The mathematics of love
-
0:01 - 0:05Today I want to talk to you
about the mathematics of love. -
0:05 - 0:07Now, I think that we can all agree
-
0:07 - 0:10that mathematicians
are famously excellent at finding love. -
0:10 - 0:12(Laughter)
-
0:12 - 0:15But it's not just because
of our dashing personalities, -
0:15 - 0:20superior conversational skills
and excellent pencil cases. -
0:20 - 0:24It's also because we've actually done
an awful lot of work into the maths -
0:24 - 0:26of how to find the perfect partner.
-
0:26 - 0:30Now, in my favorite paper
on the subject, which is entitled, -
0:30 - 0:32"Why I Don't Have a Girlfriend" --
-
0:32 - 0:33(Laughter)
-
0:33 - 0:37Peter Backus tries to rate
his chances of finding love. -
0:37 - 0:39Now, Peter's not a very greedy man.
-
0:39 - 0:42Of all of the available women in the UK,
-
0:42 - 0:45all Peter's looking for
is somebody who lives near him, -
0:45 - 0:47somebody in the right age range,
-
0:47 - 0:50somebody with a university degree,
-
0:50 - 0:52somebody he's likely to get on well with,
-
0:52 - 0:54somebody who's likely to be attractive,
-
0:54 - 0:56somebody who's likely
to find him attractive. -
0:56 - 0:59(Laughter)
-
0:59 - 1:04And comes up with an estimate
of 26 women in the whole of the UK. -
1:04 - 1:05(Laughter)
-
1:05 - 1:07It's not looking very good, is it Peter?
-
1:07 - 1:09Now, just to put that into perspective,
-
1:09 - 1:13that's about 400 times fewer
than the best estimates -
1:13 - 1:16of how many intelligent
extraterrestrial life forms there are. -
1:16 - 1:22And it also gives Peter
a 1 in 285,000 chance -
1:22 - 1:24of bumping into any one
of these special ladies -
1:24 - 1:25on a given night out.
-
1:25 - 1:27I'd like to think
that's why mathematicians -
1:27 - 1:30don't really bother
going on nights out anymore. -
1:31 - 1:33The thing is that I personally
don't subscribe -
1:33 - 1:35to such a pessimistic view.
-
1:35 - 1:38Because I know,
just as well as all of you do, -
1:38 - 1:40that love doesn't really work like that.
-
1:40 - 1:45Human emotion isn't neatly ordered
and rational and easily predictable. -
1:45 - 1:48But I also know that that doesn't mean
-
1:48 - 1:51that mathematics hasn't got something
that it can offer us, -
1:51 - 1:55because, love, as with most of life,
is full of patterns -
1:55 - 1:59and mathematics is, ultimately,
all about the study of patterns. -
1:59 - 2:04Patterns from predicting the weather
to the fluctuations in the stock market, -
2:04 - 2:07to the movement of the planets
or the growth of cities. -
2:07 - 2:09And if we're being honest,
none of those things -
2:09 - 2:12are exactly neatly ordered
and easily predictable, either. -
2:13 - 2:18Because I believe that mathematics
is so powerful that it has the potential -
2:18 - 2:21to offer us a new way of looking
at almost anything. -
2:22 - 2:24Even something as mysterious as love.
-
2:25 - 2:27And so, to try to persuade you
-
2:27 - 2:31of how totally amazing, excellent
and relevant mathematics is, -
2:31 - 2:38I want to give you my top three
mathematically verifiable tips for love. -
2:39 - 2:40(Laughter)
-
2:40 - 2:42OK, so Top Tip #1:
-
2:42 - 2:44How to win at online dating.
-
2:47 - 2:50So my favorite online dating
website is OkCupid, -
2:50 - 2:54not least because it was started
by a group of mathematicians. -
2:54 - 2:55Now, because they're mathematicians,
-
2:55 - 2:57they have been collecting data
-
2:57 - 3:00on everybody who uses their site
for almost a decade. -
3:00 - 3:03And they've been trying
to search for patterns -
3:03 - 3:04in the way that we talk about ourselves
-
3:04 - 3:06and the way that we interact
with each other -
3:07 - 3:08on an online dating website.
-
3:08 - 3:11And they've come up with some
seriously interesting findings. -
3:11 - 3:12But my particular favorite
-
3:12 - 3:16is that it turns out
that on an online dating website, -
3:16 - 3:21how attractive you are
does not dictate how popular you are, -
3:22 - 3:25and actually, having people
think that you're ugly -
3:25 - 3:27can work to your advantage.
-
3:27 - 3:29(Laughter)
-
3:29 - 3:30Let me show you how this works.
-
3:30 - 3:35In a thankfully voluntary
section of OkCupid, -
3:35 - 3:38you are allowed to rate
how attractive you think people are -
3:38 - 3:40on a scale between one and five.
-
3:40 - 3:43Now, if we compare this score,
the average score, -
3:43 - 3:46to how many messages
a selection of people receive, -
3:46 - 3:48you can begin to get a sense
-
3:48 - 3:52of how attractiveness links to popularity
on an online dating website. -
3:52 - 3:55This is the graph the OkCupid guys
have come up with. -
3:55 - 3:58And the important thing to notice
is that it's not totally true -
3:58 - 4:01that the more attractive you are,
the more messages you get. -
4:01 - 4:06But the question arises then
of what is it about people up here -
4:06 - 4:09who are so much more popular
than people down here, -
4:09 - 4:13even though they have the same
score of attractiveness? -
4:13 - 4:17And the reason why is that it's not just
straightforward looks that are important. -
4:17 - 4:20So let me try to illustrate
their findings with an example. -
4:20 - 4:23So if you take someone like
Portia de Rossi, for example, -
4:23 - 4:28everybody agrees that Portia de Rossi
is a very beautiful woman. -
4:28 - 4:32Nobody thinks that she's ugly,
but she's not a supermodel, either. -
4:32 - 4:36If you compare Portia de Rossi
to someone like Sarah Jessica Parker, -
4:36 - 4:40now, a lot of people,
myself included, I should say, -
4:40 - 4:44think that Sarah Jessica Parker
is seriously fabulous -
4:44 - 4:47and possibly one
of the most beautiful creatures -
4:47 - 4:49to have ever have walked
on the face of the Earth. -
4:49 - 4:54But some other people,
i.e., most of the Internet ... -
4:54 - 4:56(Laughter)
-
4:56 - 4:59seem to think that she looks
a bit like a horse. -
4:59 - 5:01(Laughter)
-
5:02 - 5:06Now, I think that if you ask people
how attractive they thought -
5:06 - 5:08Jessica Parker or Portia de Rossi were,
-
5:08 - 5:10and you ask them to give
them a score between one and five -
5:10 - 5:14I reckon that they'd average out
to have roughly the same score. -
5:14 - 5:16But the way that people would vote
would be very different. -
5:16 - 5:19So Portia's scores would
all be clustered around the four -
5:19 - 5:21because everybody agrees
that she's very beautiful, -
5:22 - 5:24whereas Sarah Jessica Parker
completely divides opinion. -
5:24 - 5:26There'd be a huge spread in her scores.
-
5:26 - 5:29And actually it's this spread that counts.
-
5:29 - 5:31It's this spread
that makes you more popular -
5:31 - 5:33on an online Internet dating website.
-
5:33 - 5:34So what that means then
-
5:34 - 5:37is that if some people
think that you're attractive, -
5:37 - 5:39you're actually better off
-
5:39 - 5:43having some other people
think that you're a massive minger. -
5:44 - 5:46That's much better
than everybody just thinking -
5:46 - 5:48that you're the cute girl next door.
-
5:48 - 5:51Now, I think this begins
to make a bit more sense -
5:51 - 5:54when you think in terms of the people
who are sending these messages. -
5:54 - 5:56So let's say that you think
somebody's attractive, -
5:56 - 6:00but you suspect that other people
won't necessarily be that interested. -
6:00 - 6:03That means there's
less competition for you -
6:03 - 6:05and it's an extra incentive
for you to get in touch. -
6:05 - 6:08Whereas compare that
to if you think somebody is attractive -
6:08 - 6:11but you suspect that everybody
is going to think they're attractive. -
6:11 - 6:15Well, why would you bother
humiliating yourself, let's be honest? -
6:15 - 6:17But here's where the really
interesting part comes. -
6:17 - 6:22Because when people choose the pictures
that they use on an online dating website, -
6:22 - 6:24they often try to minimize the things
-
6:24 - 6:27that they think some people
will find unattractive. -
6:27 - 6:31The classic example is people
who are, perhaps, a little bit overweight -
6:31 - 6:34deliberately choosing
a very cropped photo, -
6:34 - 6:35(Laughter)
-
6:35 - 6:37or bald men, for example,
-
6:37 - 6:40deliberately choosing pictures
where they're wearing hats. -
6:40 - 6:42But actually this is the opposite
of what you should do -
6:42 - 6:44if you want to be successful.
-
6:44 - 6:45You should really, instead,
-
6:45 - 6:48play up to whatever it is
that makes you different, -
6:48 - 6:53even if you think that some people
will find it unattractive. -
6:53 - 6:56Because the people who fancy you
are just going to fancy you anyway, -
6:56 - 7:00and the unimportant losers who don't,
well, they only play up to your advantage. -
7:00 - 7:03OK, Top Tip #2:
How to pick the perfect partner. -
7:03 - 7:06So let's imagine then
that you're a roaring success -
7:06 - 7:07on the dating scene.
-
7:07 - 7:12But the question arises
of how do you then convert that success -
7:12 - 7:14into longer-term happiness,
-
7:14 - 7:19and in particular, how do you decide
when is the right time to settle down? -
7:19 - 7:22Now generally,
it's not advisable to just cash in -
7:22 - 7:26and marry the first person who comes along
and shows you any interest at all. -
7:26 - 7:30But, equally, you don't really
want to leave it too long -
7:30 - 7:32if you want to maximize your chance
of long-term happiness. -
7:32 - 7:36As my favorite author,
Jane Austen, puts it, -
7:36 - 7:38"An unmarried woman of seven and twenty
-
7:38 - 7:41can never hope to feel
or inspire affection again." -
7:42 - 7:44(Laughter)
-
7:44 - 7:45Thanks a lot, Jane.
-
7:45 - 7:47What do you know about love?
-
7:47 - 7:48(Laughter)
-
7:48 - 7:50So the question is then,
-
7:50 - 7:52how do you know when
is the right time to settle down, -
7:53 - 7:55given all the people
that you can date in your lifetime? -
7:55 - 7:59Thankfully, there's a rather delicious bit
of mathematics that we can use -
7:59 - 8:01to help us out here,
called optimal stopping theory. -
8:01 - 8:03So let's imagine, then,
-
8:03 - 8:06that you start dating when you're 15
-
8:06 - 8:10and ideally, you'd like to be married
by the time that you're 35. -
8:10 - 8:11And there's a number of people
-
8:11 - 8:14that you could potentially
date across your lifetime, -
8:14 - 8:16and they'll be at varying
levels of goodness. -
8:16 - 8:18Now the rules are that once
you cash in and get married, -
8:18 - 8:21you can't look ahead to see
what you could have had, -
8:21 - 8:23and equally, you can't go back
and change your mind. -
8:23 - 8:25In my experience at least,
-
8:25 - 8:28I find that typically people
don't much like being recalled -
8:28 - 8:33years after being passed up
for somebody else, or that's just me. -
8:33 - 8:36So the math says then
that what you should do -
8:36 - 8:40in the first 37 percent
of your dating window, -
8:40 - 8:43you should just reject everybody
as serious marriage potential. -
8:43 - 8:45(Laughter)
-
8:46 - 8:49And then, you should pick
the next person that comes along -
8:49 - 8:52that is better than everybody
that you've seen before. -
8:52 - 8:54So here's the example.
-
8:54 - 8:56Now if you do this, it can be
mathematically proven, in fact, -
8:56 - 8:59that this is the best possible way
-
8:59 - 9:03of maximizing your chances
of finding the perfect partner. -
9:03 - 9:08Now unfortunately, I have to tell you that
this method does come with some risks. -
9:09 - 9:13For instance, imagine
if your perfect partner appeared -
9:13 - 9:16during your first 37 percent.
-
9:16 - 9:19Now, unfortunately,
you'd have to reject them. -
9:19 - 9:22(Laughter)
-
9:22 - 9:24Now, if you're following the maths,
-
9:24 - 9:26I'm afraid no one else comes along
-
9:26 - 9:28that's better than anyone
you've seen before, -
9:28 - 9:32so you have to go on
rejecting everyone and die alone. -
9:32 - 9:34(Laughter)
-
9:35 - 9:36Probably surrounded by cats ...
-
9:36 - 9:38(Laughter)
-
9:38 - 9:39nibbling at your remains.
-
9:39 - 9:43OK, another risk is,
let's imagine, instead, -
9:43 - 9:47that the first people that you dated
in your first 37 percent -
9:47 - 9:50are just incredibly dull,
boring, terrible people. -
9:51 - 9:53That's OK, because
you're in your rejection phase, -
9:53 - 9:55so that's fine, you can reject them.
-
9:55 - 9:58But then imagine
the next person to come along -
9:58 - 10:02is just marginally less boring,
dull and terrible ... -
10:02 - 10:03(Laughter)
-
10:03 - 10:05than everybody that you've seen before.
-
10:05 - 10:08Now, if you are following the maths,
I'm afraid you have to marry them ... -
10:08 - 10:09(Laughter)
-
10:09 - 10:13and end up in a relationship
which is, frankly, suboptimal. -
10:13 - 10:14Sorry about that.
-
10:14 - 10:17But I do think that there's an opportunity
here for Hallmark to cash in on -
10:17 - 10:19and really cater for this market.
-
10:19 - 10:21A Valentine's Day card like this.
-
10:21 - 10:22(Laughter)
-
10:22 - 10:25"My darling husband,
you are marginally less terrible -
10:25 - 10:27than the first 37 percent
of people I dated." -
10:27 - 10:29(Laughter)
-
10:29 - 10:31It's actually more romantic
than I normally manage. -
10:32 - 10:33(Laughter)
-
10:33 - 10:38OK, so this method doesn't give you
a 100 percent success rate, -
10:38 - 10:41but there's no other possible
strategy that can do any better. -
10:41 - 10:45And actually, in the wild,
there are certain types of fish -
10:45 - 10:48which follow and employ
this exact strategy. -
10:48 - 10:50So they reject every possible
suitor that turns up -
10:50 - 10:53in the first 37 percent
of the mating season, -
10:53 - 10:57and then they pick the next fish
that comes along after that window -
10:57 - 10:59that's, I don't know, bigger and burlier
-
10:59 - 11:02than all of the fish
that they've seen before. -
11:02 - 11:07I also think that subconsciously,
humans, we do sort of do this anyway. -
11:07 - 11:09We give ourselves a little bit of time
to play the field, -
11:09 - 11:13get a feel for the marketplace
or whatever when we're young. -
11:13 - 11:18And then we only start looking seriously
at potential marriage candidates -
11:18 - 11:20once we hit our mid-to-late 20s.
-
11:20 - 11:23I think this is conclusive proof,
if ever it were needed, -
11:23 - 11:27that everybody's brains are prewired
to be just a little bit mathematical. -
11:27 - 11:29OK, so that was Top Tip #2.
-
11:29 - 11:33Now, Top Tip #3: How to avoid divorce.
-
11:33 - 11:36OK, so let's imagine then
that you picked your perfect partner -
11:36 - 11:41and you're settling into
a lifelong relationship with them. -
11:41 - 11:45Now, I like to think that everybody
would ideally like to avoid divorce, -
11:45 - 11:49apart from, I don't know,
Piers Morgan's wife, maybe? -
11:49 - 11:50(Laughter)
-
11:50 - 11:53But it's a sad fact of modern life
-
11:53 - 11:56that one in two marriages
in the States ends in divorce, -
11:56 - 12:00with the rest of the world
not being far behind. -
12:00 - 12:02Now, you can be forgiven, perhaps
-
12:02 - 12:05for thinking that the arguments
that precede a marital breakup -
12:05 - 12:09are not an ideal candidate
for mathematical investigation. -
12:09 - 12:11For one thing, it's very hard to know
-
12:11 - 12:14what you should be measuring
or what you should be quantifying. -
12:14 - 12:20But this didn't stop a psychologist,
John Gottman, who did exactly that. -
12:20 - 12:26Gottman observed hundreds of couples
having a conversation -
12:26 - 12:28and recorded, well,
everything you can think of. -
12:28 - 12:30So he recorded what was said
in the conversation, -
12:30 - 12:33he recorded their skin conductivity,
-
12:33 - 12:35he recorded their facial expressions,
-
12:35 - 12:37their heart rates, their blood pressure,
-
12:37 - 12:43basically everything apart from whether
or not the wife was actually always right, -
12:43 - 12:46which incidentally she totally is.
-
12:46 - 12:49But what Gottman and his team found
-
12:49 - 12:52was that one of the most
important predictors -
12:52 - 12:55for whether or not a couple
is going to get divorced -
12:55 - 12:59was how positive or negative each partner
was being in the conversation. -
12:59 - 13:02Now, couples that were very low-risk
-
13:02 - 13:06scored a lot more positive points
on Gottman's scale than negative. -
13:06 - 13:08Whereas bad relationships,
-
13:08 - 13:11by which I mean,
probably going to get divorced, -
13:11 - 13:16they found themselves getting
into a spiral of negativity. -
13:16 - 13:18Now just by using these very simple ideas,
-
13:18 - 13:20Gottman and his group were able to predict
-
13:20 - 13:23whether a given couple
was going to get divorced -
13:23 - 13:25with a 90 percent accuracy.
-
13:26 - 13:29But it wasn't until he teamed up
with a mathematician, James Murray, -
13:29 - 13:31that they really started to understand
-
13:31 - 13:36what causes these negativity spirals
and how they occur. -
13:36 - 13:37And the results that they found,
-
13:37 - 13:42I think, are just incredibly
impressively simple and interesting. -
13:42 - 13:47So these equations predict how the wife
or husband is going to respond -
13:47 - 13:48in their next turn of the conversation,
-
13:48 - 13:51how positive or negative
they're going to be. -
13:51 - 13:52And these equations depend on
-
13:52 - 13:54the mood of the person
when they're on their own, -
13:54 - 13:57the mood of the person when
they're with their partner, -
13:57 - 13:59but most importantly, they depend on
-
13:59 - 14:02how much the husband and wife
influence one another. -
14:02 - 14:05Now, I think it's important
to point out at this stage, -
14:05 - 14:08that these exact equations
have also been shown -
14:08 - 14:10to be perfectly able at describing
-
14:10 - 14:14what happens between two countries
in an arms race. -
14:15 - 14:18(Laughter)
-
14:18 - 14:22So that an arguing couple
spiraling into negativity -
14:22 - 14:24and teetering on the brink of divorce
-
14:24 - 14:28is actually mathematically equivalent
to the beginning of a nuclear war. -
14:28 - 14:31(Laughter)
-
14:31 - 14:33But the really important term
in this equation -
14:33 - 14:36is the influence that people
have on one another, -
14:36 - 14:39and in particular, something called
"the negativity threshold." -
14:39 - 14:41Now, the negativity threshold,
-
14:41 - 14:46you can think of as
how annoying the husband can be -
14:46 - 14:50before the wife starts to get
really pissed off, and vice versa. -
14:50 - 14:54Now, I always thought that good marriages
were about compromise and understanding -
14:54 - 14:57and allowing the person
to have the space to be themselves. -
14:57 - 15:01So I would have thought that perhaps
the most successful relationships -
15:01 - 15:04were ones where there was
a really high negativity threshold. -
15:04 - 15:06Where couples let things go
-
15:06 - 15:08and only brought things up
if they really were a big deal. -
15:08 - 15:13But actually, the mathematics
and subsequent findings by the team -
15:13 - 15:15have shown the exact opposite is true.
-
15:16 - 15:18The best couples,
or the most successful couples, -
15:18 - 15:21are the ones with a really low
negativity threshold. -
15:22 - 15:25These are the couples
that don't let anything go unnoticed -
15:25 - 15:28and allow each other
some room to complain. -
15:28 - 15:34These are the couples that are continually
trying to repair their own relationship, -
15:34 - 15:36that have a much more positive
outlook on their marriage. -
15:36 - 15:38Couples that don't let things go
-
15:39 - 15:43and couples that don't let trivial things
end up being a really big deal. -
15:44 - 15:50Now of course, it takes a bit more
than just a low negativity threshold -
15:50 - 15:54and not compromising
to have a successful relationship. -
15:54 - 15:57But I think that it's quite interesting
-
15:57 - 15:59to know that there is really
mathematical evidence -
15:59 - 16:02to say that you should never
let the sun go down on your anger. -
16:02 - 16:04So those are my top three tips
-
16:04 - 16:07of how maths can help you
with love and relationships. -
16:07 - 16:10But I hope, that aside from
their use as tips, -
16:10 - 16:14they also give you a little bit of insight
into the power of mathematics. -
16:14 - 16:18Because for me, equations
and symbols aren't just a thing. -
16:19 - 16:23They're a voice that speaks out
about the incredible richness of nature -
16:23 - 16:25and the startling simplicity
-
16:25 - 16:30in the patterns that twist and turn
and warp and evolve all around us, -
16:30 - 16:32from how the world works to how we behave.
-
16:32 - 16:35So I hope that perhaps,
for just a couple of you, -
16:35 - 16:37a little bit of insight
into the mathematics of love -
16:37 - 16:41can persuade you to have
a little bit more love for mathematics. -
16:41 - 16:42Thank you.
-
16:42 - 16:49(Applause)
- Title:
- The mathematics of love
- Speaker:
- Hannah Fry
- 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:
- TEDTalks
- Duration:
- 16:56
Krystian Aparta commented on English subtitles for The mathematics of love | ||
Krystian Aparta edited English subtitles for The mathematics of love | ||
Krystian Aparta edited English subtitles for The mathematics of love | ||
Helene Batt edited English subtitles for The mathematics of love | ||
Helene Batt edited English subtitles for The mathematics of love | ||
NG commented on English subtitles for The mathematics of love | ||
Helene Batt edited English subtitles for The mathematics of love | ||
Helene Batt edited English subtitles for The mathematics of love |
NG
Hi English LC,
At 14:35:88, the word 'threshhold' has an extra 'h'.
'and in particular, something called
the negativity threshhold.'
Krystian Aparta
The English transcript was updated on 2/28/2017.