Return to Video

The mathematics of love

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

more » « less
Video Language:
English
Team:
closed TED
Project:
TEDTalks
Duration:
16:56
  • NG

    Hi English LC,

    At 14:35:88, the word 'threshhold' has an extra 'h'.

    'and in particular, something called
    the negativity threshhold.'

  • The English transcript was updated on 2/28/2017.

English subtitles

Revisions Compare revisions