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Internet dating is big business. | 0:00:10 | 0:00:12 | |
It's worth over 2 billion per year | 0:00:12 | 0:00:15 | |
and claims to generate one fifth of all current committed relationships. | 0:00:15 | 0:00:19 | |
Worldwide, 91 million people log on to dating sites and I'm one of them. | 0:00:19 | 0:00:25 | |
Since I started dating, it has changed a huge amount. | 0:00:25 | 0:00:28 | |
Really, now, almost everyone I know has tried online dating. | 0:00:28 | 0:00:32 | |
I've been dating in both London and New York | 0:00:33 | 0:00:36 | |
and so far I've yet to find The One. | 0:00:36 | 0:00:38 | |
I'm 37, all my friends are married, my brothers are married, | 0:00:40 | 0:00:44 | |
it's not fun being single any more. | 0:00:44 | 0:00:46 | |
Although I'm happily married now, I've done my share of online dating. | 0:00:46 | 0:00:51 | |
As a mathematician, I'm fascinated by the algorithms that dating sites | 0:00:51 | 0:00:55 | |
claim can find you love, | 0:00:55 | 0:00:57 | |
but there's little hard evidence that they actually deliver. | 0:00:57 | 0:01:00 | |
So, I'm going to put them to the test using Xand as my guinea pig. | 0:01:00 | 0:01:05 | |
I'm willing to gamble with Xand's heart and see if we can use | 0:01:05 | 0:01:09 | |
a little bit of maths to find him a girl that he really likes. | 0:01:09 | 0:01:13 | |
But can applying some science really help me find love? | 0:01:13 | 0:01:16 | |
-Hiya, how are you doing? -Oh, really nice to meet you. | 0:01:16 | 0:01:19 | |
Are matching sites any better than just choosing yourself? | 0:01:19 | 0:01:23 | |
There is no way that these algorithms can do what | 0:01:23 | 0:01:26 | |
they're claiming to do. | 0:01:26 | 0:01:28 | |
Which picture should you use? | 0:01:28 | 0:01:30 | |
God, you're like the bloomin' hair police. | 0:01:30 | 0:01:32 | |
And what's the best way to write a profile? | 0:01:32 | 0:01:35 | |
Just being a nice guy is not necessarily the best pitch. | 0:01:35 | 0:01:39 | |
We look at the science of online dating and have some fun along the way. | 0:01:39 | 0:01:43 | |
You're going right there. SHE LAUGHS | 0:01:43 | 0:01:46 | |
That's where your genitals lit up. | 0:01:46 | 0:01:48 | |
MUSIC: Ooh La La by Goldfrapp | 0:01:53 | 0:01:56 | |
Horizon has invited 50 single ladies and gentlemen | 0:02:00 | 0:02:04 | |
to a dating event in London. | 0:02:04 | 0:02:06 | |
-No-one's snogging, but... -No. -So far. | 0:02:06 | 0:02:10 | |
-It's early yet. -Early days. It's early days. | 0:02:10 | 0:02:12 | |
They haven't had enough to drink yet. | 0:02:12 | 0:02:15 | |
We are all taking part in an experiment to test the | 0:02:15 | 0:02:18 | |
mathematical matching systems used by many online dating sites. | 0:02:18 | 0:02:22 | |
There is that sort of, almost placebo effect of expectation. | 0:02:23 | 0:02:27 | |
Whether that does better or not then our actual extended algorithm, | 0:02:27 | 0:02:32 | |
we're about to find out. | 0:02:32 | 0:02:34 | |
The recent upsurge in online dating is a gold mine for researchers | 0:02:34 | 0:02:37 | |
studying human behaviour | 0:02:37 | 0:02:39 | |
and it's starting to produce some good, hard science | 0:02:39 | 0:02:42 | |
about the best techniques to help those like Xand looking for love. | 0:02:42 | 0:02:46 | |
But wait till she stands up, because she's super smoking. | 0:02:46 | 0:02:49 | |
I hate to admit it, but I really need some help. | 0:02:53 | 0:02:56 | |
So, I think the worst thing about online dating is having | 0:03:01 | 0:03:04 | |
to admit to yourself that you're single | 0:03:04 | 0:03:07 | |
and that you want to meet someone else. And at 37, I don't feel old, | 0:03:07 | 0:03:11 | |
but I'm probably in a bit more of a mess than I used to be. | 0:03:11 | 0:03:14 | |
I've been to eight weddings in the last two years and I feel like | 0:03:15 | 0:03:19 | |
always the bridesmaid, never the bride does almost literally apply to me. | 0:03:19 | 0:03:24 | |
I think I am getting a little grumpy at weddings now. I think | 0:03:24 | 0:03:27 | |
I slightly do resent... | 0:03:27 | 0:03:29 | |
..other people's happiness, which is not... | 0:03:31 | 0:03:35 | |
It's not a good position to be in. | 0:03:35 | 0:03:38 | |
First couple of divorces, though, so that made me feel better. | 0:03:38 | 0:03:41 | |
I found online dating a minefield. | 0:03:47 | 0:03:50 | |
There are thousands of different sites, from mobile apps | 0:03:50 | 0:03:52 | |
that hook you up with a simple swipe, | 0:03:52 | 0:03:54 | |
to internet dating with complex matching systems | 0:03:54 | 0:03:57 | |
that promise to find you the perfect partner. | 0:03:57 | 0:04:00 | |
But which is better? | 0:04:00 | 0:04:02 | |
I get that online dating is an efficient way of encountering other people... | 0:04:02 | 0:04:07 | |
-Yeah. -..and probably, therefore, getting me dates, | 0:04:07 | 0:04:09 | |
but it makes a much bigger claim than that. | 0:04:09 | 0:04:12 | |
-They're saying, "We'll find you someone right for you." -Mm. | 0:04:12 | 0:04:14 | |
Well, there's certainly a range of different websites that offer different things. | 0:04:14 | 0:04:18 | |
So, some of them are just effectively a catalogue of strangers, right? | 0:04:18 | 0:04:21 | |
Whereas others have these algorithms built in, | 0:04:21 | 0:04:24 | |
which is a series of calculations. | 0:04:24 | 0:04:26 | |
So, you take some input - maybe what you're looking for in a partner, | 0:04:26 | 0:04:30 | |
what prospective partners are looking for in their partner - | 0:04:30 | 0:04:34 | |
and you put it through a series of logical steps, like a recipe effectively, | 0:04:34 | 0:04:38 | |
and in the end you come up with an output, which is how good | 0:04:38 | 0:04:41 | |
the two of you would be matched as a potential couple. | 0:04:41 | 0:04:44 | |
-So, it's like a decision tree? -Yeah, exactly. | 0:04:44 | 0:04:47 | |
MUSIC: Escape (The Pina Colada Song) By Rupert Holmes | 0:04:47 | 0:04:50 | |
At their simplest, algorithms work like a flow chart, | 0:04:51 | 0:04:55 | |
with different inputs or instructions that feed into an end result or output. | 0:04:55 | 0:05:00 | |
OK, but I've only ever used the simplest algorithm, | 0:05:00 | 0:05:04 | |
-which is proximity, age, sex. -Yeah. | 0:05:04 | 0:05:07 | |
But I think that if we get you to fill in a questionnaire about | 0:05:07 | 0:05:12 | |
the type of things that you find appealing in a partner, | 0:05:12 | 0:05:15 | |
I think I could write an algorithm that would find a girl | 0:05:15 | 0:05:18 | |
who is better suited for you than if you just walked into a bar and picked someone at random. | 0:05:18 | 0:05:23 | |
I'm pretty sceptical about this, but, hey, let's give it a go. | 0:05:23 | 0:05:27 | |
-And this is actually applied maths. -Yeah. -Like, we'll use it to get me a date. -Yeah, totally. | 0:05:27 | 0:05:32 | |
All right, but the challenge is not for you to do better than me going to a bar, | 0:05:32 | 0:05:36 | |
you're actually up against me choosing random people through swiping. | 0:05:36 | 0:05:39 | |
-That's the challenge. -OK. -You're on. -Deal. | 0:05:39 | 0:05:42 | |
With mobile dating apps like Tinder, Zoosk and Happn | 0:05:49 | 0:05:52 | |
allowing users to select or reject partners with a simple | 0:05:52 | 0:05:55 | |
swipe left or right, online daters like me can feel a little jaded. | 0:05:55 | 0:06:00 | |
It sometimes feels really superficial... | 0:06:00 | 0:06:03 | |
It's very easy for people to just reject you outright. | 0:06:03 | 0:06:06 | |
So, you think, "Oh, why are they rejecting me? What's wrong with me?" | 0:06:06 | 0:06:10 | |
And traditional dating sites have their downsides, too. | 0:06:10 | 0:06:14 | |
You get a lot of creeps online who try to send you, like, | 0:06:14 | 0:06:18 | |
gross pictures of themselves. | 0:06:18 | 0:06:21 | |
The catfish. Someone who's pretending to be somebody else. | 0:06:21 | 0:06:26 | |
You're never quite sure who's telling lies or not. | 0:06:26 | 0:06:30 | |
Let's face it - online, anybody can be anything they want. | 0:06:30 | 0:06:33 | |
In order to find Xand a date, I'm going to build an experimental | 0:06:36 | 0:06:40 | |
dating website with the help of my colleague Tom Russell. | 0:06:40 | 0:06:43 | |
This is one user's set of responses. | 0:06:44 | 0:06:47 | |
Some commercial dating sites use multiple layers of algorithms. | 0:06:47 | 0:06:51 | |
eHarmony claims they assess psychological compatibility | 0:06:51 | 0:06:55 | |
and interpersonal chemistry. | 0:06:55 | 0:06:57 | |
Lovestruck uses a recommendation engine based on search activity, | 0:06:57 | 0:07:01 | |
a bit like Netflix or Amazon. | 0:07:01 | 0:07:04 | |
Show me the bit where the scores for each question goes. | 0:07:04 | 0:07:08 | |
We're using a scored questionnaire that is similar to OkCupid. | 0:07:08 | 0:07:12 | |
So, if we have three levels, then... | 0:07:12 | 0:07:14 | |
Matching algorithms are useful because they help daters sort through | 0:07:14 | 0:07:18 | |
the vast numbers of potential partners available via online dating. | 0:07:18 | 0:07:23 | |
One of the problems with online dating is the paradox of choice. | 0:07:26 | 0:07:31 | |
It felt slightly overwhelming. | 0:07:31 | 0:07:33 | |
Surprised at the number of people who were there. | 0:07:33 | 0:07:35 | |
You can sit there for hours ploughing through people from all over the country. | 0:07:35 | 0:07:41 | |
It becomes like fishing, I guess. | 0:07:41 | 0:07:43 | |
I find it's, like, almost like a drudgery. | 0:07:43 | 0:07:45 | |
The commitment to time, is exhausting, it's mentally exhausting. | 0:07:45 | 0:07:49 | |
Xand is convinced that he can choose himself a better date | 0:07:51 | 0:07:54 | |
than my algorithm, but with thousands of potential dates | 0:07:54 | 0:07:57 | |
in New York and London to choose from, | 0:07:57 | 0:08:00 | |
I think he needs some mathematical help. | 0:08:00 | 0:08:03 | |
So, what you really need is an effective search strategy to help | 0:08:03 | 0:08:07 | |
you find the perfect woman for you, without having to date | 0:08:07 | 0:08:11 | |
-every single one of them. -OK. -I've got one. | 0:08:11 | 0:08:14 | |
Optimal stopping theory, it's called. | 0:08:14 | 0:08:16 | |
That is not what I thought you were going to say. OK. | 0:08:16 | 0:08:18 | |
So, it was invented in 1875 by a chap called Arthur Cayley, | 0:08:18 | 0:08:23 | |
essentially to gamble better, | 0:08:23 | 0:08:25 | |
and two Harvard mathematicians worked out the best chance you can | 0:08:25 | 0:08:29 | |
give yourself of stopping on The One, the perfect woman for you, | 0:08:29 | 0:08:33 | |
is to spend the first 37% of your dates just, kind of, not taking them too seriously, | 0:08:33 | 0:08:40 | |
having a nice time, getting a bit of a feel for the marketplace and so on. | 0:08:40 | 0:08:43 | |
And then after that 37% period has passed, | 0:08:43 | 0:08:46 | |
you should then pick the next woman to come along that is better than | 0:08:46 | 0:08:50 | |
everybody that you've seen before. | 0:08:50 | 0:08:53 | |
And if you do that, you're maximising your chances, | 0:08:53 | 0:08:55 | |
mathematically, of finding the perfect woman for you. | 0:08:55 | 0:08:59 | |
And what will the chances be of the one after 37%, | 0:08:59 | 0:09:03 | |
that one being the right woman for me? | 0:09:03 | 0:09:06 | |
Well, OK. So, if you pick somebody completely at random | 0:09:06 | 0:09:09 | |
in your list of 100 and just chose that person to go on your date with, | 0:09:09 | 0:09:12 | |
your chance of getting the best person in your list | 0:09:12 | 0:09:14 | |
would be 1%, right? One in 100. | 0:09:14 | 0:09:17 | |
But this technique - just having that little rejection phase of 37% at the beginning - | 0:09:17 | 0:09:22 | |
means that you increase your chances all the way from 1% to 37%. | 0:09:22 | 0:09:27 | |
If the number of potential dates, n, for Xand is 100, | 0:09:27 | 0:09:31 | |
his chance of success, P, is highest when he rejects | 0:09:31 | 0:09:35 | |
37% of potential partners. | 0:09:35 | 0:09:38 | |
His success rate drops off if he either reduces | 0:09:38 | 0:09:42 | |
or increases his rejection phase, r, | 0:09:42 | 0:09:46 | |
the time before he starts thinking seriously about a match. | 0:09:46 | 0:09:49 | |
OK, that is an amazing bit of maths. That is extraordinary. | 0:09:49 | 0:09:53 | |
So, imagine you decide to take 100 people, | 0:09:53 | 0:10:00 | |
reject the first 37 of them | 0:10:00 | 0:10:03 | |
and then pick the next person who comes along that's better than | 0:10:03 | 0:10:06 | |
everyone you've seen before and take that person on a date. | 0:10:06 | 0:10:10 | |
Wow! | 0:10:10 | 0:10:12 | |
-OK, so 100 people seems reasonable. -Yeah, it's not crazy. | 0:10:12 | 0:10:15 | |
-Yeah, I can entertain 100 people. -Of course. -OK, so I just start... | 0:10:15 | 0:10:18 | |
Two, three, four... | 0:10:18 | 0:10:20 | |
Are there some of these that you would swipe right to? | 0:10:20 | 0:10:23 | |
This person, I would definitely swipe right for. | 0:10:23 | 0:10:26 | |
She looks lovely and according to you, I have to reject her, | 0:10:26 | 0:10:29 | |
because you told me to. | 0:10:29 | 0:10:30 | |
-So, like, this person seems nice. Nope, get rid of them. -Yeah. | 0:10:30 | 0:10:33 | |
So, you carry on swiping left for the entire time | 0:10:33 | 0:10:35 | |
and then you end up, well, probably dying alone... | 0:10:35 | 0:10:38 | |
SHE LAUGHS | 0:10:38 | 0:10:39 | |
..nursing a deep hatred of mathematical formulas! | 0:10:39 | 0:10:43 | |
-And mathematicians! -Yeah, probably. | 0:10:43 | 0:10:45 | |
You and the two guys at Harvard, primarily. | 0:10:45 | 0:10:48 | |
Back at home, I test Hannah's optimal stopping theory | 0:10:54 | 0:10:57 | |
on a commercial dating app. | 0:10:57 | 0:10:59 | |
I'm rejecting 37 potential dates. | 0:10:59 | 0:11:03 | |
And now the first person I see | 0:11:03 | 0:11:05 | |
who's better than everyone I've just rejected... | 0:11:05 | 0:11:09 | |
is Miss Right. | 0:11:09 | 0:11:10 | |
So, at 62, I decided to swipe right | 0:11:13 | 0:11:17 | |
and I think that this person was better than all the others. | 0:11:17 | 0:11:20 | |
I will send her a message and see if we can go on a date. | 0:11:20 | 0:11:23 | |
Well, I'm delighted she said yes and she's drop-dead gorgeous. | 0:11:26 | 0:11:30 | |
Do it again! | 0:11:30 | 0:11:32 | |
She's even volunteered to film the date | 0:11:41 | 0:11:43 | |
and tell me about her online dating experiences. | 0:11:43 | 0:11:46 | |
Surely, eHarmony's loss! | 0:11:55 | 0:11:57 | |
But as the date wore on, I wasn't convinced we were compatible. | 0:11:57 | 0:12:00 | |
It can be edited. | 0:12:00 | 0:12:03 | |
I started to wonder whether Hannah's optimal stopping theory had worked in this case. | 0:12:10 | 0:12:15 | |
I sincerely apologise for meeting Xand. | 0:12:15 | 0:12:17 | |
Well, I'm heading into work after my date with my supposed | 0:12:22 | 0:12:25 | |
Miss Right yesterday and it didn't work out. | 0:12:25 | 0:12:29 | |
So, back to the drawing board. | 0:12:29 | 0:12:32 | |
I guess choosing a date based purely on appearances is always | 0:12:40 | 0:12:43 | |
going to be a gamble. | 0:12:43 | 0:12:45 | |
However, all dating apps and websites do require a photo, | 0:12:45 | 0:12:48 | |
so it's clear that looks are important to everyone. | 0:12:48 | 0:12:52 | |
It's all about first impressions. | 0:12:52 | 0:12:54 | |
The picture engages you, then you read the profile. | 0:12:54 | 0:12:57 | |
I mean, let's be honest, it all boils down to the photos, | 0:12:57 | 0:12:59 | |
at the end of the day. | 0:12:59 | 0:13:01 | |
But it's not just attractiveness we're judged on. | 0:13:01 | 0:13:04 | |
Researchers at Princeton University have recently proved that | 0:13:04 | 0:13:07 | |
people use faces to make split-second judgements about our personalities, as well. | 0:13:07 | 0:13:12 | |
I think you can tell a lot about a person from the way they look. | 0:13:13 | 0:13:16 | |
It's really easy to make snap judgements about people based on their photo. | 0:13:16 | 0:13:21 | |
I think you can tell kindness, you can tell if someone's got a sense of fun. | 0:13:21 | 0:13:25 | |
I'd like to think that I can read intelligence in somebody's face, | 0:13:25 | 0:13:29 | |
maybe even the sense of humour that they have. | 0:13:29 | 0:13:31 | |
And while these judgements might not be right, | 0:13:33 | 0:13:35 | |
scientists have found that people tend to agree on what features | 0:13:35 | 0:13:39 | |
make someone appear likeable, trustworthy or competent. | 0:13:39 | 0:13:42 | |
And just put your chin down slightly. | 0:13:42 | 0:13:44 | |
I want to find out what people think of me. | 0:13:44 | 0:13:48 | |
So, I'm sending my picture to Dr Chris Olivola. | 0:13:48 | 0:13:51 | |
He's analysed hundreds of real online daters' reactions to profile | 0:13:51 | 0:13:55 | |
pictures and has discovered what facial attributes are most popular. | 0:13:55 | 0:13:59 | |
So, at least one of the websites I used is entirely based on | 0:14:02 | 0:14:05 | |
-swiping on pictures of people. -Yes, I know what that site is. | 0:14:05 | 0:14:08 | |
-Yeah, so in that case, photos seem to be totally essential. -Yes. | 0:14:08 | 0:14:13 | |
So, for women searching for men, they do care about attractiveness, | 0:14:13 | 0:14:16 | |
physical attractiveness, | 0:14:16 | 0:14:18 | |
but they also care about how fun and outgoing you are. | 0:14:18 | 0:14:21 | |
How warm and approachable you are. | 0:14:21 | 0:14:23 | |
So, if your goal is to try and get as many women interested in you as possible, | 0:14:23 | 0:14:28 | |
then looking more fun and outgoing is going to boost your chances | 0:14:28 | 0:14:31 | |
separately from looking more physically attractive. | 0:14:31 | 0:14:34 | |
OK. | 0:14:34 | 0:14:36 | |
To see if my face is generally perceived as fun and outgoing, | 0:14:36 | 0:14:40 | |
Chris has mapped my photo onto a 3-D model of a generic head. | 0:14:40 | 0:14:44 | |
-And, there we go. -Oh! -It doesn't do hair, so... | 0:14:45 | 0:14:49 | |
Looking at me there, I think I don't look competent, | 0:14:49 | 0:14:52 | |
I don't think I look particularly trustworthy | 0:14:52 | 0:14:54 | |
and I certainly don't think I look likeable. | 0:14:54 | 0:14:57 | |
With no hair and the computer's identification mark stamped on my forehead, | 0:14:57 | 0:15:01 | |
I think I look more like a cage fighter than a potential lover. | 0:15:01 | 0:15:04 | |
But what I think is irrelevant. | 0:15:04 | 0:15:06 | |
The computer program engineered by Chris's colleague Alex Todorov | 0:15:07 | 0:15:11 | |
combines the collective opinions of hundreds of people comparing | 0:15:11 | 0:15:14 | |
thousands of different faces. | 0:15:14 | 0:15:17 | |
-The model tells us your face looks likeable. -OK. | 0:15:17 | 0:15:20 | |
-You do also look trustworthy. -Oh! | 0:15:20 | 0:15:23 | |
In terms of competence, you have a fairly competent-looking face. | 0:15:23 | 0:15:27 | |
-Oh, wow! OK. Great. -Yes. | 0:15:27 | 0:15:29 | |
What about the other things, then? | 0:15:29 | 0:15:32 | |
Fairly extroverted and quite dominant at the same time. | 0:15:32 | 0:15:35 | |
So, I think you have a face that's good for dating and job interviews, | 0:15:35 | 0:15:38 | |
which is great. I think most people, usually, it's one or the other. | 0:15:38 | 0:15:41 | |
It's very odd seeing this, because what I'm forgetting | 0:15:41 | 0:15:44 | |
is that these are not my character traits. | 0:15:44 | 0:15:46 | |
-You're not telling me about my personality. -No. | 0:15:46 | 0:15:49 | |
You're simply telling me what a bunch of people would say | 0:15:49 | 0:15:55 | |
about my character traits glimpsing my face. | 0:15:55 | 0:15:58 | |
Yes, our faces say a lot. | 0:15:58 | 0:16:00 | |
And Chris has a way of showing me | 0:16:00 | 0:16:02 | |
how to look more likeable and trustworthy. | 0:16:02 | 0:16:04 | |
-Again, this can change my face. -Yes. -Do it, do it. | 0:16:04 | 0:16:08 | |
-OK, so which one do you want first? -Make me more likeable. | 0:16:08 | 0:16:12 | |
-So, if I ramp up your likeability... -I get thinner! | 0:16:12 | 0:16:15 | |
-And you're smiling more. -Yeah, OK. | 0:16:15 | 0:16:18 | |
So smiling is a simple and easy tip. | 0:16:18 | 0:16:21 | |
-So, my eyebrows are a little further apart... -Yes. | 0:16:21 | 0:16:24 | |
-..and I'm slightly more smiley. -Yes. | 0:16:24 | 0:16:27 | |
And what about trustworthiness? If we increased that? | 0:16:27 | 0:16:31 | |
Dial it up. | 0:16:31 | 0:16:33 | |
See, that would be hard to do without plastic surgery. | 0:16:33 | 0:16:36 | |
The BBC are refusing to pay for plastic surgery, | 0:16:38 | 0:16:41 | |
so the only alternative is for me to try and take a more fun, | 0:16:41 | 0:16:45 | |
outgoing profile picture to boost my online appeal. | 0:16:45 | 0:16:48 | |
I have to say, I'm cringing right now, but if this is what it takes, | 0:16:50 | 0:16:54 | |
I guess I'll give it a go. | 0:16:54 | 0:16:56 | |
Someone once told me you have to cough out a laugh, so... | 0:16:57 | 0:17:00 | |
HE COUGHS | 0:17:00 | 0:17:01 | |
Yes, Xand. Simply smiling can help you look more fun and outgoing, | 0:17:05 | 0:17:10 | |
but choosing your own profile picture can be counterintuitive. | 0:17:10 | 0:17:15 | |
When you look through online dating websites' data, | 0:17:15 | 0:17:19 | |
it says that actually being different is the thing that counts. | 0:17:19 | 0:17:23 | |
Dividing opinion is much better than just having everybody think | 0:17:23 | 0:17:27 | |
that you're generically attractive. | 0:17:27 | 0:17:30 | |
But the trouble is, when it comes to being objective about yourself, | 0:17:30 | 0:17:33 | |
it's easier said than done. | 0:17:33 | 0:17:35 | |
I've asked photographer Scott Chasserot to demonstrate this. | 0:17:37 | 0:17:42 | |
Scott's going to take me through the process, which includes | 0:17:42 | 0:17:45 | |
having my portrait taken with no make-up or accessories, | 0:17:45 | 0:17:50 | |
which I'm not going to lie, I feel quite nervous about, | 0:17:50 | 0:17:53 | |
but never let your vanity get in the way of doing a good job! | 0:17:53 | 0:17:58 | |
So, here goes. | 0:17:58 | 0:18:01 | |
My face has to be completely clear of both make-up... | 0:18:01 | 0:18:04 | |
# Girls on film... # | 0:18:04 | 0:18:06 | |
..and hair. | 0:18:06 | 0:18:08 | |
# ..Girls on film... # | 0:18:08 | 0:18:09 | |
-These bits? -Yeah. -God, you're like the blooming hair police. | 0:18:09 | 0:18:11 | |
# ..Girls on film... # | 0:18:11 | 0:18:13 | |
It's quite important to keep a straight neck. | 0:18:13 | 0:18:15 | |
# ..Girls on film. # | 0:18:15 | 0:18:17 | |
Scott's going to manipulate my picture and show me | 0:18:19 | 0:18:22 | |
lots of different versions to compare what I think I think | 0:18:22 | 0:18:26 | |
is the most attractive, with my brain's reaction before I've | 0:18:26 | 0:18:30 | |
had time to consciously think about it. | 0:18:30 | 0:18:33 | |
An EEG monitor will measure electrical activity | 0:18:33 | 0:18:37 | |
in my cerebral cortex as I see each image. | 0:18:37 | 0:18:40 | |
But this consumer headset isn't foolproof | 0:18:40 | 0:18:43 | |
because facial expressions will give a false reading. | 0:18:43 | 0:18:47 | |
I mean, you can try it, if you smile... Look at that! | 0:18:47 | 0:18:50 | |
SHE LAUGHS | 0:18:50 | 0:18:51 | |
Yeah. Any movement, I can see it. | 0:18:51 | 0:18:53 | |
So, it would be very hard to separate that, | 0:18:53 | 0:18:55 | |
-tease that apart from what's actually going on in the brain. -Mm-hm. | 0:18:55 | 0:18:58 | |
So, this fun test requires my best poker face. | 0:18:58 | 0:19:02 | |
It's so weird! | 0:19:05 | 0:19:07 | |
But Scott's playing dirty, because as well as the original image, | 0:19:09 | 0:19:13 | |
he's shuffled in five versions of me that have been modified | 0:19:13 | 0:19:16 | |
according to theories about femininity, facial symmetry | 0:19:16 | 0:19:20 | |
and skin tone, | 0:19:20 | 0:19:22 | |
and five less attractive versions of me. | 0:19:22 | 0:19:25 | |
There are some that are really horrible. | 0:19:25 | 0:19:28 | |
By the end of the test, | 0:19:30 | 0:19:31 | |
I'm pretty confident about which version of myself I like the best. | 0:19:31 | 0:19:35 | |
I wouldn't mind being her! | 0:19:38 | 0:19:41 | |
But it's not until we get the results of the EEG back | 0:19:43 | 0:19:46 | |
from Scott's colleague in New York University | 0:19:46 | 0:19:49 | |
that we can see what my pre-conscious brain found | 0:19:49 | 0:19:53 | |
the most striking. | 0:19:53 | 0:19:54 | |
The results have shown that you've had a strongest reaction | 0:19:54 | 0:19:58 | |
to the sixth of those 11 images. So, that's one towards... | 0:19:58 | 0:20:02 | |
-Beauty. -To beauty, yeah. | 0:20:02 | 0:20:04 | |
-And can it see what image this one is, though? -Yeah. So... | 0:20:04 | 0:20:08 | |
That is not the one I was expecting you to show. | 0:20:08 | 0:20:11 | |
-I don't even really like that picture. -Right. | 0:20:11 | 0:20:15 | |
See, I think that looks like I'm on a two-week holiday in Magaluf | 0:20:15 | 0:20:18 | |
and have spent a bit too much money on fake tan. | 0:20:18 | 0:20:21 | |
Which one were you expecting to see? | 0:20:21 | 0:20:23 | |
I thought it would be the one where you'd done... | 0:20:23 | 0:20:27 | |
you'd changed everything. | 0:20:27 | 0:20:29 | |
Where I had still quite dark eyes, but I had a smaller jaw, | 0:20:29 | 0:20:33 | |
thinner face, thinner nose, | 0:20:33 | 0:20:35 | |
you'd pinned my ears back, you'd made my neck longer. | 0:20:35 | 0:20:38 | |
Yeah. Yeah, that was the one. | 0:20:38 | 0:20:39 | |
That was certainly the one that I picked out as my favourite. | 0:20:39 | 0:20:42 | |
Right, your verbal choice was that one, yeah. | 0:20:42 | 0:20:46 | |
I consciously preferred the picture | 0:20:46 | 0:20:48 | |
that has been made much more feminine, | 0:20:48 | 0:20:50 | |
but my pre-conscious brain paid more attention to the image where only my | 0:20:50 | 0:20:54 | |
skin tone had changed. | 0:20:54 | 0:20:57 | |
A scientific study has shown that this carotenoid skin tone | 0:20:57 | 0:21:01 | |
is considered more attractive than pale skin, | 0:21:01 | 0:21:04 | |
yet my rational brain discarded this image. This shows why it can be | 0:21:04 | 0:21:09 | |
difficult to pick the best picture to represent ourselves online. | 0:21:09 | 0:21:14 | |
And I think the real lesson there is that when it comes to choosing | 0:21:14 | 0:21:17 | |
an online dating profile picture, | 0:21:17 | 0:21:18 | |
you should really get your friends to help you. | 0:21:18 | 0:21:21 | |
If my new picture is working, I should be more attractive to women. | 0:21:24 | 0:21:28 | |
But I don't want to spend even more time than I already do | 0:21:28 | 0:21:31 | |
swiping through potential dates. | 0:21:31 | 0:21:34 | |
Vancouver-based software engineer Justin Long came up with | 0:21:34 | 0:21:38 | |
a hi-tech solution to the problem of time-consuming searching. | 0:21:38 | 0:21:41 | |
I created an application that helps you automate everything on Tinder. | 0:21:41 | 0:21:45 | |
Using a computer program, or bot, to meet girls just sounds | 0:21:46 | 0:21:50 | |
a little dubious. | 0:21:50 | 0:21:51 | |
So, I've arranged an online chat with Justin. | 0:21:51 | 0:21:54 | |
I realised that after using Tinder for a while, | 0:21:55 | 0:21:57 | |
it became a situation where, you know, | 0:21:57 | 0:21:59 | |
I was using a lot of my time to swipe left and right | 0:21:59 | 0:22:03 | |
and it would be up to an hour or more a day... | 0:22:03 | 0:22:05 | |
And that's what I found I was doing. I think an hour a day | 0:22:05 | 0:22:08 | |
-is almost a conservative estimate. -Absolutely. | 0:22:08 | 0:22:11 | |
And the same with my friends. | 0:22:11 | 0:22:12 | |
If we were all out at a bar, or we were out at dinner, | 0:22:12 | 0:22:15 | |
everyone would be literally swiping left or right on their phones | 0:22:15 | 0:22:19 | |
and I figured, well, why not build a bot that actually automates this? | 0:22:19 | 0:22:22 | |
So, how does the bot work? | 0:22:22 | 0:22:24 | |
It looks at the facial structure of the person | 0:22:24 | 0:22:28 | |
and it's building a computer model behind the scenes of what | 0:22:28 | 0:22:31 | |
those people look like and it compares that facial structure | 0:22:31 | 0:22:35 | |
to the differences between other facial structures. | 0:22:35 | 0:22:37 | |
Because when you're swiping left and right, you're actually telling it | 0:22:37 | 0:22:41 | |
this is who I find attractive | 0:22:41 | 0:22:43 | |
and this is who I don't find attractive. | 0:22:43 | 0:22:45 | |
So, I've been using this bot that you built and now it knows what I like, | 0:22:45 | 0:22:48 | |
-it can make those decisions for me and I don't need to be involved any more. -Yes, that's right. | 0:22:48 | 0:22:52 | |
So, what's the next step? | 0:22:52 | 0:22:53 | |
This is actually where the bot gets more interesting. | 0:22:53 | 0:22:56 | |
And it actually saves you more time. | 0:22:56 | 0:22:58 | |
What you can do is you can customise the bot where you type in | 0:22:58 | 0:23:02 | |
your own messages to introduce yourself | 0:23:02 | 0:23:05 | |
and if they keep responding positively to your introductory messages, | 0:23:05 | 0:23:10 | |
you will then get a notification on your computer saying, | 0:23:10 | 0:23:13 | |
hey, this person's interested, you need to talk to them. | 0:23:13 | 0:23:16 | |
It's funny, I have this vague discomfort with the machine doing it all. | 0:23:16 | 0:23:20 | |
Did the people that you were talking to know that it was a bot? | 0:23:20 | 0:23:23 | |
No-one ever figured it out because even though you're having a bot | 0:23:23 | 0:23:27 | |
setting up the introduction, | 0:23:27 | 0:23:29 | |
you've still written the introduction yourself. | 0:23:29 | 0:23:31 | |
So, it's still you. | 0:23:31 | 0:23:32 | |
OK. All right. Look, thanks very much indeed, Justin. | 0:23:32 | 0:23:35 | |
-Not a problem. -Take care, bye. | 0:23:35 | 0:23:37 | |
I'm not sure getting a machine to choose me a date on the basis | 0:23:42 | 0:23:45 | |
of looks alone is going to be any more successful than my last date. | 0:23:45 | 0:23:49 | |
I'm about to go on my first Tinder bot date | 0:23:49 | 0:23:52 | |
and I don't know if it was more efficient than organising it myself, | 0:23:52 | 0:23:55 | |
but maybe it'll be a better date. | 0:23:55 | 0:23:57 | |
Maybe she'll just think I'm weirdo for using a robot. | 0:23:57 | 0:23:59 | |
Did you know you were talking to a computer? | 0:23:59 | 0:24:02 | |
Did that even cross your mind? | 0:24:02 | 0:24:04 | |
HE LAUGHS | 0:24:08 | 0:24:10 | |
-That is exactly what I was doing. -Yeah. -That's not cool, is it? | 0:24:15 | 0:24:19 | |
No-one wants to feel like you're one of hundreds. | 0:24:19 | 0:24:21 | |
'So, Tinder bot makes me look like a player and while I enjoyed the date, | 0:24:24 | 0:24:28 | |
'she thought I was a bit odd and we didn't click. Again.' | 0:24:28 | 0:24:32 | |
So far, my dates chosen randomly by looks alone haven't worked out. | 0:24:32 | 0:24:37 | |
So, I'm dumping the swipe apps | 0:24:37 | 0:24:39 | |
and I'm going to pay more attention to written profiles. | 0:24:39 | 0:24:43 | |
I think it's definitely more important what a person has written | 0:24:47 | 0:24:50 | |
about themselves than what they look like. | 0:24:50 | 0:24:53 | |
The profile takes quite a while, it's what sells you, | 0:24:53 | 0:24:56 | |
so you don't want to scrimp and save on it. | 0:24:56 | 0:24:58 | |
You can tell somebody's personality, from the way that they write. | 0:24:58 | 0:25:01 | |
And that can be quite nerve-racking in itself. | 0:25:01 | 0:25:04 | |
It's so important that you separate yourself | 0:25:04 | 0:25:06 | |
and make yourself definable. | 0:25:06 | 0:25:09 | |
Hannah's given me early access to the Horizon dating website. | 0:25:10 | 0:25:14 | |
It requires a detailed written profile, | 0:25:14 | 0:25:17 | |
but how should I describe myself to attract the most people online? | 0:25:17 | 0:25:20 | |
I'm seeking help from Professor Khalid Khan. | 0:25:23 | 0:25:26 | |
He analysed nearly 4,000 scientific papers to find the best method | 0:25:26 | 0:25:30 | |
of optimising an online dating profile | 0:25:30 | 0:25:33 | |
and published the results in a prestigious medical journal. | 0:25:33 | 0:25:37 | |
His friend and co-author Sameer Chaudry was the first to benefit. | 0:25:37 | 0:25:41 | |
Previously, seven years single, he had registered with four | 0:25:41 | 0:25:44 | |
different sites and went on hundreds of dates. | 0:25:44 | 0:25:47 | |
And then he applied the Khan technique. | 0:25:48 | 0:25:51 | |
And so what outcome did you get? | 0:25:51 | 0:25:53 | |
Within three dates, he was able to then find a partner with whom | 0:25:53 | 0:25:58 | |
-he is still in partnership for the last four years. -Wow! OK. | 0:25:58 | 0:26:03 | |
So, this all seems very good for me. | 0:26:03 | 0:26:05 | |
Horizon have built this online experimental dating site. | 0:26:05 | 0:26:09 | |
-Can you help me fill it out? -Sure. Let's have a go. -OK. | 0:26:09 | 0:26:12 | |
The first thing we've got to do is choose a username. | 0:26:12 | 0:26:16 | |
Everyone calls me Xand so, Xand seems like, I don't know, | 0:26:16 | 0:26:18 | |
XandVT would be kind of what I'd go towards. | 0:26:18 | 0:26:21 | |
-Do we have evidence about how to choose a username? -Yes. | 0:26:21 | 0:26:24 | |
I would propose that you consider something that is closer to the top | 0:26:24 | 0:26:28 | |
-of the alphabet. -Really? | 0:26:28 | 0:26:30 | |
Does that actually make a difference, | 0:26:30 | 0:26:32 | |
whether or not it's an A or an X? | 0:26:32 | 0:26:34 | |
It's more or less like the Yellow Pages effect, | 0:26:34 | 0:26:37 | |
in that the traders listed at the top of the alphabet | 0:26:37 | 0:26:41 | |
tend to receive more calls for their business | 0:26:41 | 0:26:44 | |
-than those at the bottom of the alphabet. -OK. | 0:26:44 | 0:26:46 | |
So, the next bit of the site says tell us a bit about yourself, | 0:26:46 | 0:26:49 | |
sell yourself in less than 250 words. | 0:26:49 | 0:26:52 | |
And this is my nightmare. | 0:26:52 | 0:26:54 | |
I think this is one of the big barriers to online dating, | 0:26:54 | 0:26:56 | |
because no-one knows what to put. | 0:26:56 | 0:26:58 | |
You don't want to be boastful, you want to be humble, but you need to sell yourself - | 0:26:58 | 0:27:01 | |
it's like this impossible balance of stuff. | 0:27:01 | 0:27:04 | |
So, what do women look for in this kind of thing? | 0:27:04 | 0:27:06 | |
So, the important thing to understand is that, in general, | 0:27:06 | 0:27:09 | |
women prefer that men demonstrate courageousness, | 0:27:09 | 0:27:13 | |
they prefer the ability to take risks | 0:27:13 | 0:27:16 | |
and they don't particularly like submissiveness or kindness. | 0:27:16 | 0:27:23 | |
-So, just being a nice guy is not necessarily the best pitch. -Really?! | 0:27:23 | 0:27:28 | |
-So, nice guys finish last, basically. -That is correct. | 0:27:28 | 0:27:31 | |
I mean, that's a bit depressing, isn't it? This is my problem. | 0:27:33 | 0:27:37 | |
I'm too nice! | 0:27:37 | 0:27:39 | |
It sounds almost like a cliche, | 0:27:39 | 0:27:41 | |
but Khalid's meta-analysis of other scientific studies proves that | 0:27:41 | 0:27:44 | |
in the absence of familiarity, women do prefer bravery over altruism. | 0:27:44 | 0:27:49 | |
So, I'm not trying to sell myself as a humanitarian, | 0:27:50 | 0:27:53 | |
it's better to say - I don't know, what have I done? | 0:27:53 | 0:27:57 | |
Like, I've worked in war zones, you know. | 0:27:57 | 0:27:59 | |
I should emphasise that rather than saying I fed starving children. | 0:27:59 | 0:28:02 | |
-That's correct. -And what about the tone of this? Is humour important? | 0:28:02 | 0:28:06 | |
Humour is important and it is also important to demonstrate humour | 0:28:06 | 0:28:09 | |
-without saying the words. -Be funny, don't say you're funny. -Yes. -OK. | 0:28:09 | 0:28:14 | |
So, I'm going to do this now and I will let you know how I get on. | 0:28:14 | 0:28:20 | |
I wish you very good luck in making progress. | 0:28:20 | 0:28:23 | |
-I hope your outcome will be... -As good as Sameer's? | 0:28:23 | 0:28:26 | |
As good as Sameer's, yes. | 0:28:26 | 0:28:28 | |
Xand needs to hurry up and write his profile, | 0:28:30 | 0:28:33 | |
because we're about to open the website to the public. | 0:28:33 | 0:28:36 | |
The challenge is Xand choosing a girl himself | 0:28:36 | 0:28:39 | |
versus my algorithm matching for him. | 0:28:39 | 0:28:42 | |
I think that online dating sites can match people. | 0:28:42 | 0:28:45 | |
I think it's totally possible. | 0:28:45 | 0:28:47 | |
I guess from our perspective, | 0:28:47 | 0:28:49 | |
we feel like we were matched really well. | 0:28:49 | 0:28:51 | |
98 to 99% match. | 0:28:51 | 0:28:54 | |
It's just maths. Maths got us together. | 0:28:54 | 0:28:56 | |
-We're definitely pro-algorithm! -Yeah. | 0:28:56 | 0:28:59 | |
Just like commercial websites, | 0:29:00 | 0:29:02 | |
the Horizon algorithm takes inputs from an extensive questionnaire. | 0:29:02 | 0:29:06 | |
Now, our website is based on three inputs in total. | 0:29:06 | 0:29:09 | |
First, it asks you a questionnaire to find out a little bit about you. | 0:29:09 | 0:29:13 | |
It also asks you what type of things you're looking for in your partner. | 0:29:13 | 0:29:17 | |
And thirdly and most importantly, it allows you to rate how important | 0:29:17 | 0:29:22 | |
those characteristics are in a potential date. | 0:29:22 | 0:29:25 | |
Now, this last bit is particularly important, | 0:29:25 | 0:29:28 | |
because you have to have room to set those criteria yourself, | 0:29:28 | 0:29:32 | |
rather than have a computer set them for you. | 0:29:32 | 0:29:35 | |
Now, our questionnaire has almost 300 questions, | 0:29:35 | 0:29:39 | |
so it should give us a really rich understanding of both the people | 0:29:39 | 0:29:42 | |
that are signing up and how good they'll be for Xand to date. | 0:29:42 | 0:29:46 | |
But the problem is, is that ultimately a lot of people | 0:29:46 | 0:29:49 | |
just don't really know what they want until they find it | 0:29:49 | 0:29:52 | |
and I'm slightly concerned that that might be Xand's problem. | 0:29:52 | 0:29:56 | |
Maybe not knowing what I should be looking for | 0:30:00 | 0:30:02 | |
has always been my problem. I've been on loads of dates | 0:30:02 | 0:30:05 | |
but I'm still no closer to finding a soulmate. | 0:30:05 | 0:30:08 | |
I'm on top of the Empire State Building. | 0:30:13 | 0:30:15 | |
Now, this is meant to be | 0:30:15 | 0:30:16 | |
one of the most romantic locations in the world. | 0:30:16 | 0:30:19 | |
King Kong met his end here looking for love. | 0:30:19 | 0:30:22 | |
Tom Hanks did a little better. | 0:30:22 | 0:30:24 | |
We know that a New York minute | 0:30:24 | 0:30:25 | |
can be crammed with sex in the city, but what about love? | 0:30:25 | 0:30:29 | |
Well, they say that if you can make it here, you can make it anywhere, | 0:30:29 | 0:30:32 | |
but in five years, it hasn't worked out for me. | 0:30:32 | 0:30:35 | |
Did Frank Sinatra set the bar just a little bit too high? | 0:30:35 | 0:30:38 | |
Why haven't I found love? | 0:30:38 | 0:30:40 | |
And why do we fall in love with some people and not others? | 0:30:40 | 0:30:43 | |
One online dating company was keen to find the answer, | 0:30:45 | 0:30:48 | |
so approached a scientist who has spent 30 years studying love | 0:30:48 | 0:30:51 | |
and attraction, Dr Helen Fisher. | 0:30:51 | 0:30:54 | |
Helen is an expert on what's happening in your brain when you're in love. | 0:30:54 | 0:30:58 | |
She's now taking this one step further, | 0:30:58 | 0:31:00 | |
claiming she can match people using a personality questionnaire. | 0:31:00 | 0:31:04 | |
But as she hasn't yet published her scientific paper, | 0:31:04 | 0:31:07 | |
I'm curious to find out how it works. | 0:31:07 | 0:31:10 | |
So, how did you come up with the questionnaire? | 0:31:10 | 0:31:12 | |
I had studied dopamine in the brain. So, I pulled out a sheet of paper | 0:31:12 | 0:31:15 | |
and I wrote down "dopamine" at the top of the paper and I listed all | 0:31:15 | 0:31:18 | |
of the traits that are linked with the dopamine system in the brain. | 0:31:18 | 0:31:22 | |
Being curious, creative, spontaneous, energetic, | 0:31:22 | 0:31:25 | |
risk-taking, novelty-seeking, mentally flexible. | 0:31:25 | 0:31:30 | |
I saw that list and I said, | 0:31:30 | 0:31:32 | |
"Well, you also know something about serotonin system in the brain," | 0:31:32 | 0:31:35 | |
and so I wrote "serotonin" on another sheet of paper | 0:31:35 | 0:31:37 | |
and I listed the traits linked with the serotonin system. | 0:31:37 | 0:31:40 | |
Being traditional, conventional, following the rules, | 0:31:40 | 0:31:43 | |
respecting authority. | 0:31:43 | 0:31:45 | |
And I had written a book on gender differences in the brain, | 0:31:45 | 0:31:48 | |
so I knew the traits linked with the testosterone system | 0:31:48 | 0:31:50 | |
and the oestrogen system, so I said, "I'm going to make a questionnaire | 0:31:50 | 0:31:54 | |
"to see the degree to which you express the traits | 0:31:54 | 0:31:57 | |
"linked with all four of these brain systems, | 0:31:57 | 0:32:01 | |
"and then watch on this dating site who's naturally drawn to whom." | 0:32:01 | 0:32:05 | |
Oh, wow! So, what happens? | 0:32:05 | 0:32:07 | |
Well, as it turns out, | 0:32:07 | 0:32:09 | |
people who are very expressive of the dopamine system - | 0:32:09 | 0:32:12 | |
I call them explorers - | 0:32:12 | 0:32:13 | |
they're naturally drawn to people like themselves. | 0:32:13 | 0:32:16 | |
People who are very expressive in the serotonin system - | 0:32:16 | 0:32:18 | |
I call them builders - they tend to be... | 0:32:18 | 0:32:20 | |
Traditional goes for traditional. | 0:32:20 | 0:32:22 | |
Traditional people want traditional people. | 0:32:22 | 0:32:24 | |
In those two cases, similarity attracts. | 0:32:24 | 0:32:27 | |
In the other two cases, opposites attract. | 0:32:27 | 0:32:29 | |
The high testosterone - analytical, logical, direct, decisive - | 0:32:29 | 0:32:32 | |
goes for the high oestrogen - empathetic, emotionally expressive, | 0:32:32 | 0:32:36 | |
good with people. So those two types go for their opposite. | 0:32:36 | 0:32:40 | |
Helen collected data from 40,000 people on the dating website | 0:32:41 | 0:32:45 | |
and although she hasn't published it yet, she says it proves her theory. | 0:32:45 | 0:32:49 | |
Testosterone-driven directors were drawn to | 0:32:49 | 0:32:52 | |
oestrogen-driven negotiators. | 0:32:52 | 0:32:54 | |
But serotonin-driven builders and dopamine-driven explorers | 0:32:54 | 0:32:58 | |
got on best with personality types like themselves. | 0:32:58 | 0:33:03 | |
So, if I take your personality questionnaire, you should be able to | 0:33:03 | 0:33:06 | |
figure out a lot more about who I am likely to be attracted to. | 0:33:06 | 0:33:11 | |
Yes. Absolutely. | 0:33:11 | 0:33:13 | |
Without seeing the data myself, it's difficult to know if it stands up, | 0:33:14 | 0:33:18 | |
but I'd like to test Helen's theory | 0:33:18 | 0:33:20 | |
with help from my married twin brother. | 0:33:20 | 0:33:23 | |
Our personalities are quite similar, but they're not identical, are they? | 0:33:23 | 0:33:27 | |
Why are you talking about this? Do the test and then you'll find out. | 0:33:27 | 0:33:30 | |
That's the difference! | 0:33:30 | 0:33:32 | |
Will Chris and his wife fit Helen's theory? | 0:33:34 | 0:33:36 | |
If Chris and I are the same, then maybe his wife's personality | 0:33:36 | 0:33:39 | |
might be a good indicator of what I should be looking for. | 0:33:39 | 0:33:42 | |
I can change my mind easily. Yes. | 0:33:42 | 0:33:44 | |
No! | 0:33:44 | 0:33:45 | |
Yes. | 0:33:45 | 0:33:47 | |
Will you do the test?! | 0:33:47 | 0:33:48 | |
Both Helen and her research associate, neurologist Lucy Brown, | 0:33:51 | 0:33:55 | |
have been looking at our questionnaires | 0:33:55 | 0:33:58 | |
and I've come to see what they think. | 0:33:58 | 0:34:00 | |
You were just a little bit more of an explorer than he. | 0:34:00 | 0:34:03 | |
He's a little bit more expressive, actually, of the oestrogen system | 0:34:03 | 0:34:06 | |
and you're just a tiny little bit more expressive of the dopamine system. | 0:34:06 | 0:34:10 | |
But you're very, very similar. | 0:34:10 | 0:34:12 | |
So, biologically speaking, | 0:34:12 | 0:34:14 | |
the woman that you end up falling in love with, she's going to have some | 0:34:14 | 0:34:17 | |
of these basic personality traits that your brother's wife also has. | 0:34:17 | 0:34:21 | |
Wow! OK, OK. | 0:34:21 | 0:34:23 | |
So, according to the personality questionnaire, | 0:34:23 | 0:34:26 | |
what kind of people should I be looking for? | 0:34:26 | 0:34:28 | |
Well, certainly other explorers like yourself. | 0:34:28 | 0:34:30 | |
Otherwise, I think that you'll get bored. | 0:34:30 | 0:34:33 | |
Helen's theory about the personality matching runs true for Chris | 0:34:35 | 0:34:38 | |
and his wife Dinah. She, like him, is an explorer. | 0:34:38 | 0:34:41 | |
But how deep is their love? | 0:34:41 | 0:34:43 | |
Thanks to neuroscience, we should be able to see if the love is there. | 0:34:43 | 0:34:49 | |
We can now scan people and find out whether they're really in love. | 0:34:49 | 0:34:52 | |
In fact, we have had the experience of someone about to get married, | 0:34:52 | 0:34:57 | |
and I didn't see anything | 0:34:57 | 0:34:59 | |
and it was someone I knew and I didn't know really what to say. | 0:34:59 | 0:35:02 | |
-She was divorced within a year. -HE GASPS | 0:35:02 | 0:35:05 | |
-Really?! -Yes. -Yeah. -Oh! -Yeah. | 0:35:05 | 0:35:08 | |
There's a bit of "I told you so" there. Yeah, OK. | 0:35:08 | 0:35:13 | |
In an act of brotherly love, Chris has agreed to put his marriage | 0:35:14 | 0:35:17 | |
under the microscope - or rather, the MRI scanner - | 0:35:17 | 0:35:21 | |
to find out how much he loves his explorer wife. | 0:35:21 | 0:35:24 | |
That's a nice picture of Dinah you've chosen. Or did she choose it? | 0:35:29 | 0:35:32 | |
It's a picture that Dinah chose! | 0:35:32 | 0:35:33 | |
HE LAUGHS | 0:35:33 | 0:35:35 | |
-OK, it's starting now. -OK. | 0:35:35 | 0:35:37 | |
OK. | 0:35:41 | 0:35:43 | |
And as I'm not in love, I'm the control. | 0:35:43 | 0:35:47 | |
I'm looking at an ex-girlfriend from nine years ago. | 0:35:47 | 0:35:50 | |
I shan't identify her as she's moved on in her life. | 0:35:50 | 0:35:54 | |
But as I'm still single, I'm starting to wonder | 0:35:54 | 0:35:56 | |
if my brain is equipped for romance. | 0:35:56 | 0:35:59 | |
What do you find when you scan Chris's brain versus my brain? | 0:35:59 | 0:36:02 | |
So, first let's look at Chris's brain here. | 0:36:02 | 0:36:05 | |
So, here's the brainstem and there's the ventral tegmental area. | 0:36:05 | 0:36:09 | |
It's red and yellow. | 0:36:09 | 0:36:10 | |
And he showed up a robust activation | 0:36:10 | 0:36:15 | |
in that area in response to his wife. | 0:36:15 | 0:36:18 | |
I love the idea that Chris says he's madly in love and you say, | 0:36:18 | 0:36:21 | |
"Yes, he has a robust activation in his ventral tegmental area." | 0:36:21 | 0:36:26 | |
Like that's great, that's proper science, isn't it? | 0:36:26 | 0:36:29 | |
-He's madly in love with his wife. -So, he is madly in love. | 0:36:29 | 0:36:31 | |
Good, they're not just putting on a good show. | 0:36:31 | 0:36:33 | |
There's another sweet thing here. | 0:36:33 | 0:36:35 | |
This is called the dorsolateral prefrontal cortex, | 0:36:35 | 0:36:38 | |
but it's a very cognitive area. | 0:36:38 | 0:36:40 | |
I mean, this is an area of the brain that you use to do higher-level | 0:36:40 | 0:36:44 | |
cognitive things, like spatial calculations, that kind of thing. | 0:36:44 | 0:36:48 | |
And even reasoning. | 0:36:48 | 0:36:49 | |
And reasoning. Reasoning is a great way to summarise it. | 0:36:49 | 0:36:53 | |
And he's shutting it down. | 0:36:53 | 0:36:56 | |
-He's literally not thinking. -Yeah. | 0:36:56 | 0:36:59 | |
Chris is also deactivating an area involved in social judgment - | 0:36:59 | 0:37:03 | |
in other words, he's not being critical of his wife. | 0:37:03 | 0:37:06 | |
So, if you just lived with a friend, them leaving the toilet seat up | 0:37:06 | 0:37:10 | |
would drive you crazy, | 0:37:10 | 0:37:11 | |
but you forgive it in the person you're in love with. | 0:37:11 | 0:37:13 | |
You overlook the negative. | 0:37:13 | 0:37:15 | |
And I would guess that it evolved for a very important purpose. | 0:37:15 | 0:37:19 | |
I mean, this is going to be your breeding partner, you're going | 0:37:19 | 0:37:22 | |
to spend years trying to raise some DNA together | 0:37:22 | 0:37:25 | |
and it would be very adaptive to be able to overlook | 0:37:25 | 0:37:29 | |
the toilet seat issue. | 0:37:29 | 0:37:31 | |
So, if you are with someone that you know really likes you, | 0:37:31 | 0:37:34 | |
you can pretty much behave as you want?! Is that... | 0:37:34 | 0:37:37 | |
That's what I'm taking away from this! Great. | 0:37:37 | 0:37:41 | |
-I hadn't thought of that. -No, me neither. | 0:37:41 | 0:37:44 | |
So, Chris has really got the full package here, hasn't he? | 0:37:44 | 0:37:47 | |
So, he's got intense romantic love | 0:37:47 | 0:37:49 | |
and he's suppressing negative thoughts and he's also foolish. | 0:37:49 | 0:37:53 | |
He's suppressing his thoughts in general. | 0:37:53 | 0:37:55 | |
Like, he's just a love fool with her. | 0:37:55 | 0:37:57 | |
For you, you were looking at a former girlfriend | 0:37:57 | 0:38:00 | |
and you also show that suspension of negative judgment, | 0:38:00 | 0:38:05 | |
ability to overlook some of her faults. | 0:38:05 | 0:38:09 | |
She is the latest, flakiest person I know and I forgive her every time. | 0:38:09 | 0:38:14 | |
Oh! That's great! | 0:38:14 | 0:38:17 | |
No, no. It's true, it's true, it's true. | 0:38:17 | 0:38:20 | |
In anyone else, it would drive me crazy, | 0:38:20 | 0:38:22 | |
but I'm enormously fond of her. Yeah, yeah. | 0:38:22 | 0:38:24 | |
So, it's not that my brain is simply poorly equipped for romantic love? | 0:38:24 | 0:38:28 | |
No, it's well equipped. | 0:38:28 | 0:38:31 | |
So, I'm just as capable of overlooking the negative | 0:38:31 | 0:38:34 | |
as my brother, which is great news. | 0:38:34 | 0:38:36 | |
But Lucy has spotted some other brain activity. | 0:38:36 | 0:38:39 | |
This is all your somatosensory system, | 0:38:39 | 0:38:42 | |
and there's a huge red blob there. | 0:38:42 | 0:38:45 | |
As you know, there is a body map, right? | 0:38:45 | 0:38:49 | |
-Yes. The homunculus. -The homunculus. | 0:38:49 | 0:38:52 | |
So, leg, arm, face... | 0:38:52 | 0:38:54 | |
and the genitals, I know... | 0:38:54 | 0:38:56 | |
HE LAUGHS | 0:38:56 | 0:38:58 | |
-And that became active? -Yes. -Really? | 0:38:58 | 0:39:00 | |
-Really?! -Yes. | 0:39:00 | 0:39:02 | |
HE LAUGHS | 0:39:02 | 0:39:05 | |
That's very funny. So, this is very strange, | 0:39:05 | 0:39:08 | |
to sit with you looking at my brain and you're going...right there. | 0:39:08 | 0:39:12 | |
-Right. -That's where your genitals lit up. | 0:39:12 | 0:39:15 | |
There really is no hiding how you feel from these scientists. | 0:39:16 | 0:39:19 | |
But I'm happy that my brain has the capacity for love. | 0:39:19 | 0:39:24 | |
It's renewed my enthusiasm for online dating | 0:39:24 | 0:39:27 | |
and given me an insight into | 0:39:27 | 0:39:29 | |
the personality type I should be trying to choose. | 0:39:29 | 0:39:31 | |
-Cuddling? -Yeah, cuddling is very important. -Everyone loves cuddling. | 0:39:34 | 0:39:37 | |
The Horizon website has been live for five weeks now | 0:39:37 | 0:39:40 | |
and there are plenty of women for Xand to choose from. | 0:39:40 | 0:39:43 | |
But will the algorithm do better than him? | 0:39:43 | 0:39:46 | |
It's matching on shared values and ideals, | 0:39:46 | 0:39:49 | |
rather than personality traits. | 0:39:49 | 0:39:51 | |
They've got a very good match at 82. | 0:39:51 | 0:39:53 | |
But we're not just looking for a girl for Xand. | 0:39:53 | 0:39:57 | |
200 men and women of all ages and orientations | 0:39:57 | 0:40:00 | |
have signed up to the site and some will be invited | 0:40:00 | 0:40:03 | |
to the event where we test the matching system. | 0:40:03 | 0:40:06 | |
-And they look pretty amenable, right? -Mm-hm. | 0:40:06 | 0:40:09 | |
They're quite happy to get on with a lot of people. | 0:40:09 | 0:40:11 | |
Because it's a relatively small sample size, our algorithm | 0:40:11 | 0:40:15 | |
only matches one couple at 85%. | 0:40:15 | 0:40:19 | |
But when we reduce the match percentage, | 0:40:19 | 0:40:21 | |
more and more people become compatible with each other. | 0:40:21 | 0:40:24 | |
So, we know that this is a group of people who are quite intelligent, | 0:40:24 | 0:40:28 | |
who like science - goes without saying - | 0:40:28 | 0:40:30 | |
but find geekiness quite sexy. | 0:40:30 | 0:40:33 | |
This is a group of people who are quite romantic, | 0:40:33 | 0:40:36 | |
who are looking for a long-term relationships, | 0:40:36 | 0:40:38 | |
rather than just hook-ups, | 0:40:38 | 0:40:39 | |
but they also like beer and are very open to new ideas. | 0:40:39 | 0:40:44 | |
So, generally a good bunch, I think. | 0:40:44 | 0:40:47 | |
It's boding well for finding a date for Xand, | 0:40:47 | 0:40:49 | |
but I want to dig into some of the things I know are important to him. | 0:40:49 | 0:40:53 | |
What about the cats question, though? | 0:40:53 | 0:40:55 | |
Because I know cats is very important for Xand. | 0:40:55 | 0:40:57 | |
So, the algorithm has given us a shortlist. | 0:40:57 | 0:41:01 | |
We think that there are two, maybe three matches | 0:41:01 | 0:41:05 | |
that we can set up for Xand of potential dates. | 0:41:05 | 0:41:08 | |
But do all daters believe these algorithms work? | 0:41:10 | 0:41:14 | |
The matching's easy, it's the chemistry bit which is the hard bit. | 0:41:14 | 0:41:18 | |
I don't think it can just boil down to a computer program that decides | 0:41:18 | 0:41:21 | |
whether you get on with somebody or not. | 0:41:21 | 0:41:23 | |
I like to think that love is much more impulsive and spontaneous | 0:41:23 | 0:41:26 | |
than science can ever create. | 0:41:26 | 0:41:27 | |
Lots of people tell you that their eyes met across a crowded bar | 0:41:27 | 0:41:30 | |
and from that moment onwards they were smitten, and that's not | 0:41:30 | 0:41:33 | |
an algorithm or a spreadsheet that's telling them that. | 0:41:33 | 0:41:36 | |
That's something that if you could bottle it, you'd be extremely rich. | 0:41:36 | 0:41:40 | |
Online dating is lucrative business | 0:41:41 | 0:41:44 | |
and some websites make strong claims about their algorithm's ability | 0:41:44 | 0:41:47 | |
to find people's soulmates. | 0:41:47 | 0:41:50 | |
But social psychologist Eli Finkel doesn't believe the hype. | 0:41:50 | 0:41:53 | |
He can't prove it, because the sites haven't disclosed their algorithms, | 0:41:53 | 0:41:57 | |
but in his paper critiquing the industry, he argues that dating | 0:41:57 | 0:42:00 | |
companies haven't published any evidence to support their claims. | 0:42:00 | 0:42:04 | |
They have spent hundreds of millions of dollars telling the world that | 0:42:05 | 0:42:08 | |
there are soulmates, but it turns out that even believing that there | 0:42:08 | 0:42:13 | |
is such a thing as a soulmate tends to be destructive for relationships. | 0:42:13 | 0:42:17 | |
I wouldn't say I'm particularly | 0:42:17 | 0:42:19 | |
romantic or naive about these things, | 0:42:19 | 0:42:22 | |
but that's a bit of a body blow, I have to say, | 0:42:22 | 0:42:24 | |
-that I don't have a soulmate. -You don't! -OK. | 0:42:24 | 0:42:27 | |
But my assumption was that because they're getting such massive | 0:42:27 | 0:42:32 | |
quantities of data, the algorithms would do a better job than I would. | 0:42:32 | 0:42:35 | |
That they would be more sophisticated than a swiping app. | 0:42:35 | 0:42:38 | |
The truth is, there is no way that | 0:42:38 | 0:42:40 | |
these algorithms can do what they're claiming to do. | 0:42:40 | 0:42:44 | |
-Really?! -Yes. | 0:42:44 | 0:42:46 | |
They're claiming that they can set you up with somebody who is | 0:42:46 | 0:42:49 | |
more romantically compatible with you than some other person | 0:42:49 | 0:42:53 | |
chosen more and less at random. And, yes, the scientific community | 0:42:53 | 0:42:58 | |
who don't have a horse in the race, there's a pretty wide consensus | 0:42:58 | 0:43:01 | |
here is that none of these algorithms can succeed in that task. | 0:43:01 | 0:43:05 | |
If these online dating sites conducted one rigorous, | 0:43:05 | 0:43:09 | |
compelling study showing nothing but increased satisfaction | 0:43:09 | 0:43:13 | |
following a first date, I would already take back my words. | 0:43:13 | 0:43:17 | |
But having sifted through the psychological literature, Eli thinks | 0:43:22 | 0:43:26 | |
there's one area where algorithms can work. | 0:43:26 | 0:43:29 | |
People who are highly neurotic are in fact, on average, | 0:43:29 | 0:43:33 | |
not very good relationship partners. | 0:43:33 | 0:43:35 | |
They have way more conflict and they're much more difficult. | 0:43:35 | 0:43:38 | |
Do I think eHarmony any can figure out who's neurotic? Yes. | 0:43:38 | 0:43:41 | |
It's not a hard thing to do. | 0:43:41 | 0:43:43 | |
And the reason why I believe that eHarmony actually does assess | 0:43:43 | 0:43:47 | |
that stuff and use it in their algorithm | 0:43:47 | 0:43:49 | |
is they frequently tell people we don't have anybody for you. | 0:43:49 | 0:43:53 | |
And my guess is what they're saying is, | 0:43:53 | 0:43:56 | |
you're a lousy relationship partner | 0:43:56 | 0:43:59 | |
-and we're not going to take your money. -Wow! | 0:43:59 | 0:44:03 | |
Because we think you will pollute our pool. | 0:44:03 | 0:44:05 | |
So, even though dating sites can't match you with your soulmate, | 0:44:05 | 0:44:09 | |
at least they can sift out undesirables. But is that enough? | 0:44:09 | 0:44:13 | |
I often get presented as like a scold, | 0:44:13 | 0:44:16 | |
somebody who's taking the industry to task, | 0:44:16 | 0:44:18 | |
and I suppose that's fair enough, but if the question is, | 0:44:18 | 0:44:22 | |
is the overall wellbeing in the world better | 0:44:22 | 0:44:25 | |
because online dating exists? | 0:44:25 | 0:44:27 | |
-The answer is, without any qualification, yes. -Wow! OK. | 0:44:27 | 0:44:31 | |
-Thank you very much. -My pleasure. | 0:44:31 | 0:44:33 | |
You've got to keep you posted on how it goes. | 0:44:33 | 0:44:37 | |
So having spoken to Eli about this, I guess I feel quite conflicted. | 0:44:39 | 0:44:42 | |
On the one hand, he is sceptical about algorithms, | 0:44:42 | 0:44:44 | |
but on the other hand, he thinks that online dating - | 0:44:44 | 0:44:47 | |
and I guess dating in general - is a good thing, | 0:44:47 | 0:44:49 | |
that's how I'll get what I want. | 0:44:49 | 0:44:51 | |
So, now it's time for me to pick my date from the Horizon dating site. | 0:44:51 | 0:44:56 | |
Helen Fisher and Lucy Brown have told me I should be looking | 0:44:56 | 0:44:59 | |
for someone who's adventurous like me. | 0:44:59 | 0:45:02 | |
So, I made a shortlist, I'm hoping my written profile - | 0:45:02 | 0:45:06 | |
and writing that profile was a nightmare - | 0:45:06 | 0:45:08 | |
but I'm hoping it makes me sound funny AND courageous - not easy. | 0:45:08 | 0:45:12 | |
My profile picture I'm hoping looks fun and outgoing enough | 0:45:12 | 0:45:16 | |
for people to want to meet me. So, here goes. | 0:45:16 | 0:45:19 | |
But before Xand can find out who likes him, | 0:45:22 | 0:45:24 | |
I want to do an experiment with the rest | 0:45:24 | 0:45:26 | |
of Horizon's online dating guinea pigs. | 0:45:26 | 0:45:29 | |
Of the 200 people who signed up to my dating site, we've invited 50 | 0:45:29 | 0:45:34 | |
to help me test whether algorithms | 0:45:34 | 0:45:37 | |
are as ineffective as Eli Finkel believes. | 0:45:37 | 0:45:40 | |
MUSIC: Ooh La La by Goldfrapp | 0:45:40 | 0:45:43 | |
I guess when I arrived I thought I'd feel sorry for them, | 0:45:46 | 0:45:49 | |
like, "Oh, you poor old single losers!" | 0:45:49 | 0:45:51 | |
But because I'm one of them, I now look at them and go... | 0:45:51 | 0:45:53 | |
-You are a single loser! -I know! I know, | 0:45:53 | 0:45:55 | |
-and I really admire them for doing this. -Fortune favours the brave. | 0:45:55 | 0:45:59 | |
But first I want to determine how much of the success of online dating | 0:45:59 | 0:46:04 | |
comes down to actual matching | 0:46:04 | 0:46:06 | |
and how much is due to the power of suggestion - the placebo effect. | 0:46:06 | 0:46:12 | |
So, we'll run an experiment. | 0:46:12 | 0:46:14 | |
Four different groups, each of them slightly different. | 0:46:14 | 0:46:17 | |
Group A, over in that corner there, they are well matched | 0:46:17 | 0:46:22 | |
and we've told them that they're all well matched together. | 0:46:22 | 0:46:26 | |
These yellow wristband wearers are part of a group of people who, | 0:46:26 | 0:46:30 | |
according to the algorithm, | 0:46:30 | 0:46:32 | |
should match well to a number of different partners. | 0:46:32 | 0:46:35 | |
Group B, just behind me here, they are also very well matched, | 0:46:35 | 0:46:39 | |
but we've told them that they're a terrible match for each other. | 0:46:39 | 0:46:43 | |
It'll be interesting to see whether these pink wristband wearers | 0:46:43 | 0:46:46 | |
are more influenced by the algorithm or the power of suggestion. | 0:46:46 | 0:46:52 | |
We've also got the people who are actually badly matched. | 0:46:52 | 0:46:55 | |
So, groups C and D over here. | 0:46:55 | 0:46:58 | |
Of these badly matched daters, Group C, green, | 0:46:58 | 0:47:02 | |
were told that they were well matched. | 0:47:02 | 0:47:04 | |
But Group D, purple, were told the truth. | 0:47:04 | 0:47:08 | |
Maybe it's just that the perception of being well matched is enough | 0:47:08 | 0:47:11 | |
to trick people into thinking their dates were better than they were. | 0:47:11 | 0:47:15 | |
At this exact moment, having split them up into the different groups, | 0:47:15 | 0:47:18 | |
it doesn't look as though one group is having a better time than others. | 0:47:18 | 0:47:22 | |
After half an hour, everyone puts their wristbands | 0:47:23 | 0:47:26 | |
into a container according to how well they got on with their dates. | 0:47:26 | 0:47:30 | |
Statistically, if neither algorithm nor the power of suggestion | 0:47:30 | 0:47:34 | |
has an effect, we should find the wristbands equally distributed | 0:47:34 | 0:47:39 | |
between all three baskets. | 0:47:39 | 0:47:40 | |
So, first up in the sad basket - | 0:47:40 | 0:47:43 | |
the people who did not have a very good time - | 0:47:43 | 0:47:45 | |
what is interesting is that there are only pink and purple in here. | 0:47:45 | 0:47:50 | |
Pink and purple were the two groups that were told that they were | 0:47:50 | 0:47:54 | |
-not well matched with each other. -Power of suggestion. | 0:47:54 | 0:47:57 | |
Yeah, implying that people who were expecting to have a bad time | 0:47:57 | 0:48:00 | |
really did have a bad time. | 0:48:00 | 0:48:02 | |
Nobody who was told that they were well matched ended up | 0:48:02 | 0:48:04 | |
not having a good time. It's extraordinary. Suggestion works. | 0:48:04 | 0:48:08 | |
There's a hint there. OK. | 0:48:08 | 0:48:10 | |
But if you look at the basket where people had a really good time, | 0:48:10 | 0:48:14 | |
the biggest number of wristbands in here are the yellow wristbands, | 0:48:14 | 0:48:19 | |
which is where people were told they were going to have a good time, | 0:48:19 | 0:48:24 | |
but also, the algorithm said that they would be well matched. | 0:48:24 | 0:48:27 | |
-That's the highest number in here. -That's really good. | 0:48:27 | 0:48:30 | |
So, your algorithm did make people have a good time, | 0:48:30 | 0:48:33 | |
-even beyond what we told them. -Yeah, absolutely. | 0:48:33 | 0:48:36 | |
I think, generally, what this is saying is that both things | 0:48:36 | 0:48:39 | |
make a difference - | 0:48:39 | 0:48:40 | |
both what you tell people - this power of suggestion - | 0:48:40 | 0:48:42 | |
but also that the algorithm seems to have some effect. | 0:48:42 | 0:48:45 | |
I think it's really funny that you're surprised by this. | 0:48:45 | 0:48:48 | |
Well, yeah. We have to be scientists here, in that this is... | 0:48:48 | 0:48:53 | |
You do, I'm just looking for love! | 0:48:53 | 0:48:55 | |
SHE LAUGHS | 0:48:55 | 0:48:57 | |
As there were equal numbers of the two groups who were duped | 0:48:57 | 0:48:59 | |
- green and pink - | 0:48:59 | 0:49:01 | |
we'll have to call it a draw between algorithm and placebo. | 0:49:01 | 0:49:05 | |
Our little test mirrors the results of a much larger online experiment | 0:49:05 | 0:49:10 | |
by OkCupid. | 0:49:10 | 0:49:12 | |
'Now it's time to introduce our daters to their best matches...' | 0:49:13 | 0:49:17 | |
-Recovering-Cyclist... -With Miss... | 0:49:17 | 0:49:20 | |
'..to see if Hannah's algorithm can find love among our volunteers.' | 0:49:20 | 0:49:26 | |
-Adman91. -You're with Babe2. | 0:49:26 | 0:49:30 | |
'If successful, it should bode well for Xand's dates tomorrow.' | 0:49:30 | 0:49:35 | |
-Alien-Turned-Human. -You are with Knotted-Sheep. | 0:49:35 | 0:49:39 | |
Oh, gosh. You're already standing together! | 0:49:39 | 0:49:42 | |
What a surprise! | 0:49:42 | 0:49:45 | |
That's a good sign. | 0:49:45 | 0:49:47 | |
It's a fun way of approaching topology, isn't it? | 0:49:51 | 0:49:54 | |
Yeah, absolutely. | 0:49:54 | 0:49:55 | |
Do you feel like you wrote this algorithm and you are fiddling with their lives in quite a weird way? | 0:49:58 | 0:50:04 | |
In a way, it would be very cool if some people actually got together | 0:50:04 | 0:50:07 | |
this evening and we got to go to a wedding in a couple of years' time. | 0:50:07 | 0:50:10 | |
You would get to officiate that wedding. You'd be... | 0:50:10 | 0:50:14 | |
You'd be like the guest of honour. You'd be on top table, for sure. | 0:50:14 | 0:50:17 | |
I want a little statue of me on top of their cake. That's all I'm saying. | 0:50:17 | 0:50:20 | |
THEY LAUGH | 0:50:20 | 0:50:22 | |
But to make sure everyone got paired up, | 0:50:22 | 0:50:25 | |
not every single match was perfect. | 0:50:25 | 0:50:27 | |
Well, I had an interesting conversation with my match, | 0:50:27 | 0:50:30 | |
but there was no initial attraction there, no. | 0:50:30 | 0:50:33 | |
-I think he likes someone else. -Really? -So, yeah. | 0:50:33 | 0:50:36 | |
She was very lovely and we had quite a good conversation, | 0:50:36 | 0:50:39 | |
but I don't think we had a whole lot in common. | 0:50:39 | 0:50:42 | |
But most seemed quite happy with their match up. | 0:50:42 | 0:50:44 | |
She lives in Bristol, which is where I'm originally from. | 0:50:44 | 0:50:47 | |
I do go back to Bristol quite a bit. So, who knows? | 0:50:47 | 0:50:51 | |
He's quite funny and do you know what, if a guy makes me laugh, I'm putty in their hand. So, yeah. | 0:50:51 | 0:50:56 | |
We found out we actually had a lot in common. | 0:50:56 | 0:50:59 | |
And actually we're getting on really well right now. | 0:50:59 | 0:51:01 | |
So, I guess there might be something to this algorithm. | 0:51:01 | 0:51:04 | |
But what about the algorithm's very best-matched couple, at 85%? | 0:51:04 | 0:51:10 | |
-Have you found that you've got quite a lot in common, then? -Yes. -Yes. | 0:51:10 | 0:51:14 | |
It was not a surprise that we were matched up. We've just been talking the whole day. | 0:51:14 | 0:51:18 | |
-We started talking while we were still outside. -Do you think you'll stay in touch? | 0:51:18 | 0:51:21 | |
-Do you think you'll want to see each other again? -I think we'll stay in touch. -I would like to, yes. | 0:51:21 | 0:51:27 | |
I think from a small sample of people | 0:51:27 | 0:51:29 | |
over quite a short period of time, you did really well. | 0:51:29 | 0:51:32 | |
Some of them left arm in arm. | 0:51:32 | 0:51:34 | |
Yeah, yeah. | 0:51:35 | 0:51:36 | |
So, I think the algorithm will have picked out some ladies | 0:51:36 | 0:51:41 | |
for you tomorrow that you'll, at the very least, get on well with. | 0:51:41 | 0:51:45 | |
All right, we'll see. We'll see. | 0:51:45 | 0:51:47 | |
I'm looking forward to it much more now than I was before this started. | 0:51:47 | 0:51:53 | |
-I think that's a good place to start, at the very least. -OK. | 0:51:53 | 0:51:58 | |
Finally, I'm going to meet my dates. | 0:52:01 | 0:52:04 | |
-Very nice to meet you. -Nice to meet you. | 0:52:04 | 0:52:07 | |
The first girl I'm meeting is one I picked using just her photo | 0:52:07 | 0:52:10 | |
and profile information. | 0:52:10 | 0:52:13 | |
And since the whole challenge is riding on these dates, | 0:52:14 | 0:52:17 | |
I'm keeping an eye on proceedings. | 0:52:17 | 0:52:20 | |
-Are you a chemist by background, then? -I'm a chemist, yeah. | 0:52:20 | 0:52:23 | |
I did nanochemistry for my PhD. | 0:52:23 | 0:52:25 | |
I thought Cat was beautiful, | 0:52:25 | 0:52:26 | |
she's obviously very intelligent, which I really like. | 0:52:26 | 0:52:29 | |
Do you have strong opinions about national service? | 0:52:29 | 0:52:32 | |
I don't really have strong opinions on a lot of things. | 0:52:32 | 0:52:34 | |
She was really good fun. | 0:52:34 | 0:52:35 | |
Oh, she's Iranian. Great, I'll definitely bring that up. | 0:52:35 | 0:52:39 | |
That can be fed in somehow. | 0:52:39 | 0:52:40 | |
I think she quite fancies Xand. | 0:52:42 | 0:52:44 | |
Yeah, he's cute. | 0:52:44 | 0:52:46 | |
Yeah, I really enjoyed it. | 0:52:46 | 0:52:48 | |
I don't know if I'd go on a second date and I kind of think, | 0:52:50 | 0:52:53 | |
if I don't want to go on a second date with her, | 0:52:53 | 0:52:55 | |
then what am I doing? Who would I go on a second date with? | 0:52:55 | 0:52:57 | |
I discovered I didn't like New York at New Year. | 0:52:57 | 0:53:00 | |
-Nowhere's fun at New Year. -No. | 0:53:00 | 0:53:03 | |
So, Xand isn't as good at picking a partner as he thinks he is. | 0:53:07 | 0:53:11 | |
The next date was matched by the algorithm, according to | 0:53:11 | 0:53:14 | |
shared interests and opinions. | 0:53:14 | 0:53:16 | |
-Hello. -Very nice to meet you. How are you doing? -I'm good. Nice to meet you. -Thank you for coming. | 0:53:16 | 0:53:21 | |
But will she have that special something Xand is looking for? | 0:53:21 | 0:53:24 | |
Do you have, like, do you think you've got good at dating? | 0:53:24 | 0:53:28 | |
Erm...I don't know, I'm not sure. | 0:53:28 | 0:53:31 | |
-That's a really unfair question, I think you're good at dating! -Yeah, thanks. Yeah. | 0:53:31 | 0:53:35 | |
I liked her, I thought she was nice, I thought she was attractive. | 0:53:35 | 0:53:38 | |
You know, it's a bit like when you interview people for a job... | 0:53:38 | 0:53:41 | |
I didn't think the algorithm did a bad job... | 0:53:41 | 0:53:43 | |
I think dates are a little bit like that. You know straight away if you're going to like someone or not. | 0:53:43 | 0:53:48 | |
Ooh, there was locked eye contact and a smile right then! | 0:53:48 | 0:53:51 | |
He could probably chat the hind legs off a donkey, I'm pretty sure. | 0:53:56 | 0:54:00 | |
But, yeah, he seems like a nice, genuine guy. | 0:54:00 | 0:54:03 | |
I think subtle personality traits meant that there wasn't a spark, | 0:54:03 | 0:54:06 | |
but I don't know, is that the algorithm's fault? I suspect not. | 0:54:06 | 0:54:09 | |
I think, I guess, if I met 50 people like her, | 0:54:09 | 0:54:13 | |
one of them might be perfect. | 0:54:13 | 0:54:15 | |
-The format of a date... -Yeah. -..it is a terrible idea. | 0:54:15 | 0:54:18 | |
Yeah, yeah. It is. | 0:54:18 | 0:54:19 | |
Having watched both Xand's dates, | 0:54:19 | 0:54:22 | |
I don't think either of us have won the bet. | 0:54:22 | 0:54:25 | |
But there's one more date left. | 0:54:25 | 0:54:27 | |
How are you doing? Oh, really nice to meet you. | 0:54:30 | 0:54:33 | |
-Come in, this way. -Great. | 0:54:33 | 0:54:35 | |
This date appeared on both the list of good matches, | 0:54:35 | 0:54:39 | |
according to the algorithm and the list that we asked Xand to put | 0:54:39 | 0:54:43 | |
together himself of people he'd like to meet and date. | 0:54:43 | 0:54:46 | |
Because we both selected her, | 0:54:46 | 0:54:48 | |
neither of us can claim this as a win if this date goes well. | 0:54:48 | 0:54:53 | |
-Your username was Little Burp, wasn't it? -Yes. -Yeah. -That's right. | 0:54:53 | 0:54:56 | |
Why was it Little Burp? | 0:54:56 | 0:54:58 | |
Well, it's a bit silly really, I've got lots of bird tattoos, so | 0:54:58 | 0:55:01 | |
for a long time my friends have called me Little Bird, | 0:55:01 | 0:55:04 | |
which is a bit naff, so eventually that became Little Burp, | 0:55:04 | 0:55:06 | |
because it's funnier and more appropriate. | 0:55:06 | 0:55:09 | |
From behind, that basically could be my head! | 0:55:09 | 0:55:13 | |
She looks really similar to me. | 0:55:13 | 0:55:16 | |
Although, she's much cuter! | 0:55:16 | 0:55:18 | |
I feel fairly convinced that they both fancy each other. | 0:55:22 | 0:55:25 | |
I mean, Xand's very dishy. | 0:55:25 | 0:55:27 | |
I was really bored with my hometown | 0:55:32 | 0:55:35 | |
by the time I was about ten, I think. | 0:55:35 | 0:55:37 | |
I'm from Beccles, which is right on the... | 0:55:37 | 0:55:39 | |
Er, Beccles, just so you know, | 0:55:39 | 0:55:41 | |
is where my family are from, where my English family are from. | 0:55:41 | 0:55:44 | |
It's a tiny little town, it's where I'm spending Christmas! | 0:55:44 | 0:55:47 | |
I've lived in London for 13 years this week. | 0:55:47 | 0:55:50 | |
-Really? You have, like, a London anniversary. -I do, 17th September. | 0:55:50 | 0:55:53 | |
I've lived in London for 13 years this week! | 0:55:53 | 0:55:56 | |
-I deliberately didn't spend lots of time thinking about what you might be like. -OK. | 0:55:56 | 0:56:00 | |
I had to make the choice, so maybe I'm a bit more... | 0:56:00 | 0:56:03 | |
Maybe I'm a bit more invested. | 0:56:03 | 0:56:04 | |
-Oh, bless you! -HE LAUGHS | 0:56:04 | 0:56:06 | |
I think the date went pretty well. | 0:56:06 | 0:56:09 | |
As soon as she arrived, I just thought she looked really great. | 0:56:09 | 0:56:12 | |
Just everything about her was really nice. | 0:56:12 | 0:56:15 | |
She has a great smile, she was really... | 0:56:15 | 0:56:17 | |
She was just someone I quite fancied. | 0:56:17 | 0:56:20 | |
He's a very, sort of, attractive character. He's very articulate. | 0:56:20 | 0:56:26 | |
I think the more you like someone, | 0:56:26 | 0:56:28 | |
the harder it is to tell what they think of you. | 0:56:28 | 0:56:32 | |
So, yeah, maybe there is something in the algorithm. | 0:56:32 | 0:56:35 | |
Are you texting someone there, Xand? | 0:56:40 | 0:56:42 | |
SHE LAUGHS | 0:56:43 | 0:56:45 | |
So, it went well, then? | 0:56:45 | 0:56:47 | |
Yes. So, my date with Cindy was great, | 0:56:49 | 0:56:52 | |
but I still have the nervousness of going, "Did she like me?" | 0:56:52 | 0:56:55 | |
So, she hasn't responded to my text message saying, | 0:56:55 | 0:56:57 | |
would she like to go for a drink? | 0:56:57 | 0:56:59 | |
You sent it about three minutes ago! | 0:56:59 | 0:57:01 | |
Well, no, but... I might check it again! | 0:57:01 | 0:57:04 | |
No, still nothing. | 0:57:05 | 0:57:07 | |
-Mate, that's still three-and-a-half minutes later! -Yeah. | 0:57:07 | 0:57:10 | |
Very seriously, from watching it, | 0:57:10 | 0:57:13 | |
it was like a completely different date. | 0:57:13 | 0:57:16 | |
So, I think the algorithm does well, | 0:57:16 | 0:57:20 | |
but I also think what it can't do is tell you about that spark. | 0:57:20 | 0:57:25 | |
There's something extra, which you just can't define or capture, | 0:57:26 | 0:57:30 | |
and you only know it when it's put in front of you. | 0:57:30 | 0:57:33 | |
But I think that's still massively impressive. | 0:57:33 | 0:57:37 | |
It's so hard to meet people - my life is so busy, | 0:57:37 | 0:57:41 | |
my friends are so married. | 0:57:41 | 0:57:43 | |
Prior to doing this, I'd never written a profile | 0:57:43 | 0:57:46 | |
and I had never used an algorithm-driven site, | 0:57:46 | 0:57:49 | |
I'd just used a swiping app, | 0:57:49 | 0:57:51 | |
and I wouldn't bother with that any more. | 0:57:51 | 0:57:54 | |
I think online dating is just an introductory service. | 0:57:54 | 0:57:57 | |
So, it is just a numbers game. | 0:57:57 | 0:57:58 | |
I wouldn't say it's JUST a numbers game, I think it's, like, | 0:57:58 | 0:58:01 | |
the most important numbers game you can possibly play! | 0:58:01 | 0:58:04 | |
I'm still rolling the dice, right? I'm like the last guy in the casino | 0:58:04 | 0:58:07 | |
when they're trying to turn off the lights. | 0:58:07 | 0:58:10 | |
I guess what I mean is, I think the internet dating websites | 0:58:10 | 0:58:15 | |
and their algorithms do do something, | 0:58:15 | 0:58:19 | |
but I think, ultimately, | 0:58:19 | 0:58:20 | |
it doesn't guarantee that every date will be good, | 0:58:20 | 0:58:23 | |
but it gives you a good solid basis on which to build. | 0:58:23 | 0:58:27 |