Recorded at | April 04, 2014 |
---|---|

Event | TEDxBinghamtonUniversity |

Duration (min:sec) | 16:48 |

Video Type | TEDx Talk |

Words per minute | 173.02 fast |

Readability (FK) | 46.92 difficult |

Speaker | Hannah Fry |

Country | United Kingdom |

Occupation | mathematician, presenter, orator, author |

Description | British mathematician and TV presenter |

Official TED page for this talk

**Synopsis**

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.

1 | 00:12 | Today I want to talk to you about the mathematics of love. | ||

2 | 00:17 | Now, I think that we can all agree | ||

3 | 00:18 | that mathematicians are famously excellent at finding love. | ||

4 | 00:22 | (Laughter) | ||

5 | 00:23 | But it's not just because of our dashing personalities, | ||

6 | 00:26 | superior conversational skills and excellent pencil cases. | ||

7 | 00:32 | It's also because we've actually done an awful lot of work into the maths | ||

8 | 00:35 | of how to find the perfect partner. | ||

9 | 00:38 | Now, in my favorite paper on the subject, which is entitled, | ||

10 | 00:42 | "Why I Don't Have a Girlfriend" -- | ||

11 | 00:43 | (Laughter) | ||

12 | 00:45 | Peter Backus tries to rate his chances of finding love. | ||

13 | 00:49 | Now, Peter's not a very greedy man. | ||

14 | 00:51 | Of all of the available women in the UK, | ||

15 | 00:53 | all Peter's looking for is somebody who lives near him, | ||

16 | 00:57 | somebody in the right age range, | ||

17 | 00:58 | somebody with a university degree, | ||

18 | 01:01 | somebody he's likely to get on well with, | ||

19 | 01:03 | somebody who's likely to be attractive, | ||

20 | 01:05 | somebody who's likely to find him attractive. | ||

21 | 01:08 | (Laughter) | ||

22 | 01:11 | And comes up with an estimate of 26 women in the whole of the UK. | ||

23 | 01:16 | (Laughter) | ||

24 | 01:17 | It's not looking very good, is it Peter? | ||

25 | 01:19 | Now, just to put that into perspective, | ||

26 | 01:21 | that's about 400 times fewer than the best estimates | ||

27 | 01:24 | of how many intelligent extraterrestrial life forms there are. | ||

28 | 01:28 | And it also gives Peter a 1 in 285,000 chance | ||

29 | 01:33 | of bumping into any one of these special ladies | ||

30 | 01:35 | on a given night out. | ||

31 | 01:37 | I'd like to think that's why mathematicians | ||

32 | 01:39 | don't really bother going on nights out anymore. | ||

33 | 01:43 | The thing is that I personally don't subscribe | ||

34 | 01:45 | to such a pessimistic view. | ||

35 | 01:47 | Because I know, just as well as all of you do, | ||

36 | 01:49 | that love doesn't really work like that. | ||

37 | 01:52 | Human emotion isn't neatly ordered and rational and easily predictable. | ||

38 | 01:57 | But I also know that that doesn't mean | ||

39 | 01:59 | that mathematics hasn't got something that it can offer us, | ||

40 | 02:02 | because, love, as with most of life, is full of patterns | ||

41 | 02:06 | and mathematics is, ultimately, all about the study of patterns. | ||

42 | 02:11 | Patterns from predicting the weather to the fluctuations in the stock market, | ||

43 | 02:15 | to the movement of the planets or the growth of cities. | ||

44 | 02:18 | And if we're being honest, none of those things | ||

45 | 02:20 | are exactly neatly ordered and easily predictable, either. | ||

46 | 02:24 | Because I believe that mathematics is so powerful that it has the potential | ||

47 | 02:30 | to offer us a new way of looking at almost anything. | ||

48 | 02:33 | Even something as mysterious as love. | ||

49 | 02:36 | And so, to try to persuade you | ||

50 | 02:38 | of how totally amazing, excellent and relevant mathematics is, | ||

51 | 02:43 | I want to give you my top three mathematically verifiable tips for love. | ||

52 | 02:50 | (Laughter) | ||

53 | 02:52 | OK, so Top Tip #1: | ||

54 | 02:54 | How to win at online dating. | ||

55 | 02:58 | So my favorite online dating website is OkCupid, | ||

56 | 03:01 | not least because it was started by a group of mathematicians. | ||

57 | 03:05 | Now, because they're mathematicians, | ||

58 | 03:07 | they have been collecting data | ||

59 | 03:08 | on everybody who uses their site for almost a decade. | ||

60 | 03:12 | And they've been trying to search for patterns | ||

61 | 03:14 | in the way that we talk about ourselves | ||

62 | 03:16 | and the way that we interact with each other | ||

63 | 03:18 | on an online dating website. | ||

64 | 03:19 | And they've come up with some seriously interesting findings. | ||

65 | 03:22 | But my particular favorite | ||

66 | 03:24 | is that it turns out that on an online dating website, | ||

67 | 03:27 | how attractive you are does not dictate how popular you are, | ||

68 | 03:33 | and actually, having people think that you're ugly | ||

69 | 03:37 | can work to your advantage. | ||

70 | 03:39 | (Laughter) | ||

71 | 03:40 | Let me show you how this works. | ||

72 | 03:42 | In a thankfully voluntary section of OkCupid, | ||

73 | 03:46 | you are allowed to rate how attractive you think people are | ||

74 | 03:49 | on a scale between one and five. | ||

75 | 03:51 | Now, if we compare this score, the average score, | ||

76 | 03:54 | to how many messages a selection of people receive, | ||

77 | 03:58 | you can begin to get a sense | ||

78 | 03:59 | of how attractiveness links to popularity on an online dating website. | ||

79 | 04:04 | This is the graph the OkCupid guys have come up with. | ||

80 | 04:07 | And the important thing to notice is that it's not totally true | ||

81 | 04:10 | that the more attractive you are, the more messages you get. | ||

82 | 04:13 | But the question arises then of what is it about people up here | ||

83 | 04:17 | who are so much more popular than people down here, | ||

84 | 04:21 | even though they have the same score of attractiveness? | ||

85 | 04:24 | And the reason why is that it's not just straightforward looks that are important. | ||

86 | 04:28 | So let me try to illustrate their findings with an example. | ||

87 | 04:31 | So if you take someone like Portia de Rossi, for example, | ||

88 | 04:35 | everybody agrees that Portia de Rossi is a very beautiful woman. | ||

89 | 04:39 | Nobody thinks that she's ugly, but she's not a supermodel, either. | ||

90 | 04:43 | If you compare Portia de Rossi to someone like Sarah Jessica Parker, | ||

91 | 04:48 | now, a lot of people, myself included, I should say, | ||

92 | 04:52 | think that Sarah Jessica Parker is seriously fabulous | ||

93 | 04:56 | and possibly one of the most beautiful creatures | ||

94 | 04:58 | to have ever have walked on the face of the Earth. | ||

95 | 05:01 | But some other people, i.e., most of the Internet . | ||

96 | 05:06 | (Laughter) | ||

97 | 05:08 | seem to think that she looks a bit like a horse. | ||

98 | 05:10 | (Laughter) | ||

99 | 05:13 | Now, I think that if you ask people how attractive they thought | ||

100 | 05:17 | Jessica Parker or Portia de Rossi were, | ||

101 | 05:19 | and you ask them to give them a score between one and five | ||

102 | 05:22 | I reckon that they'd average out to have roughly the same score. | ||

103 | 05:25 | But the way that people would vote would be very different. | ||

104 | 05:28 | So Portia's scores would all be clustered around the four | ||

105 | 05:31 | because everybody agrees that she's very beautiful, | ||

106 | 05:33 | whereas Sarah Jessica Parker completely divides opinion. | ||

107 | 05:36 | There'd be a huge spread in her scores. | ||

108 | 05:38 | And actually it's this spread that counts. | ||

109 | 05:40 | It's this spread that makes you more popular | ||

110 | 05:42 | on an online Internet dating website. | ||

111 | 05:45 | So what that means then | ||

112 | 05:46 | is that if some people think that you're attractive, | ||

113 | 05:48 | you're actually better off | ||

114 | 05:50 | having some other people think that you're a massive minger. | ||

115 | 05:55 | That's much better than everybody just thinking | ||

116 | 05:58 | that you're the cute girl next door. | ||

117 | 06:00 | Now, I think this begins to make a bit more sense | ||

118 | 06:02 | when you think in terms of the people who are sending these messages. | ||

119 | 06:05 | So let's say that you think somebody's attractive, | ||

120 | 06:08 | but you suspect that other people won't necessarily be that interested. | ||

121 | 06:12 | That means there's less competition for you | ||

122 | 06:14 | and it's an extra incentive for you to get in touch. | ||

123 | 06:17 | Whereas compare that to if you think somebody is attractive | ||

124 | 06:20 | but you suspect that everybody is going to think they're attractive. | ||

125 | 06:23 | Well, why would you bother humiliating yourself, let's be honest? | ||

126 | 06:27 | But here's where the really interesting part comes. | ||

127 | 06:29 | Because when people choose the pictures that they use on an online dating website, | ||

128 | 06:33 | they often try to minimize the things | ||

129 | 06:35 | that they think some people will find unattractive. | ||

130 | 06:39 | The classic example is people who are, perhaps, a little bit overweight | ||

131 | 06:43 | deliberately choosing a very cropped photo, | ||

132 | 06:45 | (Laughter) | ||

133 | 06:47 | or bald men, for example, | ||

134 | 06:48 | deliberately choosing pictures where they're wearing hats. | ||

135 | 06:51 | But actually this is the opposite of what you should do | ||

136 | 06:54 | if you want to be successful. | ||

137 | 06:55 | You should really, instead, | ||

138 | 06:57 | play up to whatever it is that makes you different, | ||

139 | 07:00 | even if you think that some people will find it unattractive. | ||

140 | 07:04 | Because the people who fancy you are just going to fancy you anyway, | ||

141 | 07:07 | and the unimportant losers who don't, well, they only play up to your advantage. | ||

142 | 07:12 | OK, Top Tip #2: How to pick the perfect partner. | ||

143 | 07:14 | So let's imagine then that you're a roaring success | ||

144 | 07:17 | on the dating scene. | ||

145 | 07:19 | But the question arises of how do you then convert that success | ||

146 | 07:23 | into longer-term happiness, | ||

147 | 07:26 | and in particular, how do you decide when is the right time to settle down? | ||

148 | 07:31 | Now generally, it's not advisable to just cash in | ||

149 | 07:34 | and marry the first person who comes along and shows you any interest at all. | ||

150 | 07:38 | But, equally, you don't really want to leave it too long | ||

151 | 07:41 | if you want to maximize your chance of long-term happiness. | ||

152 | 07:44 | As my favorite author, Jane Austen, puts it, | ||

153 | 07:47 | "An unmarried woman of seven and twenty | ||

154 | 07:50 | can never hope to feel or inspire affection again." | ||

155 | 07:53 | (Laughter) | ||

156 | 07:56 | Thanks a lot, Jane. | ||

157 | 07:57 | What do you know about love? | ||

158 | 07:58 | (Laughter) | ||

159 | 07:59 | So the question is then, | ||

160 | 08:01 | how do you know when is the right time to settle down, | ||

161 | 08:04 | given all the people that you can date in your lifetime? | ||

162 | 08:07 | Thankfully, there's a rather delicious bit of mathematics that we can use | ||

163 | 08:10 | to help us out here, called optimal stopping theory. | ||

164 | 08:13 | So let's imagine, then, | ||

165 | 08:15 | that you start dating when you're 15 | ||

166 | 08:17 | and ideally, you'd like to be married by the time that you're 35. | ||

167 | 08:21 | And there's a number of people | ||

168 | 08:23 | that you could potentially date across your lifetime, | ||

169 | 08:25 | and they'll be at varying levels of goodness. | ||

170 | 08:27 | Now the rules are that once you cash in and get married, | ||

171 | 08:30 | you can't look ahead to see what you could have had, | ||

172 | 08:32 | and equally, you can't go back and change your mind. | ||

173 | 08:35 | In my experience at least, | ||

174 | 08:37 | I find that typically people don't much like being recalled | ||

175 | 08:39 | years after being passed up for somebody else, or that's just me. | ||

176 | 08:45 | So the math says then that what you should do | ||

177 | 08:48 | in the first 37 percent of your dating window, | ||

178 | 08:51 | you should just reject everybody as serious marriage potential. | ||

179 | 08:55 | (Laughter) | ||

180 | 08:57 | And then, you should pick the next person that comes along | ||

181 | 09:01 | that is better than everybody that you've seen before. | ||

182 | 09:04 | So here's the example. | ||

183 | 09:05 | Now if you do this, it can be mathematically proven, in fact, | ||

184 | 09:08 | that this is the best possible way | ||

185 | 09:10 | of maximizing your chances of finding the perfect partner. | ||

186 | 09:15 | Now unfortunately, I have to tell you that this method does come with some risks. | ||

187 | 09:20 | For instance, imagine if your perfect partner appeared | ||

188 | 09:25 | during your first 37 percent. | ||

189 | 09:28 | Now, unfortunately, you'd have to reject them. | ||

190 | 09:30 | (Laughter) | ||

191 | 09:34 | Now, if you're following the maths, | ||

192 | 09:36 | I'm afraid no one else comes along | ||

193 | 09:37 | that's better than anyone you've seen before, | ||

194 | 09:40 | so you have to go on rejecting everyone and die alone. | ||

195 | 09:44 | (Laughter) | ||

196 | 09:46 | Probably surrounded by cats . | ||

197 | 09:48 | (Laughter) | ||

198 | 09:49 | nibbling at your remains. | ||

199 | 09:51 | OK, another risk is, let's imagine, instead, | ||

200 | 09:55 | that the first people that you dated in your first 37 percent | ||

201 | 09:58 | are just incredibly dull, boring, terrible people. | ||

202 | 10:02 | That's OK, because you're in your rejection phase, | ||

203 | 10:05 | so that's fine, you can reject them. | ||

204 | 10:06 | But then imagine the next person to come along | ||

205 | 10:10 | is just marginally less boring, dull and terrible . | ||

206 | 10:13 | (Laughter) | ||

207 | 10:14 | than everybody that you've seen before. | ||

208 | 10:16 | Now, if you are following the maths, I'm afraid you have to marry them . | ||

209 | 10:20 | (Laughter) | ||

210 | 10:21 | and end up in a relationship which is, frankly, suboptimal. | ||

211 | 10:24 | Sorry about that. | ||

212 | 10:25 | But I do think that there's an opportunity here for Hallmark to cash in on | ||

213 | 10:29 | and really cater for this market. | ||

214 | 10:30 | A Valentine's Day card like this. | ||

215 | 10:32 | (Laughter) | ||

216 | 10:33 | "My darling husband, you are marginally less terrible | ||

217 | 10:36 | than the first 37 percent of people I dated." | ||

218 | 10:38 | (Laughter) | ||

219 | 10:40 | It's actually more romantic than I normally manage. | ||

220 | 10:43 | (Laughter) | ||

221 | 10:45 | OK, so this method doesn't give you a 100 percent success rate, | ||

222 | 10:49 | but there's no other possible strategy that can do any better. | ||

223 | 10:53 | And actually, in the wild, there are certain types of fish | ||

224 | 10:56 | which follow and employ this exact strategy. | ||

225 | 10:59 | So they reject every possible suitor that turns up | ||

226 | 11:02 | in the first 37 percent of the mating season, | ||

227 | 11:05 | and then they pick the next fish that comes along after that window | ||

228 | 11:08 | that's, I don't know, bigger and burlier | ||

229 | 11:11 | than all of the fish that they've seen before. | ||

230 | 11:13 | I also think that subconsciously, humans, we do sort of do this anyway. | ||

231 | 11:18 | We give ourselves a little bit of time to play the field, | ||

232 | 11:21 | get a feel for the marketplace or whatever when we're young. | ||

233 | 11:25 | And then we only start looking seriously at potential marriage candidates | ||

234 | 11:29 | once we hit our mid-to-late 20s. | ||

235 | 11:31 | I think this is conclusive proof, if ever it were needed, | ||

236 | 11:35 | that everybody's brains are prewired to be just a little bit mathematical. | ||

237 | 11:39 | OK, so that was Top Tip #2. | ||

238 | 11:41 | Now, Top Tip #3: How to avoid divorce. | ||

239 | 11:45 | OK, so let's imagine then that you picked your perfect partner | ||

240 | 11:48 | and you're settling into a lifelong relationship with them. | ||

241 | 11:52 | Now, I like to think that everybody would ideally like to avoid divorce, | ||

242 | 11:56 | apart from, I don't know, Piers Morgan's wife, maybe? | ||

243 | 12:00 | (Laughter) | ||

244 | 12:02 | But it's a sad fact of modern life | ||

245 | 12:04 | that one in two marriages in the States ends in divorce, | ||

246 | 12:07 | with the rest of the world not being far behind. | ||

247 | 12:11 | Now, you can be forgiven, perhaps | ||

248 | 12:13 | for thinking that the arguments that precede a marital breakup | ||

249 | 12:17 | are not an ideal candidate for mathematical investigation. | ||

250 | 12:21 | For one thing, it's very hard to know | ||

251 | 12:23 | what you should be measuring or what you should be quantifying. | ||

252 | 12:26 | But this didn't stop a psychologist, John Gottman, who did exactly that. | ||

253 | 12:32 | Gottman observed hundreds of couples having a conversation | ||

254 | 12:37 | and recorded, well, everything you can think of. | ||

255 | 12:40 | So he recorded what was said in the conversation, | ||

256 | 12:42 | he recorded their skin conductivity, | ||

257 | 12:44 | he recorded their facial expressions, | ||

258 | 12:46 | their heart rates, their blood pressure, | ||

259 | 12:48 | basically everything apart from whether or not the wife was actually always right, | ||

260 | 12:55 | which incidentally she totally is. | ||

261 | 12:58 | But what Gottman and his team found | ||

262 | 13:01 | was that one of the most important predictors | ||

263 | 13:04 | for whether or not a couple is going to get divorced | ||

264 | 13:06 | was how positive or negative each partner was being in the conversation. | ||

265 | 13:11 | Now, couples that were very low-risk | ||

266 | 13:13 | scored a lot more positive points on Gottman's scale than negative. | ||

267 | 13:17 | Whereas bad relationships, | ||

268 | 13:20 | by which I mean, probably going to get divorced, | ||

269 | 13:23 | they found themselves getting into a spiral of negativity. | ||

270 | 13:27 | Now just by using these very simple ideas, | ||

271 | 13:29 | Gottman and his group were able to predict | ||

272 | 13:32 | whether a given couple was going to get divorced | ||

273 | 13:35 | with a 90 percent accuracy. | ||

274 | 13:38 | But it wasn't until he teamed up with a mathematician, James Murray, | ||

275 | 13:41 | that they really started to understand | ||

276 | 13:43 | what causes these negativity spirals and how they occur. | ||

277 | 13:47 | And the results that they found, | ||

278 | 13:49 | I think, are just incredibly impressively simple and interesting. | ||

279 | 13:53 | So these equations predict how the wife or husband is going to respond | ||

280 | 13:58 | in their next turn of the conversation, | ||

281 | 14:00 | how positive or negative they're going to be. | ||

282 | 14:02 | And these equations depend on | ||

283 | 14:04 | the mood of the person when they're on their own, | ||

284 | 14:06 | the mood of the person when they're with their partner, | ||

285 | 14:09 | but most importantly, they depend on | ||

286 | 14:10 | how much the husband and wife influence one another. | ||

287 | 14:14 | Now, I think it's important to point out at this stage, | ||

288 | 14:16 | that these exact equations have also been shown | ||

289 | 14:20 | to be perfectly able at describing | ||

290 | 14:22 | what happens between two countries in an arms race. | ||

291 | 14:27 | (Laughter) | ||

292 | 14:30 | So that an arguing couple spiraling into negativity | ||

293 | 14:33 | and teetering on the brink of divorce | ||

294 | 14:35 | is actually mathematically equivalent to the beginning of a nuclear war. | ||

295 | 14:40 | (Laughter) | ||

296 | 14:43 | But the really important term in this equation | ||

297 | 14:45 | is the influence that people have on one another, | ||

298 | 14:47 | and in particular, something called "the negativity threshold." | ||

299 | 14:51 | Now, the negativity threshold, | ||

300 | 14:52 | you can think of as how annoying the husband can be | ||

301 | 14:57 | before the wife starts to get really pissed off, and vice versa. | ||

302 | 15:01 | Now, I always thought that good marriages were about compromise and understanding | ||

303 | 15:06 | and allowing the person to have the space to be themselves. | ||

304 | 15:09 | So I would have thought that perhaps the most successful relationships | ||

305 | 15:12 | were ones where there was a really high negativity threshold. | ||

306 | 15:15 | Where couples let things go | ||

307 | 15:17 | and only brought things up if they really were a big deal. | ||

308 | 15:20 | But actually, the mathematics and subsequent findings by the team | ||

309 | 15:24 | have shown the exact opposite is true. | ||

310 | 15:27 | The best couples, or the most successful couples, | ||

311 | 15:30 | are the ones with a really low negativity threshold. | ||

312 | 15:33 | These are the couples that don't let anything go unnoticed | ||

313 | 15:37 | and allow each other some room to complain. | ||

314 | 15:40 | These are the couples that are continually trying to repair their own relationship, | ||

315 | 15:45 | that have a much more positive outlook on their marriage. | ||

316 | 15:48 | Couples that don't let things go | ||

317 | 15:50 | and couples that don't let trivial things end up being a really big deal. | ||

318 | 15:56 | Now of course, it takes a bit more than just a low negativity threshold | ||

319 | 16:01 | and not compromising to have a successful relationship. | ||

320 | 16:06 | But I think that it's quite interesting | ||

321 | 16:08 | to know that there is really mathematical evidence | ||

322 | 16:11 | to say that you should never let the sun go down on your anger. | ||

323 | 16:14 | So those are my top three tips | ||

324 | 16:16 | of how maths can help you with love and relationships. | ||

325 | 16:19 | But I hope, that aside from their use as tips, | ||

326 | 16:21 | they also give you a little bit of insight into the power of mathematics. | ||

327 | 16:25 | Because for me, equations and symbols aren't just a thing. | ||

328 | 16:30 | They're a voice that speaks out about the incredible richness of nature | ||

329 | 16:35 | and the startling simplicity | ||

330 | 16:36 | in the patterns that twist and turn and warp and evolve all around us, | ||

331 | 16:41 | from how the world works to how we behave. | ||

332 | 16:44 | So I hope that perhaps, for just a couple of you, | ||

333 | 16:46 | a little bit of insight into the mathematics of love | ||

334 | 16:49 | can persuade you to have a little bit more love for mathematics. | ||

335 | 16:52 | Thank you. | ||

336 | 16:53 | (Applause) |