seriously fabulous -
5:13 - 5:15and possibly one
of the most beautiful creatures -
5:15 - 5:18to have ever have walked
on the face of the Earth. -
5:18 - 5:22But some other people,
i.e., most of the Internet, -
5:25 - 5:29seem to think that she looks
a bit like a horse. (Laughter) -
5:30 - 5:34Now, I think that if you ask people
how attractive they thought -
5:34 - 5:36Sarah Jessica Parker
or Portia de Rossi were, -
5:36 - 5:39and you ask them to give them
a score between 1 and 5, -
5:39 - 5:42I reckon that they'd average out
to have roughly the same score. -
5:42 - 5:45But the way that people would vote
would be very different. -
5:45 - 5:47So Portia's scores would
all be clustered around the 4 -
5:47 - 5:50because everybody agrees
that she's very beautiful, -
5:50 - 5:52whereas Sarah Jessica Parker
completely divides opinion. -
5:52 - 5:55There'd be a huge spread in her scores.
-
5:55 - 5:57And actually it's this spread that counts.
-
5:57 - 5:59It's this spread
that makes you more popular -
5:59 - 6:02on an online Internet dating website.
-
6:02 - 6:03So what that means then
-
6:03 - 6:06is that if some people
think that you're attractive, -
6:06 - 6:08you're actually better off
-
6:08 - 6:11having some other people think
that you're a massive minger. -
6:12 - 6:15That's much better
than everybody just thinking -
6:15 - 6:17that you're the cute girl next door.
-
6:17 - 6:19Now, I think this begins
makes a bit more sense -
6:19 - 6:23when you think in terms of the people
who are sending these messages. -
6:23 - 6:25So let's say that you think
somebody's attractive, -
6:25 - 6:29but you suspect that other people
won't necessarily be that interested. -
6:29 - 6:31That means there's
less competition for you -
6:31 - 6:34and it's an extra incentive
for you to get in touch. -
6:34 - 6:37Whereas compare that to
if you think somebody is attractive -
6:37 - 6:40but you suspect that everybody
is going to think they're attractive. -
6:40 - 6:44Well, why would you bother
humiliating yourself, let's be honest? -
6:44 - 6:46Here's where the really
interesting part comes. -
6:46 - 6:50Because when people choose the pictures
that they use on an online dating website, -
6:50 - 6:52they often try to minimize the things
-
6:52 - 6:56that they think some people
will find unattractive. -
6:56 - 6:59The classic example is people who are,
perhaps, a little bit overweight -
7:00 - 7:03deliberately choosing
a very cropped photo, -
7:05 - 7:07or bald men, for example,
-
7:07 - 7:10deliberately choosing pictures
where they're wearing hats. -
7:10 - 7:12But actually this is the opposite
of what you should do -
7:12 - 7:14if you want to be successful.
-
7:14 - 7:18You should really, instead, play up to
whatever it is that makes you different, -
7:18 - 7:22even if you think that some people
will find it unattractive. -
7:22 - 7:25Because the people who fancy you
are just going to fancy you anyway, -
7:25 - 7:30and the unimportant losers who don't,
well, they only play up to your advantage. -
7:31 - 7:34Okay, Top Tip #2:
How to pick the perfect partner. -
7:34 - 7:37So let's imagine then
that you're a roaring success -
7:37 - 7:39on the dating scene.
-
7:39 - 7:43But the question arises of how do you then
convert that success -
7:44 - 7:47into longer-term happiness
and in particular, -
7:47 - 7:51how do you decide
when is the right time to settle down? -
7:51 - 7:54Now generally,
it's not advisable to just cash in -
7:54 - 7:56and marry the first person
who comes along -
7:56 - 7:58and shows you any interest at all.
-
7:58 - 8:02But, equally, you don't really
want to leave it too long -
8:02 - 8:05if you want to maximize your chance
of long-term happiness. -
8:05 - 8:08As my favorite author,
Jane Austen, puts it, -
8:08 - 8:11"An unmarried woman of seven and twenty
-
8:11 - 8:14can never hope to feel or inspire
affection again." -
8:14 - 8:16(Laughter)
-
8:17 - 8:20Thanks a lot, Jane.
What do you know about love? -
8:21 - 8:23So the question is then,
-
8:23 - 8:25how do you know when
is the right time to settle down -
8:25 - 8:28given all the people
that you can date in your lifetime? -
8:28 - 8:31Thankfully, there's a rather delicious bit
of mathematics that we can use -
8:31 - 8:34to help us out here, called
optimal stopping theory. -
8:34 - 8:36So let's imagine then,
-
8:36 - 8:38that you start dating when you're 15
-
8:38 - 8:42and ideally, you'd like to be married
by the time that you're 35. -
8:42 - 8:44And there's a number of people
-
8:44 - 8:47that you could potentially
date across your lifetime, -
8:47 - 8:50and they'll be at varying levels
of goodness. -
8:50 - 8:53Now the rules are that once you cash in
and get married, -
8:53 - 8:56you can't look ahead to see
what you could have had, -
8:56 - 8:59and equally, you can't go back
and change your mind. -
8:59 - 9:00In my experience at least,
-
9:00 - 9:03I find that typically people don't
much like being recalled -
9:03 - 9:08years after being passed up
for somebody else, or that's just me. -
9:09 - 9:11So the math says then
that what you should do -
9:11 - 9:14in the first 37 percent
of your dating window, -
9:14 - 9:18you should just reject everybody
as serious marriage potential. -
9:18 - 9:21(Laughter)
-
9:21 - 9:24And then, you should pick
the next person that comes along -
9:24 - 9:27that is better than everybody
that you've seen before. -
9:27 - 9:29So here's the example.
-
9:29 - 9:33Now if you do this, it can be
mathematically proven, in fact, -
9:34 - 9:36that this is the best possible way
-
9:36 - 9:40of maximizing your chances
of finding the perfect partner. -
9:41 - 9:45Now unfortunately, I have to tell you that
this method does come with some risks. -
9:46 - 9:49For instance,
imagine if your perfect partner -
9:50 - 9:53appeared during your first 37 percent.
-
9:53 - 9:56Now, unfortunately,
you'd have to reject them. -
9:56 - 9:59(Laughter)
-
10:00 - 10:02Now, if you're following the maths,
-
10:02 - 10:04I'm afraid no one else comes along
-
10:04 - 10:06that's better than anyone
you've seen before, -
10:06 - 10:09so you have to go on
rejecting everyone and die alone. -
10:09 - 10:12(Laughter)
-
10:12 - 10:16Probably surrounded by cats
nibbling at your remains. -
10:17 - 10:21Okay, another risk is,
let's imagine, instead, -
10:21 - 10:25that the first people that you dated
in your first 37 percent -
10:25 - 10:28are just incredibly dull,
boring, terrible people. -
10:29 - 10:32Now, that's okay,
because you're in your rejection phase - -
10:33 - 10:36that's okay,
because you're in your rejection phase, -
10:36 - 10:38so thats fine, you can reject them.
-
10:39 - 10:41But then imagine, the next person
to come along -
10:41 - 10:45is just marginally less boring,
dull and terrible -
10:46 - 10:48than everybody that you've seen before.
-
10:48 - 10:52Now, if you are following the maths,
I'm afraid you have to marry them -
10:52 - 10:56and end up in a relationship
which is, frankly, suboptimal. -
10:56 - 10:57Sorry about that.
-
10:57 - 11:00But I do think that there's
an opportunity here -
11:00 - 11:02for Hallmark to cash in on
and really cater for this market. -
11:02 - 11:05A Valentine's Day card like this.
(Laughter) -
11:05 - 11:08"My darling husband,
you are marginally less terrible -
11:08 - 11:11than the first 37 percent
of people I dated." -
11:13 - 11:16It's actually more romantic
than I normally manage. -
11:17 - 11:21Okay, so this method doesn't give you
a 100 percent success rate, -
11:21 - 11:25but there's no other possible
strategy that can do any better. -
11:25 - 11:28And actually, in the wild,
there are certain types -
11:28 - 11:31of fish which follow
and employ this exact strategy. -
11:31 - 11:33So they reject every possible suitor
that turns up -
11:33 - 11:37in the first 37 percent
of the mating season, -
11:37 - 11:40and then they pick the next fish
that comes along after that window -
11:40 - 11:43that's, I don't know, bigger and burlier
-
11:43 - 11:45than all of the fish
that they've seen before. -
11:45 - 11:50I also think that subconsciously,
humans, we do sort of do this anyway. -
11:50 - 11:53We give ourselves a little bit of time
to play the field, -
11:53 - 11:56get a feel for the marketplace
or whatever when we're young. -
11:56 - 12:01And then we only start looking seriously
at potential marriage candidates -
12:01 - 12:03once we hit our mid-to-late 20s.
-
12:03 - 12:07I think this is conclusive proof,
if ever it were needed, -
12:07 - 12:11that everybody's brains are prewired
to be just a little bit mathematical. -
12:11 - 12:13Okay, so that was Top Tip #2.
-
12:13 - 12:16Now, Top Tip #3: How to avoid divorce.
-
12:18 - 12:21Okay, so let's imagine then
that you picked your perfect partner -
12:21 - 12:24and you're settling into
a lifelong relationship with them. -
12:25 - 12:29Now, I like to think that everybody
would ideally like to avoid divorce, -
12:29 - 12:32apart from, I don't know,
Piers Morgan's wife, maybe? -
12:35 - 12:37But it's a sad fact of modern life
-
12:37 - 12:40that 1 in 2 marriages
in the States ends in divorce, -
12:40 - 12:44with the rest of the world
not being far behind. -
12:44 - 12:46Now, you can be forgiven, perhaps
-
12:46 - 12:50for thinking that the arguments
that precede a marital breakup -
12:50 - 12:53are not an ideal candidate
for mathematical investigation. -
12:53 - 12:55For one thing, it's very hard to know
-
12:55 - 12:58what you should be measuring
or what you should be quantifying. -
12:58 - 13:04But this didn't stop a psychologist,
John Gottman, who did exactly that. -
13:05 - 13:10Gottman observed hundreds of couples
having a conversation -
13:10 - 13:12and recorded, well,
everything you can think of. -
13:12 - 13:15So he recorded what was said
in the conversation, -
13:15 - 13:17he recorded their skin conductivity,
-
13:17 - 13:19he recorded their facial expressions,
-
13:19 - 13:21their heart rates, their blood pressure,
-
13:21 - 13:26basically everything apart from whether
or not the wife was actually always right, -
13:27 - 13:30which incidentally she totally is.
-
13:31 - 13:33But what Gottman and his team found
-
13:33 - 13:36was that one of the most important
predictors -
13:36 - 13:39for whether or not a couple
is going to get divorced -
13:39 - 13:43was how positive or negative each partner
was being in the conversation. -
13:44 - 13:46Now, couples that were very low-risk
-
13:46 - 13:50scored a lot more positive points
on Gottman's scale than negative. -
13:50 - 13:52Whereas bad relationships,
-
13:52 - 13:55by which I mean, probably
going to get divorced, -
13:55 - 14:00they found themselves
getting into a spiral of negativity. -
14:01 - 14:03Now just by using these very simple ideas,
-
14:03 - 14:05Gottman and his group were able to predict
-
14:05 - 14:08whether a given couple
was going to get divorced -
14:08 - 14:11with a 90 percent accuracy.
-
14:11 - 14:15But it wasn't until he teamed up
with a mathematician, James Murray, -
14:15 - 14:17that they really started to understand
-
14:17 - 14:21what causes these negativity spirals
and how they occur. -
14:21 - 14:23And the results that they found
-
14:23 - 14:26I think are just incredibly
impressively simple and interesting. -
14:28 - 14:30So here they are.
-
14:33 - 14:35I think that should be fairly clear.
-
14:37 - 14:42So these equations, they predict how
the wife or husband is going to respond -
14:43 - 14:45in their next turn of the conversation,
-
14:45 - 14:47how positive or negative
they're going to be. -
14:47 - 14:49And these equations, they depend on
-
14:49 - 14:51the mood of the person
when they're on their own, -
14:51 - 14:54the mood of the person when
they're with their partner, -
14:54 - 14:56but most importantly, they depend on
-
14:56 - 14:59how much the husband and wife
influence one another. -
14:59 - 15:02Now, I think it's important
to point out at this stage, -
15:02 - 15:05that these exact equations
have also been shown -
15:05 - 15:08to be perfectly able at describing
-
15:08 - 15:11what happens between two countries
in an arms race. -
15:12 - 15:15(Laughter)
-
15:16 - 15:19So that - an arguing couple
spiraling into negativity -
15:19 - 15:21and teetering on the brink of divorce -
-
15:21 - 15:26is actually mathematically equivalent
to the beginning of a nuclear war. -
15:26 - 15:28(Laughter)
-
15:28 - 15:31But the really important term
in this equation -
15:31 - 15:33is the influence that people
have on one another, -
15:33 - 15:36and in particular, something called
the negativity threshold. -
15:36 - 15:38Now, the negativity threshold,
-
15:38 - 15:43you can think of as
how annoying the husband can be -
15:43 - 15:47before the wife starts to get
really pissed off, and vice versa. -
15:47 - 15:52Now, I always thought that good marriages
were about compromise and understanding -
15:52 - 15:55and allowing the person
to have the space to be themselves. -
15:55 - 15:58So I would have thought that perhaps
the most successful relationships -
15:58 - 16:01were ones where there was
a really high negativity threshold. -
16:01 - 16:03Where couples let things go
-
16:03 - 16:06and only brought things up
if they really were a big deal. -
16:06 - 16:10But actually, the mathematics
and subsequent findings by the team -
16:10 - 16:13have shown the exact opposite is true.
-
16:13 - 16:15The best couples,
or the most successful couples, -
16:15 - 16:19are the ones with
a really low negativity threshold. -
16:19 - 16:23These are the couples that don't let
anything go unnoticed -
16:23 - 16:26and allow each other
some room to complain. -
16:26 - 16:31These are the couples that are continually
trying to repair their own relationship, -
16:31 - 16:34that have a much more positive
outlook on their marriage. -
16:34 - 16:36Couples that don't let things go
-
16:36 - 16:41and couples that don't let trivial things
end up being a really big deal. -
16:41 - 16:47Now of course, it takes bit more
than just a low negativity threshold -
16:47 - 16:51and not compromising to have
a successful relationship. -
16:51 - 16:54But I think that it's quite interesting
-
16:54 - 16:56to know that there is really
mathematical evidence -
16:56 - 17:00to say that you should never
let the sun go down on your anger. -
17:00 - 17:02So those are my top three tips
-
17:02 - 17:05of how maths can help you
with love and relationships. -
17:05 - 17:07But I hope
that aside from their use as tips, -
17:07 - 17:11they also give you a little bit of insight
into the power of mathematics. -
17:11 - 17:16Because for me, equations and symbols
aren't just a thing. -
17:16 - 17:20They're a voice that speaks out
about the incredible richness of nature -
17:20 - 17:22and the startling simplicity
-
17:22 - 17:27in the patterns that twist and turn
and warp and evolve all around us, -
17:27 - 17:30from how the world works to how we behave.
-
17:30 - 17:32So I hope that perhaps,
for just a couple of you, -
17:32 - 17:34a little bit of insight into
the mathematics of love -
17:34 - 17:38can persuade you to have a little bit
more love for mathematics. -
17:38 - 17:39Thank you.
-
17:39 - 17:41(Applause)
- Title:
- The Mathematics of Love | Hannah Fry | TEDxBinghamtonUniversity
- Description:
-
Finding the right mate is no cakewalk -- but is it even mathematically likely? In a charming talk, mathematician Hannah Fry shows patterns in how we look for love, and gives her top three tips (verified by math!) for finding that special someone.
- Video Language:
- English
- Team:
- closed TED
- Project:
- TEDxTalks
- Duration:
- 17:43
Ivana Korom edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity | ||
TED Translators admin edited English subtitles for The Mathematics of Love: Hannah Fry at TEDxBinghamtonUniversity |