0:00:10 > 0:00:12Internet dating is big business.
0:00:12 > 0:00:15It's worth over 2 billion per year
0:00:15 > 0:00:19and claims to generate one fifth of all current committed relationships.
0:00:19 > 0:00:25Worldwide, 91 million people log on to dating sites and I'm one of them.
0:00:25 > 0:00:28Since I started dating, it has changed a huge amount.
0:00:28 > 0:00:32Really, now, almost everyone I know has tried online dating.
0:00:33 > 0:00:36I've been dating in both London and New York
0:00:36 > 0:00:38and so far I've yet to find The One.
0:00:40 > 0:00:44I'm 37, all my friends are married, my brothers are married,
0:00:44 > 0:00:46it's not fun being single any more.
0:00:46 > 0:00:51Although I'm happily married now, I've done my share of online dating.
0:00:51 > 0:00:55As a mathematician, I'm fascinated by the algorithms that dating sites
0:00:55 > 0:00:57claim can find you love,
0:00:57 > 0:01:00but there's little hard evidence that they actually deliver.
0:01:00 > 0:01:05So, I'm going to put them to the test using Xand as my guinea pig.
0:01:05 > 0:01:09I'm willing to gamble with Xand's heart and see if we can use
0:01:09 > 0:01:13a little bit of maths to find him a girl that he really likes.
0:01:13 > 0:01:16But can applying some science really help me find love?
0:01:16 > 0:01:19- Hiya, how are you doing?- Oh, really nice to meet you.
0:01:19 > 0:01:23Are matching sites any better than just choosing yourself?
0:01:23 > 0:01:26There is no way that these algorithms can do what
0:01:26 > 0:01:28they're claiming to do.
0:01:28 > 0:01:30Which picture should you use?
0:01:30 > 0:01:32God, you're like the bloomin' hair police.
0:01:32 > 0:01:35And what's the best way to write a profile?
0:01:35 > 0:01:39Just being a nice guy is not necessarily the best pitch.
0:01:39 > 0:01:43We look at the science of online dating and have some fun along the way.
0:01:43 > 0:01:46You're going right there. SHE LAUGHS
0:01:46 > 0:01:48That's where your genitals lit up.
0:01:53 > 0:01:56MUSIC: Ooh La La by Goldfrapp
0:02:00 > 0:02:04Horizon has invited 50 single ladies and gentlemen
0:02:04 > 0:02:06to a dating event in London.
0:02:06 > 0:02:10- No-one's snogging, but...- No. - So far.
0:02:10 > 0:02:12- It's early yet.- Early days. It's early days.
0:02:12 > 0:02:15They haven't had enough to drink yet.
0:02:15 > 0:02:18We are all taking part in an experiment to test the
0:02:18 > 0:02:22mathematical matching systems used by many online dating sites.
0:02:23 > 0:02:27There is that sort of, almost placebo effect of expectation.
0:02:27 > 0:02:32Whether that does better or not then our actual extended algorithm,
0:02:32 > 0:02:34we're about to find out.
0:02:34 > 0:02:37The recent upsurge in online dating is a gold mine for researchers
0:02:37 > 0:02:39studying human behaviour
0:02:39 > 0:02:42and it's starting to produce some good, hard science
0:02:42 > 0:02:46about the best techniques to help those like Xand looking for love.
0:02:46 > 0:02:49But wait till she stands up, because she's super smoking.
0:02:53 > 0:02:56I hate to admit it, but I really need some help.
0:03:01 > 0:03:04So, I think the worst thing about online dating is having
0:03:04 > 0:03:07to admit to yourself that you're single
0:03:07 > 0:03:11and that you want to meet someone else. And at 37, I don't feel old,
0:03:11 > 0:03:14but I'm probably in a bit more of a mess than I used to be.
0:03:15 > 0:03:19I've been to eight weddings in the last two years and I feel like
0:03:19 > 0:03:24always the bridesmaid, never the bride does almost literally apply to me.
0:03:24 > 0:03:27I think I am getting a little grumpy at weddings now. I think
0:03:27 > 0:03:29I slightly do resent...
0:03:31 > 0:03:35..other people's happiness, which is not...
0:03:35 > 0:03:38It's not a good position to be in.
0:03:38 > 0:03:41First couple of divorces, though, so that made me feel better.
0:03:47 > 0:03:50I found online dating a minefield.
0:03:50 > 0:03:52There are thousands of different sites, from mobile apps
0:03:52 > 0:03:54that hook you up with a simple swipe,
0:03:54 > 0:03:57to internet dating with complex matching systems
0:03:57 > 0:04:00that promise to find you the perfect partner.
0:04:00 > 0:04:02But which is better?
0:04:02 > 0:04:07I get that online dating is an efficient way of encountering other people...
0:04:07 > 0:04:09- Yeah.- ..and probably, therefore, getting me dates,
0:04:09 > 0:04:12but it makes a much bigger claim than that.
0:04:12 > 0:04:14- They're saying, "We'll find you someone right for you."- Mm.
0:04:14 > 0:04:18Well, there's certainly a range of different websites that offer different things.
0:04:18 > 0:04:21So, some of them are just effectively a catalogue of strangers, right?
0:04:21 > 0:04:24Whereas others have these algorithms built in,
0:04:24 > 0:04:26which is a series of calculations.
0:04:26 > 0:04:30So, you take some input - maybe what you're looking for in a partner,
0:04:30 > 0:04:34what prospective partners are looking for in their partner -
0:04:34 > 0:04:38and you put it through a series of logical steps, like a recipe effectively,
0:04:38 > 0:04:41and in the end you come up with an output, which is how good
0:04:41 > 0:04:44the two of you would be matched as a potential couple.
0:04:44 > 0:04:47- So, it's like a decision tree? - Yeah, exactly.
0:04:47 > 0:04:50MUSIC: Escape (The Pina Colada Song) By Rupert Holmes
0:04:51 > 0:04:55At their simplest, algorithms work like a flow chart,
0:04:55 > 0:05:00with different inputs or instructions that feed into an end result or output.
0:05:00 > 0:05:04OK, but I've only ever used the simplest algorithm,
0:05:04 > 0:05:07- which is proximity, age, sex.- Yeah.
0:05:07 > 0:05:12But I think that if we get you to fill in a questionnaire about
0:05:12 > 0:05:15the type of things that you find appealing in a partner,
0:05:15 > 0:05:18I think I could write an algorithm that would find a girl
0:05:18 > 0:05:23who is better suited for you than if you just walked into a bar and picked someone at random.
0:05:23 > 0:05:27I'm pretty sceptical about this, but, hey, let's give it a go.
0:05:27 > 0:05:32- And this is actually applied maths. - Yeah.- Like, we'll use it to get me a date.- Yeah, totally.
0:05:32 > 0:05:36All right, but the challenge is not for you to do better than me going to a bar,
0:05:36 > 0:05:39you're actually up against me choosing random people through swiping.
0:05:39 > 0:05:42- That's the challenge.- OK. - You're on.- Deal.
0:05:49 > 0:05:52With mobile dating apps like Tinder, Zoosk and Happn
0:05:52 > 0:05:55allowing users to select or reject partners with a simple
0:05:55 > 0:06:00swipe left or right, online daters like me can feel a little jaded.
0:06:00 > 0:06:03It sometimes feels really superficial...
0:06:03 > 0:06:06It's very easy for people to just reject you outright.
0:06:06 > 0:06:10So, you think, "Oh, why are they rejecting me? What's wrong with me?"
0:06:10 > 0:06:14And traditional dating sites have their downsides, too.
0:06:14 > 0:06:18You get a lot of creeps online who try to send you, like,
0:06:18 > 0:06:21gross pictures of themselves.
0:06:21 > 0:06:26The catfish. Someone who's pretending to be somebody else.
0:06:26 > 0:06:30You're never quite sure who's telling lies or not.
0:06:30 > 0:06:33Let's face it - online, anybody can be anything they want.
0:06:36 > 0:06:40In order to find Xand a date, I'm going to build an experimental
0:06:40 > 0:06:43dating website with the help of my colleague Tom Russell.
0:06:44 > 0:06:47This is one user's set of responses.
0:06:47 > 0:06:51Some commercial dating sites use multiple layers of algorithms.
0:06:51 > 0:06:55eHarmony claims they assess psychological compatibility
0:06:55 > 0:06:57and interpersonal chemistry.
0:06:57 > 0:07:01Lovestruck uses a recommendation engine based on search activity,
0:07:01 > 0:07:04a bit like Netflix or Amazon.
0:07:04 > 0:07:08Show me the bit where the scores for each question goes.
0:07:08 > 0:07:12We're using a scored questionnaire that is similar to OkCupid.
0:07:12 > 0:07:14So, if we have three levels, then...
0:07:14 > 0:07:18Matching algorithms are useful because they help daters sort through
0:07:18 > 0:07:23the vast numbers of potential partners available via online dating.
0:07:26 > 0:07:31One of the problems with online dating is the paradox of choice.
0:07:31 > 0:07:33It felt slightly overwhelming.
0:07:33 > 0:07:35Surprised at the number of people who were there.
0:07:35 > 0:07:41You can sit there for hours ploughing through people from all over the country.
0:07:41 > 0:07:43It becomes like fishing, I guess.
0:07:43 > 0:07:45I find it's, like, almost like a drudgery.
0:07:45 > 0:07:49The commitment to time, is exhausting, it's mentally exhausting.
0:07:51 > 0:07:54Xand is convinced that he can choose himself a better date
0:07:54 > 0:07:57than my algorithm, but with thousands of potential dates
0:07:57 > 0:08:00in New York and London to choose from,
0:08:00 > 0:08:03I think he needs some mathematical help.
0:08:03 > 0:08:07So, what you really need is an effective search strategy to help
0:08:07 > 0:08:11you find the perfect woman for you, without having to date
0:08:11 > 0:08:14- every single one of them. - OK.- I've got one.
0:08:14 > 0:08:16Optimal stopping theory, it's called.
0:08:16 > 0:08:18That is not what I thought you were going to say. OK.
0:08:18 > 0:08:23So, it was invented in 1875 by a chap called Arthur Cayley,
0:08:23 > 0:08:25essentially to gamble better,
0:08:25 > 0:08:29and two Harvard mathematicians worked out the best chance you can
0:08:29 > 0:08:33give yourself of stopping on The One, the perfect woman for you,
0:08:33 > 0:08:40is to spend the first 37% of your dates just, kind of, not taking them too seriously,
0:08:40 > 0:08:43having a nice time, getting a bit of a feel for the marketplace and so on.
0:08:43 > 0:08:46And then after that 37% period has passed,
0:08:46 > 0:08:50you should then pick the next woman to come along that is better than
0:08:50 > 0:08:53everybody that you've seen before.
0:08:53 > 0:08:55And if you do that, you're maximising your chances,
0:08:55 > 0:08:59mathematically, of finding the perfect woman for you.
0:08:59 > 0:09:03And what will the chances be of the one after 37%,
0:09:03 > 0:09:06that one being the right woman for me?
0:09:06 > 0:09:09Well, OK. So, if you pick somebody completely at random
0:09:09 > 0:09:12in your list of 100 and just chose that person to go on your date with,
0:09:12 > 0:09:14your chance of getting the best person in your list
0:09:14 > 0:09:17would be 1%, right? One in 100.
0:09:17 > 0:09:22But this technique - just having that little rejection phase of 37% at the beginning -
0:09:22 > 0:09:27means that you increase your chances all the way from 1% to 37%.
0:09:27 > 0:09:31If the number of potential dates, n, for Xand is 100,
0:09:31 > 0:09:35his chance of success, P, is highest when he rejects
0:09:35 > 0:09:3837% of potential partners.
0:09:38 > 0:09:42His success rate drops off if he either reduces
0:09:42 > 0:09:46or increases his rejection phase, r,
0:09:46 > 0:09:49the time before he starts thinking seriously about a match.
0:09:49 > 0:09:53OK, that is an amazing bit of maths. That is extraordinary.
0:09:53 > 0:10:00So, imagine you decide to take 100 people,
0:10:00 > 0:10:03reject the first 37 of them
0:10:03 > 0:10:06and then pick the next person who comes along that's better than
0:10:06 > 0:10:10everyone you've seen before and take that person on a date.
0:10:10 > 0:10:12Wow!
0:10:12 > 0:10:15- OK, so 100 people seems reasonable. - Yeah, it's not crazy.
0:10:15 > 0:10:18- Yeah, I can entertain 100 people. - Of course.- OK, so I just start...
0:10:18 > 0:10:20Two, three, four...
0:10:20 > 0:10:23Are there some of these that you would swipe right to?
0:10:23 > 0:10:26This person, I would definitely swipe right for.
0:10:26 > 0:10:29She looks lovely and according to you, I have to reject her,
0:10:29 > 0:10:30because you told me to.
0:10:30 > 0:10:33- So, like, this person seems nice. Nope, get rid of them.- Yeah.
0:10:33 > 0:10:35So, you carry on swiping left for the entire time
0:10:35 > 0:10:38and then you end up, well, probably dying alone...
0:10:38 > 0:10:39SHE LAUGHS
0:10:39 > 0:10:43..nursing a deep hatred of mathematical formulas!
0:10:43 > 0:10:45- And mathematicians!- Yeah, probably.
0:10:45 > 0:10:48You and the two guys at Harvard, primarily.
0:10:54 > 0:10:57Back at home, I test Hannah's optimal stopping theory
0:10:57 > 0:10:59on a commercial dating app.
0:10:59 > 0:11:03I'm rejecting 37 potential dates.
0:11:03 > 0:11:05And now the first person I see
0:11:05 > 0:11:09who's better than everyone I've just rejected...
0:11:09 > 0:11:10is Miss Right.
0:11:13 > 0:11:17So, at 62, I decided to swipe right
0:11:17 > 0:11:20and I think that this person was better than all the others.
0:11:20 > 0:11:23I will send her a message and see if we can go on a date.
0:11:26 > 0:11:30Well, I'm delighted she said yes and she's drop-dead gorgeous.
0:11:30 > 0:11:32Do it again!
0:11:41 > 0:11:43She's even volunteered to film the date
0:11:43 > 0:11:46and tell me about her online dating experiences.
0:11:55 > 0:11:57Surely, eHarmony's loss!
0:11:57 > 0:12:00But as the date wore on, I wasn't convinced we were compatible.
0:12:00 > 0:12:03It can be edited.
0:12:10 > 0:12:15I started to wonder whether Hannah's optimal stopping theory had worked in this case.
0:12:15 > 0:12:17I sincerely apologise for meeting Xand.
0:12:22 > 0:12:25Well, I'm heading into work after my date with my supposed
0:12:25 > 0:12:29Miss Right yesterday and it didn't work out.
0:12:29 > 0:12:32So, back to the drawing board.
0:12:40 > 0:12:43I guess choosing a date based purely on appearances is always
0:12:43 > 0:12:45going to be a gamble.
0:12:45 > 0:12:48However, all dating apps and websites do require a photo,
0:12:48 > 0:12:52so it's clear that looks are important to everyone.
0:12:52 > 0:12:54It's all about first impressions.
0:12:54 > 0:12:57The picture engages you, then you read the profile.
0:12:57 > 0:12:59I mean, let's be honest, it all boils down to the photos,
0:12:59 > 0:13:01at the end of the day.
0:13:01 > 0:13:04But it's not just attractiveness we're judged on.
0:13:04 > 0:13:07Researchers at Princeton University have recently proved that
0:13:07 > 0:13:12people use faces to make split-second judgements about our personalities, as well.
0:13:13 > 0:13:16I think you can tell a lot about a person from the way they look.
0:13:16 > 0:13:21It's really easy to make snap judgements about people based on their photo.
0:13:21 > 0:13:25I think you can tell kindness, you can tell if someone's got a sense of fun.
0:13:25 > 0:13:29I'd like to think that I can read intelligence in somebody's face,
0:13:29 > 0:13:31maybe even the sense of humour that they have.
0:13:33 > 0:13:35And while these judgements might not be right,
0:13:35 > 0:13:39scientists have found that people tend to agree on what features
0:13:39 > 0:13:42make someone appear likeable, trustworthy or competent.
0:13:42 > 0:13:44And just put your chin down slightly.
0:13:44 > 0:13:48I want to find out what people think of me.
0:13:48 > 0:13:51So, I'm sending my picture to Dr Chris Olivola.
0:13:51 > 0:13:55He's analysed hundreds of real online daters' reactions to profile
0:13:55 > 0:13:59pictures and has discovered what facial attributes are most popular.
0:14:02 > 0:14:05So, at least one of the websites I used is entirely based on
0:14:05 > 0:14:08- swiping on pictures of people. - Yes, I know what that site is.
0:14:08 > 0:14:13- Yeah, so in that case, photos seem to be totally essential.- Yes.
0:14:13 > 0:14:16So, for women searching for men, they do care about attractiveness,
0:14:16 > 0:14:18physical attractiveness,
0:14:18 > 0:14:21but they also care about how fun and outgoing you are.
0:14:21 > 0:14:23How warm and approachable you are.
0:14:23 > 0:14:28So, if your goal is to try and get as many women interested in you as possible,
0:14:28 > 0:14:31then looking more fun and outgoing is going to boost your chances
0:14:31 > 0:14:34separately from looking more physically attractive.
0:14:34 > 0:14:36OK.
0:14:36 > 0:14:40To see if my face is generally perceived as fun and outgoing,
0:14:40 > 0:14:44Chris has mapped my photo onto a 3-D model of a generic head.
0:14:45 > 0:14:49- And, there we go.- Oh! - It doesn't do hair, so...
0:14:49 > 0:14:52Looking at me there, I think I don't look competent,
0:14:52 > 0:14:54I don't think I look particularly trustworthy
0:14:54 > 0:14:57and I certainly don't think I look likeable.
0:14:57 > 0:15:01With no hair and the computer's identification mark stamped on my forehead,
0:15:01 > 0:15:04I think I look more like a cage fighter than a potential lover.
0:15:04 > 0:15:06But what I think is irrelevant.
0:15:07 > 0:15:11The computer program engineered by Chris's colleague Alex Todorov
0:15:11 > 0:15:14combines the collective opinions of hundreds of people comparing
0:15:14 > 0:15:17thousands of different faces.
0:15:17 > 0:15:20- The model tells us your face looks likeable.- OK.
0:15:20 > 0:15:23- You do also look trustworthy.- Oh!
0:15:23 > 0:15:27In terms of competence, you have a fairly competent-looking face.
0:15:27 > 0:15:29- Oh, wow! OK. Great.- Yes.
0:15:29 > 0:15:32What about the other things, then?
0:15:32 > 0:15:35Fairly extroverted and quite dominant at the same time.
0:15:35 > 0:15:38So, I think you have a face that's good for dating and job interviews,
0:15:38 > 0:15:41which is great. I think most people, usually, it's one or the other.
0:15:41 > 0:15:44It's very odd seeing this, because what I'm forgetting
0:15:44 > 0:15:46is that these are not my character traits.
0:15:46 > 0:15:49- You're not telling me about my personality.- No.
0:15:49 > 0:15:55You're simply telling me what a bunch of people would say
0:15:55 > 0:15:58about my character traits glimpsing my face.
0:15:58 > 0:16:00Yes, our faces say a lot.
0:16:00 > 0:16:02And Chris has a way of showing me
0:16:02 > 0:16:04how to look more likeable and trustworthy.
0:16:04 > 0:16:08- Again, this can change my face. - Yes.- Do it, do it.
0:16:08 > 0:16:12- OK, so which one do you want first? - Make me more likeable.
0:16:12 > 0:16:15- So, if I ramp up your likeability... - I get thinner!
0:16:15 > 0:16:18- And you're smiling more.- Yeah, OK.
0:16:18 > 0:16:21So smiling is a simple and easy tip.
0:16:21 > 0:16:24- So, my eyebrows are a little further apart...- Yes.
0:16:24 > 0:16:27- ..and I'm slightly more smiley.- Yes.
0:16:27 > 0:16:31And what about trustworthiness? If we increased that?
0:16:31 > 0:16:33Dial it up.
0:16:33 > 0:16:36See, that would be hard to do without plastic surgery.
0:16:38 > 0:16:41The BBC are refusing to pay for plastic surgery,
0:16:41 > 0:16:45so the only alternative is for me to try and take a more fun,
0:16:45 > 0:16:48outgoing profile picture to boost my online appeal.
0:16:50 > 0:16:54I have to say, I'm cringing right now, but if this is what it takes,
0:16:54 > 0:16:56I guess I'll give it a go.
0:16:57 > 0:17:00Someone once told me you have to cough out a laugh, so...
0:17:00 > 0:17:01HE COUGHS
0:17:05 > 0:17:10Yes, Xand. Simply smiling can help you look more fun and outgoing,
0:17:10 > 0:17:15but choosing your own profile picture can be counterintuitive.
0:17:15 > 0:17:19When you look through online dating websites' data,
0:17:19 > 0:17:23it says that actually being different is the thing that counts.
0:17:23 > 0:17:27Dividing opinion is much better than just having everybody think
0:17:27 > 0:17:30that you're generically attractive.
0:17:30 > 0:17:33But the trouble is, when it comes to being objective about yourself,
0:17:33 > 0:17:35it's easier said than done.
0:17:37 > 0:17:42I've asked photographer Scott Chasserot to demonstrate this.
0:17:42 > 0:17:45Scott's going to take me through the process, which includes
0:17:45 > 0:17:50having my portrait taken with no make-up or accessories,
0:17:50 > 0:17:53which I'm not going to lie, I feel quite nervous about,
0:17:53 > 0:17:58but never let your vanity get in the way of doing a good job!
0:17:58 > 0:18:01So, here goes.
0:18:01 > 0:18:04My face has to be completely clear of both make-up...
0:18:04 > 0:18:06# Girls on film... #
0:18:06 > 0:18:08..and hair.
0:18:08 > 0:18:09# ..Girls on film... #
0:18:09 > 0:18:11- These bits?- Yeah.- God, you're like the blooming hair police.
0:18:11 > 0:18:13# ..Girls on film... #
0:18:13 > 0:18:15It's quite important to keep a straight neck.
0:18:15 > 0:18:17# ..Girls on film. #
0:18:19 > 0:18:22Scott's going to manipulate my picture and show me
0:18:22 > 0:18:26lots of different versions to compare what I think I think
0:18:26 > 0:18:30is the most attractive, with my brain's reaction before I've
0:18:30 > 0:18:33had time to consciously think about it.
0:18:33 > 0:18:37An EEG monitor will measure electrical activity
0:18:37 > 0:18:40in my cerebral cortex as I see each image.
0:18:40 > 0:18:43But this consumer headset isn't foolproof
0:18:43 > 0:18:47because facial expressions will give a false reading.
0:18:47 > 0:18:50I mean, you can try it, if you smile... Look at that!
0:18:50 > 0:18:51SHE LAUGHS
0:18:51 > 0:18:53Yeah. Any movement, I can see it.
0:18:53 > 0:18:55So, it would be very hard to separate that,
0:18:55 > 0:18:58- tease that apart from what's actually going on in the brain. - Mm-hm.
0:18:58 > 0:19:02So, this fun test requires my best poker face.
0:19:05 > 0:19:07It's so weird!
0:19:09 > 0:19:13But Scott's playing dirty, because as well as the original image,
0:19:13 > 0:19:16he's shuffled in five versions of me that have been modified
0:19:16 > 0:19:20according to theories about femininity, facial symmetry
0:19:20 > 0:19:22and skin tone,
0:19:22 > 0:19:25and five less attractive versions of me.
0:19:25 > 0:19:28There are some that are really horrible.
0:19:30 > 0:19:31By the end of the test,
0:19:31 > 0:19:35I'm pretty confident about which version of myself I like the best.
0:19:38 > 0:19:41I wouldn't mind being her!
0:19:43 > 0:19:46But it's not until we get the results of the EEG back
0:19:46 > 0:19:49from Scott's colleague in New York University
0:19:49 > 0:19:53that we can see what my pre-conscious brain found
0:19:53 > 0:19:54the most striking.
0:19:54 > 0:19:58The results have shown that you've had a strongest reaction
0:19:58 > 0:20:02to the sixth of those 11 images. So, that's one towards...
0:20:02 > 0:20:04- Beauty.- To beauty, yeah.
0:20:04 > 0:20:08- And can it see what image this one is, though?- Yeah. So...
0:20:08 > 0:20:11That is not the one I was expecting you to show.
0:20:11 > 0:20:15- I don't even really like that picture.- Right.
0:20:15 > 0:20:18See, I think that looks like I'm on a two-week holiday in Magaluf
0:20:18 > 0:20:21and have spent a bit too much money on fake tan.
0:20:21 > 0:20:23Which one were you expecting to see?
0:20:23 > 0:20:27I thought it would be the one where you'd done...
0:20:27 > 0:20:29you'd changed everything.
0:20:29 > 0:20:33Where I had still quite dark eyes, but I had a smaller jaw,
0:20:33 > 0:20:35thinner face, thinner nose,
0:20:35 > 0:20:38you'd pinned my ears back, you'd made my neck longer.
0:20:38 > 0:20:39Yeah. Yeah, that was the one.
0:20:39 > 0:20:42That was certainly the one that I picked out as my favourite.
0:20:42 > 0:20:46Right, your verbal choice was that one, yeah.
0:20:46 > 0:20:48I consciously preferred the picture
0:20:48 > 0:20:50that has been made much more feminine,
0:20:50 > 0:20:54but my pre-conscious brain paid more attention to the image where only my
0:20:54 > 0:20:57skin tone had changed.
0:20:57 > 0:21:01A scientific study has shown that this carotenoid skin tone
0:21:01 > 0:21:04is considered more attractive than pale skin,
0:21:04 > 0:21:09yet my rational brain discarded this image. This shows why it can be
0:21:09 > 0:21:14difficult to pick the best picture to represent ourselves online.
0:21:14 > 0:21:17And I think the real lesson there is that when it comes to choosing
0:21:17 > 0:21:18an online dating profile picture,
0:21:18 > 0:21:21you should really get your friends to help you.
0:21:24 > 0:21:28If my new picture is working, I should be more attractive to women.
0:21:28 > 0:21:31But I don't want to spend even more time than I already do
0:21:31 > 0:21:34swiping through potential dates.
0:21:34 > 0:21:38Vancouver-based software engineer Justin Long came up with
0:21:38 > 0:21:41a hi-tech solution to the problem of time-consuming searching.
0:21:41 > 0:21:45I created an application that helps you automate everything on Tinder.
0:21:46 > 0:21:50Using a computer program, or bot, to meet girls just sounds
0:21:50 > 0:21:51a little dubious.
0:21:51 > 0:21:54So, I've arranged an online chat with Justin.
0:21:55 > 0:21:57I realised that after using Tinder for a while,
0:21:57 > 0:21:59it became a situation where, you know,
0:21:59 > 0:22:03I was using a lot of my time to swipe left and right
0:22:03 > 0:22:05and it would be up to an hour or more a day...
0:22:05 > 0:22:08And that's what I found I was doing. I think an hour a day
0:22:08 > 0:22:11- is almost a conservative estimate. - Absolutely.
0:22:11 > 0:22:12And the same with my friends.
0:22:12 > 0:22:15If we were all out at a bar, or we were out at dinner,
0:22:15 > 0:22:19everyone would be literally swiping left or right on their phones
0:22:19 > 0:22:22and I figured, well, why not build a bot that actually automates this?
0:22:22 > 0:22:24So, how does the bot work?
0:22:24 > 0:22:28It looks at the facial structure of the person
0:22:28 > 0:22:31and it's building a computer model behind the scenes of what
0:22:31 > 0:22:35those people look like and it compares that facial structure
0:22:35 > 0:22:37to the differences between other facial structures.
0:22:37 > 0:22:41Because when you're swiping left and right, you're actually telling it
0:22:41 > 0:22:43this is who I find attractive
0:22:43 > 0:22:45and this is who I don't find attractive.
0:22:45 > 0:22:48So, I've been using this bot that you built and now it knows what I like,
0:22:48 > 0:22:52- it can make those decisions for me and I don't need to be involved any more.- Yes, that's right.
0:22:52 > 0:22:53So, what's the next step?
0:22:53 > 0:22:56This is actually where the bot gets more interesting.
0:22:56 > 0:22:58And it actually saves you more time.
0:22:58 > 0:23:02What you can do is you can customise the bot where you type in
0:23:02 > 0:23:05your own messages to introduce yourself
0:23:05 > 0:23:10and if they keep responding positively to your introductory messages,
0:23:10 > 0:23:13you will then get a notification on your computer saying,
0:23:13 > 0:23:16hey, this person's interested, you need to talk to them.
0:23:16 > 0:23:20It's funny, I have this vague discomfort with the machine doing it all.
0:23:20 > 0:23:23Did the people that you were talking to know that it was a bot?
0:23:23 > 0:23:27No-one ever figured it out because even though you're having a bot
0:23:27 > 0:23:29setting up the introduction,
0:23:29 > 0:23:31you've still written the introduction yourself.
0:23:31 > 0:23:32So, it's still you.
0:23:32 > 0:23:35OK. All right. Look, thanks very much indeed, Justin.
0:23:35 > 0:23:37- Not a problem.- Take care, bye.
0:23:42 > 0:23:45I'm not sure getting a machine to choose me a date on the basis
0:23:45 > 0:23:49of looks alone is going to be any more successful than my last date.
0:23:49 > 0:23:52I'm about to go on my first Tinder bot date
0:23:52 > 0:23:55and I don't know if it was more efficient than organising it myself,
0:23:55 > 0:23:57but maybe it'll be a better date.
0:23:57 > 0:23:59Maybe she'll just think I'm weirdo for using a robot.
0:23:59 > 0:24:02Did you know you were talking to a computer?
0:24:02 > 0:24:04Did that even cross your mind?
0:24:08 > 0:24:10HE LAUGHS
0:24:15 > 0:24:19- That is exactly what I was doing. - Yeah.- That's not cool, is it?
0:24:19 > 0:24:21No-one wants to feel like you're one of hundreds.
0:24:24 > 0:24:28'So, Tinder bot makes me look like a player and while I enjoyed the date,
0:24:28 > 0:24:32'she thought I was a bit odd and we didn't click. Again.'
0:24:32 > 0:24:37So far, my dates chosen randomly by looks alone haven't worked out.
0:24:37 > 0:24:39So, I'm dumping the swipe apps
0:24:39 > 0:24:43and I'm going to pay more attention to written profiles.
0:24:47 > 0:24:50I think it's definitely more important what a person has written
0:24:50 > 0:24:53about themselves than what they look like.
0:24:53 > 0:24:56The profile takes quite a while, it's what sells you,
0:24:56 > 0:24:58so you don't want to scrimp and save on it.
0:24:58 > 0:25:01You can tell somebody's personality, from the way that they write.
0:25:01 > 0:25:04And that can be quite nerve-racking in itself.
0:25:04 > 0:25:06It's so important that you separate yourself
0:25:06 > 0:25:09and make yourself definable.
0:25:10 > 0:25:14Hannah's given me early access to the Horizon dating website.
0:25:14 > 0:25:17It requires a detailed written profile,
0:25:17 > 0:25:20but how should I describe myself to attract the most people online?
0:25:23 > 0:25:26I'm seeking help from Professor Khalid Khan.
0:25:26 > 0:25:30He analysed nearly 4,000 scientific papers to find the best method
0:25:30 > 0:25:33of optimising an online dating profile
0:25:33 > 0:25:37and published the results in a prestigious medical journal.
0:25:37 > 0:25:41His friend and co-author Sameer Chaudry was the first to benefit.
0:25:41 > 0:25:44Previously, seven years single, he had registered with four
0:25:44 > 0:25:47different sites and went on hundreds of dates.
0:25:48 > 0:25:51And then he applied the Khan technique.
0:25:51 > 0:25:53And so what outcome did you get?
0:25:53 > 0:25:58Within three dates, he was able to then find a partner with whom
0:25:58 > 0:26:03- he is still in partnership for the last four years.- Wow! OK.
0:26:03 > 0:26:05So, this all seems very good for me.
0:26:05 > 0:26:09Horizon have built this online experimental dating site.
0:26:09 > 0:26:12- Can you help me fill it out?- Sure. Let's have a go.- OK.
0:26:12 > 0:26:16The first thing we've got to do is choose a username.
0:26:16 > 0:26:18Everyone calls me Xand so, Xand seems like, I don't know,
0:26:18 > 0:26:21XandVT would be kind of what I'd go towards.
0:26:21 > 0:26:24- Do we have evidence about how to choose a username?- Yes.
0:26:24 > 0:26:28I would propose that you consider something that is closer to the top
0:26:28 > 0:26:30- of the alphabet.- Really?
0:26:30 > 0:26:32Does that actually make a difference,
0:26:32 > 0:26:34whether or not it's an A or an X?
0:26:34 > 0:26:37It's more or less like the Yellow Pages effect,
0:26:37 > 0:26:41in that the traders listed at the top of the alphabet
0:26:41 > 0:26:44tend to receive more calls for their business
0:26:44 > 0:26:46- than those at the bottom of the alphabet.- OK.
0:26:46 > 0:26:49So, the next bit of the site says tell us a bit about yourself,
0:26:49 > 0:26:52sell yourself in less than 250 words.
0:26:52 > 0:26:54And this is my nightmare.
0:26:54 > 0:26:56I think this is one of the big barriers to online dating,
0:26:56 > 0:26:58because no-one knows what to put.
0:26:58 > 0:27:01You don't want to be boastful, you want to be humble, but you need to sell yourself -
0:27:01 > 0:27:04it's like this impossible balance of stuff.
0:27:04 > 0:27:06So, what do women look for in this kind of thing?
0:27:06 > 0:27:09So, the important thing to understand is that, in general,
0:27:09 > 0:27:13women prefer that men demonstrate courageousness,
0:27:13 > 0:27:16they prefer the ability to take risks
0:27:16 > 0:27:23and they don't particularly like submissiveness or kindness.
0:27:23 > 0:27:28- So, just being a nice guy is not necessarily the best pitch.- Really?!
0:27:28 > 0:27:31- So, nice guys finish last, basically.- That is correct.
0:27:33 > 0:27:37I mean, that's a bit depressing, isn't it? This is my problem.
0:27:37 > 0:27:39I'm too nice!
0:27:39 > 0:27:41It sounds almost like a cliche,
0:27:41 > 0:27:44but Khalid's meta-analysis of other scientific studies proves that
0:27:44 > 0:27:49in the absence of familiarity, women do prefer bravery over altruism.
0:27:50 > 0:27:53So, I'm not trying to sell myself as a humanitarian,
0:27:53 > 0:27:57it's better to say - I don't know, what have I done?
0:27:57 > 0:27:59Like, I've worked in war zones, you know.
0:27:59 > 0:28:02I should emphasise that rather than saying I fed starving children.
0:28:02 > 0:28:06- That's correct.- And what about the tone of this? Is humour important?
0:28:06 > 0:28:09Humour is important and it is also important to demonstrate humour
0:28:09 > 0:28:14- without saying the words.- Be funny, don't say you're funny.- Yes.- OK.
0:28:14 > 0:28:20So, I'm going to do this now and I will let you know how I get on.
0:28:20 > 0:28:23I wish you very good luck in making progress.
0:28:23 > 0:28:26- I hope your outcome will be... - As good as Sameer's?
0:28:26 > 0:28:28As good as Sameer's, yes.
0:28:30 > 0:28:33Xand needs to hurry up and write his profile,
0:28:33 > 0:28:36because we're about to open the website to the public.
0:28:36 > 0:28:39The challenge is Xand choosing a girl himself
0:28:39 > 0:28:42versus my algorithm matching for him.
0:28:42 > 0:28:45I think that online dating sites can match people.
0:28:45 > 0:28:47I think it's totally possible.
0:28:47 > 0:28:49I guess from our perspective,
0:28:49 > 0:28:51we feel like we were matched really well.
0:28:51 > 0:28:5498 to 99% match.
0:28:54 > 0:28:56It's just maths. Maths got us together.
0:28:56 > 0:28:59- We're definitely pro-algorithm! - Yeah.
0:29:00 > 0:29:02Just like commercial websites,
0:29:02 > 0:29:06the Horizon algorithm takes inputs from an extensive questionnaire.
0:29:06 > 0:29:09Now, our website is based on three inputs in total.
0:29:09 > 0:29:13First, it asks you a questionnaire to find out a little bit about you.
0:29:13 > 0:29:17It also asks you what type of things you're looking for in your partner.
0:29:17 > 0:29:22And thirdly and most importantly, it allows you to rate how important
0:29:22 > 0:29:25those characteristics are in a potential date.
0:29:25 > 0:29:28Now, this last bit is particularly important,
0:29:28 > 0:29:32because you have to have room to set those criteria yourself,
0:29:32 > 0:29:35rather than have a computer set them for you.
0:29:35 > 0:29:39Now, our questionnaire has almost 300 questions,
0:29:39 > 0:29:42so it should give us a really rich understanding of both the people
0:29:42 > 0:29:46that are signing up and how good they'll be for Xand to date.
0:29:46 > 0:29:49But the problem is, is that ultimately a lot of people
0:29:49 > 0:29:52just don't really know what they want until they find it
0:29:52 > 0:29:56and I'm slightly concerned that that might be Xand's problem.
0:30:00 > 0:30:02Maybe not knowing what I should be looking for
0:30:02 > 0:30:05has always been my problem. I've been on loads of dates
0:30:05 > 0:30:08but I'm still no closer to finding a soulmate.
0:30:13 > 0:30:15I'm on top of the Empire State Building.
0:30:15 > 0:30:16Now, this is meant to be
0:30:16 > 0:30:19one of the most romantic locations in the world.
0:30:19 > 0:30:22King Kong met his end here looking for love.
0:30:22 > 0:30:24Tom Hanks did a little better.
0:30:24 > 0:30:25We know that a New York minute
0:30:25 > 0:30:29can be crammed with sex in the city, but what about love?
0:30:29 > 0:30:32Well, they say that if you can make it here, you can make it anywhere,
0:30:32 > 0:30:35but in five years, it hasn't worked out for me.
0:30:35 > 0:30:38Did Frank Sinatra set the bar just a little bit too high?
0:30:38 > 0:30:40Why haven't I found love?
0:30:40 > 0:30:43And why do we fall in love with some people and not others?
0:30:45 > 0:30:48One online dating company was keen to find the answer,
0:30:48 > 0:30:51so approached a scientist who has spent 30 years studying love
0:30:51 > 0:30:54and attraction, Dr Helen Fisher.
0:30:54 > 0:30:58Helen is an expert on what's happening in your brain when you're in love.
0:30:58 > 0:31:00She's now taking this one step further,
0:31:00 > 0:31:04claiming she can match people using a personality questionnaire.
0:31:04 > 0:31:07But as she hasn't yet published her scientific paper,
0:31:07 > 0:31:10I'm curious to find out how it works.
0:31:10 > 0:31:12So, how did you come up with the questionnaire?
0:31:12 > 0:31:15I had studied dopamine in the brain. So, I pulled out a sheet of paper
0:31:15 > 0:31:18and I wrote down "dopamine" at the top of the paper and I listed all
0:31:18 > 0:31:22of the traits that are linked with the dopamine system in the brain.
0:31:22 > 0:31:25Being curious, creative, spontaneous, energetic,
0:31:25 > 0:31:30risk-taking, novelty-seeking, mentally flexible.
0:31:30 > 0:31:32I saw that list and I said,
0:31:32 > 0:31:35"Well, you also know something about serotonin system in the brain,"
0:31:35 > 0:31:37and so I wrote "serotonin" on another sheet of paper
0:31:37 > 0:31:40and I listed the traits linked with the serotonin system.
0:31:40 > 0:31:43Being traditional, conventional, following the rules,
0:31:43 > 0:31:45respecting authority.
0:31:45 > 0:31:48And I had written a book on gender differences in the brain,
0:31:48 > 0:31:50so I knew the traits linked with the testosterone system
0:31:50 > 0:31:54and the oestrogen system, so I said, "I'm going to make a questionnaire
0:31:54 > 0:31:57"to see the degree to which you express the traits
0:31:57 > 0:32:01"linked with all four of these brain systems,
0:32:01 > 0:32:05"and then watch on this dating site who's naturally drawn to whom."
0:32:05 > 0:32:07Oh, wow! So, what happens?
0:32:07 > 0:32:09Well, as it turns out,
0:32:09 > 0:32:12people who are very expressive of the dopamine system -
0:32:12 > 0:32:13I call them explorers -
0:32:13 > 0:32:16they're naturally drawn to people like themselves.
0:32:16 > 0:32:18People who are very expressive in the serotonin system -
0:32:18 > 0:32:20I call them builders - they tend to be...
0:32:20 > 0:32:22Traditional goes for traditional.
0:32:22 > 0:32:24Traditional people want traditional people.
0:32:24 > 0:32:27In those two cases, similarity attracts.
0:32:27 > 0:32:29In the other two cases, opposites attract.
0:32:29 > 0:32:32The high testosterone - analytical, logical, direct, decisive -
0:32:32 > 0:32:36goes for the high oestrogen - empathetic, emotionally expressive,
0:32:36 > 0:32:40good with people. So those two types go for their opposite.
0:32:41 > 0:32:45Helen collected data from 40,000 people on the dating website
0:32:45 > 0:32:49and although she hasn't published it yet, she says it proves her theory.
0:32:49 > 0:32:52Testosterone-driven directors were drawn to
0:32:52 > 0:32:54oestrogen-driven negotiators.
0:32:54 > 0:32:58But serotonin-driven builders and dopamine-driven explorers
0:32:58 > 0:33:03got on best with personality types like themselves.
0:33:03 > 0:33:06So, if I take your personality questionnaire, you should be able to
0:33:06 > 0:33:11figure out a lot more about who I am likely to be attracted to.
0:33:11 > 0:33:13Yes. Absolutely.
0:33:14 > 0:33:18Without seeing the data myself, it's difficult to know if it stands up,
0:33:18 > 0:33:20but I'd like to test Helen's theory
0:33:20 > 0:33:23with help from my married twin brother.
0:33:23 > 0:33:27Our personalities are quite similar, but they're not identical, are they?
0:33:27 > 0:33:30Why are you talking about this? Do the test and then you'll find out.
0:33:30 > 0:33:32That's the difference!
0:33:34 > 0:33:36Will Chris and his wife fit Helen's theory?
0:33:36 > 0:33:39If Chris and I are the same, then maybe his wife's personality
0:33:39 > 0:33:42might be a good indicator of what I should be looking for.
0:33:42 > 0:33:44I can change my mind easily. Yes.
0:33:44 > 0:33:45No!
0:33:45 > 0:33:47Yes.
0:33:47 > 0:33:48Will you do the test?!
0:33:51 > 0:33:55Both Helen and her research associate, neurologist Lucy Brown,
0:33:55 > 0:33:58have been looking at our questionnaires
0:33:58 > 0:34:00and I've come to see what they think.
0:34:00 > 0:34:03You were just a little bit more of an explorer than he.
0:34:03 > 0:34:06He's a little bit more expressive, actually, of the oestrogen system
0:34:06 > 0:34:10and you're just a tiny little bit more expressive of the dopamine system.
0:34:10 > 0:34:12But you're very, very similar.
0:34:12 > 0:34:14So, biologically speaking,
0:34:14 > 0:34:17the woman that you end up falling in love with, she's going to have some
0:34:17 > 0:34:21of these basic personality traits that your brother's wife also has.
0:34:21 > 0:34:23Wow! OK, OK.
0:34:23 > 0:34:26So, according to the personality questionnaire,
0:34:26 > 0:34:28what kind of people should I be looking for?
0:34:28 > 0:34:30Well, certainly other explorers like yourself.
0:34:30 > 0:34:33Otherwise, I think that you'll get bored.
0:34:35 > 0:34:38Helen's theory about the personality matching runs true for Chris
0:34:38 > 0:34:41and his wife Dinah. She, like him, is an explorer.
0:34:41 > 0:34:43But how deep is their love?
0:34:43 > 0:34:49Thanks to neuroscience, we should be able to see if the love is there.
0:34:49 > 0:34:52We can now scan people and find out whether they're really in love.
0:34:52 > 0:34:57In fact, we have had the experience of someone about to get married,
0:34:57 > 0:34:59and I didn't see anything
0:34:59 > 0:35:02and it was someone I knew and I didn't know really what to say.
0:35:02 > 0:35:05- She was divorced within a year. - HE GASPS
0:35:05 > 0:35:08- Really?!- Yes.- Yeah.- Oh!- Yeah.
0:35:08 > 0:35:13There's a bit of "I told you so" there. Yeah, OK.
0:35:14 > 0:35:17In an act of brotherly love, Chris has agreed to put his marriage
0:35:17 > 0:35:21under the microscope - or rather, the MRI scanner -
0:35:21 > 0:35:24to find out how much he loves his explorer wife.
0:35:29 > 0:35:32That's a nice picture of Dinah you've chosen. Or did she choose it?
0:35:32 > 0:35:33It's a picture that Dinah chose!
0:35:33 > 0:35:35HE LAUGHS
0:35:35 > 0:35:37- OK, it's starting now.- OK.
0:35:41 > 0:35:43OK.
0:35:43 > 0:35:47And as I'm not in love, I'm the control.
0:35:47 > 0:35:50I'm looking at an ex-girlfriend from nine years ago.
0:35:50 > 0:35:54I shan't identify her as she's moved on in her life.
0:35:54 > 0:35:56But as I'm still single, I'm starting to wonder
0:35:56 > 0:35:59if my brain is equipped for romance.
0:35:59 > 0:36:02What do you find when you scan Chris's brain versus my brain?
0:36:02 > 0:36:05So, first let's look at Chris's brain here.
0:36:05 > 0:36:09So, here's the brainstem and there's the ventral tegmental area.
0:36:09 > 0:36:10It's red and yellow.
0:36:10 > 0:36:15And he showed up a robust activation
0:36:15 > 0:36:18in that area in response to his wife.
0:36:18 > 0:36:21I love the idea that Chris says he's madly in love and you say,
0:36:21 > 0:36:26"Yes, he has a robust activation in his ventral tegmental area."
0:36:26 > 0:36:29Like that's great, that's proper science, isn't it?
0:36:29 > 0:36:31- He's madly in love with his wife. - So, he is madly in love.
0:36:31 > 0:36:33Good, they're not just putting on a good show.
0:36:33 > 0:36:35There's another sweet thing here.
0:36:35 > 0:36:38This is called the dorsolateral prefrontal cortex,
0:36:38 > 0:36:40but it's a very cognitive area.
0:36:40 > 0:36:44I mean, this is an area of the brain that you use to do higher-level
0:36:44 > 0:36:48cognitive things, like spatial calculations, that kind of thing.
0:36:48 > 0:36:49And even reasoning.
0:36:49 > 0:36:53And reasoning. Reasoning is a great way to summarise it.
0:36:53 > 0:36:56And he's shutting it down.
0:36:56 > 0:36:59- He's literally not thinking.- Yeah.
0:36:59 > 0:37:03Chris is also deactivating an area involved in social judgment -
0:37:03 > 0:37:06in other words, he's not being critical of his wife.
0:37:06 > 0:37:10So, if you just lived with a friend, them leaving the toilet seat up
0:37:10 > 0:37:11would drive you crazy,
0:37:11 > 0:37:13but you forgive it in the person you're in love with.
0:37:13 > 0:37:15You overlook the negative.
0:37:15 > 0:37:19And I would guess that it evolved for a very important purpose.
0:37:19 > 0:37:22I mean, this is going to be your breeding partner, you're going
0:37:22 > 0:37:25to spend years trying to raise some DNA together
0:37:25 > 0:37:29and it would be very adaptive to be able to overlook
0:37:29 > 0:37:31the toilet seat issue.
0:37:31 > 0:37:34So, if you are with someone that you know really likes you,
0:37:34 > 0:37:37you can pretty much behave as you want?! Is that...
0:37:37 > 0:37:41That's what I'm taking away from this! Great.
0:37:41 > 0:37:44- I hadn't thought of that. - No, me neither.
0:37:44 > 0:37:47So, Chris has really got the full package here, hasn't he?
0:37:47 > 0:37:49So, he's got intense romantic love
0:37:49 > 0:37:53and he's suppressing negative thoughts and he's also foolish.
0:37:53 > 0:37:55He's suppressing his thoughts in general.
0:37:55 > 0:37:57Like, he's just a love fool with her.
0:37:57 > 0:38:00For you, you were looking at a former girlfriend
0:38:00 > 0:38:05and you also show that suspension of negative judgment,
0:38:05 > 0:38:09ability to overlook some of her faults.
0:38:09 > 0:38:14She is the latest, flakiest person I know and I forgive her every time.
0:38:14 > 0:38:17Oh! That's great!
0:38:17 > 0:38:20No, no. It's true, it's true, it's true.
0:38:20 > 0:38:22In anyone else, it would drive me crazy,
0:38:22 > 0:38:24but I'm enormously fond of her. Yeah, yeah.
0:38:24 > 0:38:28So, it's not that my brain is simply poorly equipped for romantic love?
0:38:28 > 0:38:31No, it's well equipped.
0:38:31 > 0:38:34So, I'm just as capable of overlooking the negative
0:38:34 > 0:38:36as my brother, which is great news.
0:38:36 > 0:38:39But Lucy has spotted some other brain activity.
0:38:39 > 0:38:42This is all your somatosensory system,
0:38:42 > 0:38:45and there's a huge red blob there.
0:38:45 > 0:38:49As you know, there is a body map, right?
0:38:49 > 0:38:52- Yes. The homunculus.- The homunculus.
0:38:52 > 0:38:54So, leg, arm, face...
0:38:54 > 0:38:56and the genitals, I know...
0:38:56 > 0:38:58HE LAUGHS
0:38:58 > 0:39:00- And that became active?- Yes.- Really?
0:39:00 > 0:39:02- Really?!- Yes.
0:39:02 > 0:39:05HE LAUGHS
0:39:05 > 0:39:08That's very funny. So, this is very strange,
0:39:08 > 0:39:12to sit with you looking at my brain and you're going...right there.
0:39:12 > 0:39:15- Right. - That's where your genitals lit up.
0:39:16 > 0:39:19There really is no hiding how you feel from these scientists.
0:39:19 > 0:39:24But I'm happy that my brain has the capacity for love.
0:39:24 > 0:39:27It's renewed my enthusiasm for online dating
0:39:27 > 0:39:29and given me an insight into
0:39:29 > 0:39:31the personality type I should be trying to choose.
0:39:34 > 0:39:37- Cuddling?- Yeah, cuddling is very important.- Everyone loves cuddling.
0:39:37 > 0:39:40The Horizon website has been live for five weeks now
0:39:40 > 0:39:43and there are plenty of women for Xand to choose from.
0:39:43 > 0:39:46But will the algorithm do better than him?
0:39:46 > 0:39:49It's matching on shared values and ideals,
0:39:49 > 0:39:51rather than personality traits.
0:39:51 > 0:39:53They've got a very good match at 82.
0:39:53 > 0:39:57But we're not just looking for a girl for Xand.
0:39:57 > 0:40:00200 men and women of all ages and orientations
0:40:00 > 0:40:03have signed up to the site and some will be invited
0:40:03 > 0:40:06to the event where we test the matching system.
0:40:06 > 0:40:09- And they look pretty amenable, right?- Mm-hm.
0:40:09 > 0:40:11They're quite happy to get on with a lot of people.
0:40:11 > 0:40:15Because it's a relatively small sample size, our algorithm
0:40:15 > 0:40:19only matches one couple at 85%.
0:40:19 > 0:40:21But when we reduce the match percentage,
0:40:21 > 0:40:24more and more people become compatible with each other.
0:40:24 > 0:40:28So, we know that this is a group of people who are quite intelligent,
0:40:28 > 0:40:30who like science - goes without saying -
0:40:30 > 0:40:33but find geekiness quite sexy.
0:40:33 > 0:40:36This is a group of people who are quite romantic,
0:40:36 > 0:40:38who are looking for a long-term relationships,
0:40:38 > 0:40:39rather than just hook-ups,
0:40:39 > 0:40:44but they also like beer and are very open to new ideas.
0:40:44 > 0:40:47So, generally a good bunch, I think.
0:40:47 > 0:40:49It's boding well for finding a date for Xand,
0:40:49 > 0:40:53but I want to dig into some of the things I know are important to him.
0:40:53 > 0:40:55What about the cats question, though?
0:40:55 > 0:40:57Because I know cats is very important for Xand.
0:40:57 > 0:41:01So, the algorithm has given us a shortlist.
0:41:01 > 0:41:05We think that there are two, maybe three matches
0:41:05 > 0:41:08that we can set up for Xand of potential dates.
0:41:10 > 0:41:14But do all daters believe these algorithms work?
0:41:14 > 0:41:18The matching's easy, it's the chemistry bit which is the hard bit.
0:41:18 > 0:41:21I don't think it can just boil down to a computer program that decides
0:41:21 > 0:41:23whether you get on with somebody or not.
0:41:23 > 0:41:26I like to think that love is much more impulsive and spontaneous
0:41:26 > 0:41:27than science can ever create.
0:41:27 > 0:41:30Lots of people tell you that their eyes met across a crowded bar
0:41:30 > 0:41:33and from that moment onwards they were smitten, and that's not
0:41:33 > 0:41:36an algorithm or a spreadsheet that's telling them that.
0:41:36 > 0:41:40That's something that if you could bottle it, you'd be extremely rich.
0:41:41 > 0:41:44Online dating is lucrative business
0:41:44 > 0:41:47and some websites make strong claims about their algorithm's ability
0:41:47 > 0:41:50to find people's soulmates.
0:41:50 > 0:41:53But social psychologist Eli Finkel doesn't believe the hype.
0:41:53 > 0:41:57He can't prove it, because the sites haven't disclosed their algorithms,
0:41:57 > 0:42:00but in his paper critiquing the industry, he argues that dating
0:42:00 > 0:42:04companies haven't published any evidence to support their claims.
0:42:05 > 0:42:08They have spent hundreds of millions of dollars telling the world that
0:42:08 > 0:42:13there are soulmates, but it turns out that even believing that there
0:42:13 > 0:42:17is such a thing as a soulmate tends to be destructive for relationships.
0:42:17 > 0:42:19I wouldn't say I'm particularly
0:42:19 > 0:42:22romantic or naive about these things,
0:42:22 > 0:42:24but that's a bit of a body blow, I have to say,
0:42:24 > 0:42:27- that I don't have a soulmate. - You don't!- OK.
0:42:27 > 0:42:32But my assumption was that because they're getting such massive
0:42:32 > 0:42:35quantities of data, the algorithms would do a better job than I would.
0:42:35 > 0:42:38That they would be more sophisticated than a swiping app.
0:42:38 > 0:42:40The truth is, there is no way that
0:42:40 > 0:42:44these algorithms can do what they're claiming to do.
0:42:44 > 0:42:46- Really?!- Yes.
0:42:46 > 0:42:49They're claiming that they can set you up with somebody who is
0:42:49 > 0:42:53more romantically compatible with you than some other person
0:42:53 > 0:42:58chosen more and less at random. And, yes, the scientific community
0:42:58 > 0:43:01who don't have a horse in the race, there's a pretty wide consensus
0:43:01 > 0:43:05here is that none of these algorithms can succeed in that task.
0:43:05 > 0:43:09If these online dating sites conducted one rigorous,
0:43:09 > 0:43:13compelling study showing nothing but increased satisfaction
0:43:13 > 0:43:17following a first date, I would already take back my words.
0:43:22 > 0:43:26But having sifted through the psychological literature, Eli thinks
0:43:26 > 0:43:29there's one area where algorithms can work.
0:43:29 > 0:43:33People who are highly neurotic are in fact, on average,
0:43:33 > 0:43:35not very good relationship partners.
0:43:35 > 0:43:38They have way more conflict and they're much more difficult.
0:43:38 > 0:43:41Do I think eHarmony any can figure out who's neurotic? Yes.
0:43:41 > 0:43:43It's not a hard thing to do.
0:43:43 > 0:43:47And the reason why I believe that eHarmony actually does assess
0:43:47 > 0:43:49that stuff and use it in their algorithm
0:43:49 > 0:43:53is they frequently tell people we don't have anybody for you.
0:43:53 > 0:43:56And my guess is what they're saying is,
0:43:56 > 0:43:59you're a lousy relationship partner
0:43:59 > 0:44:03- and we're not going to take your money.- Wow!
0:44:03 > 0:44:05Because we think you will pollute our pool.
0:44:05 > 0:44:09So, even though dating sites can't match you with your soulmate,
0:44:09 > 0:44:13at least they can sift out undesirables. But is that enough?
0:44:13 > 0:44:16I often get presented as like a scold,
0:44:16 > 0:44:18somebody who's taking the industry to task,
0:44:18 > 0:44:22and I suppose that's fair enough, but if the question is,
0:44:22 > 0:44:25is the overall wellbeing in the world better
0:44:25 > 0:44:27because online dating exists?
0:44:27 > 0:44:31- The answer is, without any qualification, yes.- Wow! OK.
0:44:31 > 0:44:33- Thank you very much.- My pleasure.
0:44:33 > 0:44:37You've got to keep you posted on how it goes.
0:44:39 > 0:44:42So having spoken to Eli about this, I guess I feel quite conflicted.
0:44:42 > 0:44:44On the one hand, he is sceptical about algorithms,
0:44:44 > 0:44:47but on the other hand, he thinks that online dating -
0:44:47 > 0:44:49and I guess dating in general - is a good thing,
0:44:49 > 0:44:51that's how I'll get what I want.
0:44:51 > 0:44:56So, now it's time for me to pick my date from the Horizon dating site.
0:44:56 > 0:44:59Helen Fisher and Lucy Brown have told me I should be looking
0:44:59 > 0:45:02for someone who's adventurous like me.
0:45:02 > 0:45:06So, I made a shortlist, I'm hoping my written profile -
0:45:06 > 0:45:08and writing that profile was a nightmare -
0:45:08 > 0:45:12but I'm hoping it makes me sound funny AND courageous - not easy.
0:45:12 > 0:45:16My profile picture I'm hoping looks fun and outgoing enough
0:45:16 > 0:45:19for people to want to meet me. So, here goes.
0:45:22 > 0:45:24But before Xand can find out who likes him,
0:45:24 > 0:45:26I want to do an experiment with the rest
0:45:26 > 0:45:29of Horizon's online dating guinea pigs.
0:45:29 > 0:45:34Of the 200 people who signed up to my dating site, we've invited 50
0:45:34 > 0:45:37to help me test whether algorithms
0:45:37 > 0:45:40are as ineffective as Eli Finkel believes.
0:45:40 > 0:45:43MUSIC: Ooh La La by Goldfrapp
0:45:46 > 0:45:49I guess when I arrived I thought I'd feel sorry for them,
0:45:49 > 0:45:51like, "Oh, you poor old single losers!"
0:45:51 > 0:45:53But because I'm one of them, I now look at them and go...
0:45:53 > 0:45:55- You are a single loser!- I know! I know,
0:45:55 > 0:45:59- and I really admire them for doing this.- Fortune favours the brave.
0:45:59 > 0:46:04But first I want to determine how much of the success of online dating
0:46:04 > 0:46:06comes down to actual matching
0:46:06 > 0:46:12and how much is due to the power of suggestion - the placebo effect.
0:46:12 > 0:46:14So, we'll run an experiment.
0:46:14 > 0:46:17Four different groups, each of them slightly different.
0:46:17 > 0:46:22Group A, over in that corner there, they are well matched
0:46:22 > 0:46:26and we've told them that they're all well matched together.
0:46:26 > 0:46:30These yellow wristband wearers are part of a group of people who,
0:46:30 > 0:46:32according to the algorithm,
0:46:32 > 0:46:35should match well to a number of different partners.
0:46:35 > 0:46:39Group B, just behind me here, they are also very well matched,
0:46:39 > 0:46:43but we've told them that they're a terrible match for each other.
0:46:43 > 0:46:46It'll be interesting to see whether these pink wristband wearers
0:46:46 > 0:46:52are more influenced by the algorithm or the power of suggestion.
0:46:52 > 0:46:55We've also got the people who are actually badly matched.
0:46:55 > 0:46:58So, groups C and D over here.
0:46:58 > 0:47:02Of these badly matched daters, Group C, green,
0:47:02 > 0:47:04were told that they were well matched.
0:47:04 > 0:47:08But Group D, purple, were told the truth.
0:47:08 > 0:47:11Maybe it's just that the perception of being well matched is enough
0:47:11 > 0:47:15to trick people into thinking their dates were better than they were.
0:47:15 > 0:47:18At this exact moment, having split them up into the different groups,
0:47:18 > 0:47:22it doesn't look as though one group is having a better time than others.
0:47:23 > 0:47:26After half an hour, everyone puts their wristbands
0:47:26 > 0:47:30into a container according to how well they got on with their dates.
0:47:30 > 0:47:34Statistically, if neither algorithm nor the power of suggestion
0:47:34 > 0:47:39has an effect, we should find the wristbands equally distributed
0:47:39 > 0:47:40between all three baskets.
0:47:40 > 0:47:43So, first up in the sad basket -
0:47:43 > 0:47:45the people who did not have a very good time -
0:47:45 > 0:47:50what is interesting is that there are only pink and purple in here.
0:47:50 > 0:47:54Pink and purple were the two groups that were told that they were
0:47:54 > 0:47:57- not well matched with each other. - Power of suggestion.
0:47:57 > 0:48:00Yeah, implying that people who were expecting to have a bad time
0:48:00 > 0:48:02really did have a bad time.
0:48:02 > 0:48:04Nobody who was told that they were well matched ended up
0:48:04 > 0:48:08not having a good time. It's extraordinary. Suggestion works.
0:48:08 > 0:48:10There's a hint there. OK.
0:48:10 > 0:48:14But if you look at the basket where people had a really good time,
0:48:14 > 0:48:19the biggest number of wristbands in here are the yellow wristbands,
0:48:19 > 0:48:24which is where people were told they were going to have a good time,
0:48:24 > 0:48:27but also, the algorithm said that they would be well matched.
0:48:27 > 0:48:30- That's the highest number in here. - That's really good.
0:48:30 > 0:48:33So, your algorithm did make people have a good time,
0:48:33 > 0:48:36- even beyond what we told them. - Yeah, absolutely.
0:48:36 > 0:48:39I think, generally, what this is saying is that both things
0:48:39 > 0:48:40make a difference -
0:48:40 > 0:48:42both what you tell people - this power of suggestion -
0:48:42 > 0:48:45but also that the algorithm seems to have some effect.
0:48:45 > 0:48:48I think it's really funny that you're surprised by this.
0:48:48 > 0:48:53Well, yeah. We have to be scientists here, in that this is...
0:48:53 > 0:48:55You do, I'm just looking for love!
0:48:55 > 0:48:57SHE LAUGHS
0:48:57 > 0:48:59As there were equal numbers of the two groups who were duped
0:48:59 > 0:49:01- green and pink -
0:49:01 > 0:49:05we'll have to call it a draw between algorithm and placebo.
0:49:05 > 0:49:10Our little test mirrors the results of a much larger online experiment
0:49:10 > 0:49:12by OkCupid.
0:49:13 > 0:49:17'Now it's time to introduce our daters to their best matches...'
0:49:17 > 0:49:20- Recovering-Cyclist...- With Miss...
0:49:20 > 0:49:26'..to see if Hannah's algorithm can find love among our volunteers.'
0:49:26 > 0:49:30- Adman91.- You're with Babe2.
0:49:30 > 0:49:35'If successful, it should bode well for Xand's dates tomorrow.'
0:49:35 > 0:49:39- Alien-Turned-Human. - You are with Knotted-Sheep.
0:49:39 > 0:49:42Oh, gosh. You're already standing together!
0:49:42 > 0:49:45What a surprise!
0:49:45 > 0:49:47That's a good sign.
0:49:51 > 0:49:54It's a fun way of approaching topology, isn't it?
0:49:54 > 0:49:55Yeah, absolutely.
0:49:58 > 0:50:04Do you feel like you wrote this algorithm and you are fiddling with their lives in quite a weird way?
0:50:04 > 0:50:07In a way, it would be very cool if some people actually got together
0:50:07 > 0:50:10this evening and we got to go to a wedding in a couple of years' time.
0:50:10 > 0:50:14You would get to officiate that wedding. You'd be...
0:50:14 > 0:50:17You'd be like the guest of honour. You'd be on top table, for sure.
0:50:17 > 0:50:20I want a little statue of me on top of their cake. That's all I'm saying.
0:50:20 > 0:50:22THEY LAUGH
0:50:22 > 0:50:25But to make sure everyone got paired up,
0:50:25 > 0:50:27not every single match was perfect.
0:50:27 > 0:50:30Well, I had an interesting conversation with my match,
0:50:30 > 0:50:33but there was no initial attraction there, no.
0:50:33 > 0:50:36- I think he likes someone else. - Really?- So, yeah.
0:50:36 > 0:50:39She was very lovely and we had quite a good conversation,
0:50:39 > 0:50:42but I don't think we had a whole lot in common.
0:50:42 > 0:50:44But most seemed quite happy with their match up.
0:50:44 > 0:50:47She lives in Bristol, which is where I'm originally from.
0:50:47 > 0:50:51I do go back to Bristol quite a bit. So, who knows?
0:50:51 > 0:50:56He's quite funny and do you know what, if a guy makes me laugh, I'm putty in their hand. So, yeah.
0:50:56 > 0:50:59We found out we actually had a lot in common.
0:50:59 > 0:51:01And actually we're getting on really well right now.
0:51:01 > 0:51:04So, I guess there might be something to this algorithm.
0:51:04 > 0:51:10But what about the algorithm's very best-matched couple, at 85%?
0:51:10 > 0:51:14- Have you found that you've got quite a lot in common, then?- Yes.- Yes.
0:51:14 > 0:51:18It was not a surprise that we were matched up. We've just been talking the whole day.
0:51:18 > 0:51:21- We started talking while we were still outside.- Do you think you'll stay in touch?
0:51:21 > 0:51:27- Do you think you'll want to see each other again?- I think we'll stay in touch.- I would like to, yes.
0:51:27 > 0:51:29I think from a small sample of people
0:51:29 > 0:51:32over quite a short period of time, you did really well.
0:51:32 > 0:51:34Some of them left arm in arm.
0:51:35 > 0:51:36Yeah, yeah.
0:51:36 > 0:51:41So, I think the algorithm will have picked out some ladies
0:51:41 > 0:51:45for you tomorrow that you'll, at the very least, get on well with.
0:51:45 > 0:51:47All right, we'll see. We'll see.
0:51:47 > 0:51:53I'm looking forward to it much more now than I was before this started.
0:51:53 > 0:51:58- I think that's a good place to start, at the very least.- OK.
0:52:01 > 0:52:04Finally, I'm going to meet my dates.
0:52:04 > 0:52:07- Very nice to meet you. - Nice to meet you.
0:52:07 > 0:52:10The first girl I'm meeting is one I picked using just her photo
0:52:10 > 0:52:13and profile information.
0:52:14 > 0:52:17And since the whole challenge is riding on these dates,
0:52:17 > 0:52:20I'm keeping an eye on proceedings.
0:52:20 > 0:52:23- Are you a chemist by background, then?- I'm a chemist, yeah.
0:52:23 > 0:52:25I did nanochemistry for my PhD.
0:52:25 > 0:52:26I thought Cat was beautiful,
0:52:26 > 0:52:29she's obviously very intelligent, which I really like.
0:52:29 > 0:52:32Do you have strong opinions about national service?
0:52:32 > 0:52:34I don't really have strong opinions on a lot of things.
0:52:34 > 0:52:35She was really good fun.
0:52:35 > 0:52:39Oh, she's Iranian. Great, I'll definitely bring that up.
0:52:39 > 0:52:40That can be fed in somehow.
0:52:42 > 0:52:44I think she quite fancies Xand.
0:52:44 > 0:52:46Yeah, he's cute.
0:52:46 > 0:52:48Yeah, I really enjoyed it.
0:52:50 > 0:52:53I don't know if I'd go on a second date and I kind of think,
0:52:53 > 0:52:55if I don't want to go on a second date with her,
0:52:55 > 0:52:57then what am I doing? Who would I go on a second date with?
0:52:57 > 0:53:00I discovered I didn't like New York at New Year.
0:53:00 > 0:53:03- Nowhere's fun at New Year.- No.
0:53:07 > 0:53:11So, Xand isn't as good at picking a partner as he thinks he is.
0:53:11 > 0:53:14The next date was matched by the algorithm, according to
0:53:14 > 0:53:16shared interests and opinions.
0:53:16 > 0:53:21- Hello.- Very nice to meet you. How are you doing?- I'm good. Nice to meet you.- Thank you for coming.
0:53:21 > 0:53:24But will she have that special something Xand is looking for?
0:53:24 > 0:53:28Do you have, like, do you think you've got good at dating?
0:53:28 > 0:53:31Erm...I don't know, I'm not sure.
0:53:31 > 0:53:35- That's a really unfair question, I think you're good at dating!- Yeah, thanks. Yeah.
0:53:35 > 0:53:38I liked her, I thought she was nice, I thought she was attractive.
0:53:38 > 0:53:41You know, it's a bit like when you interview people for a job...
0:53:41 > 0:53:43I didn't think the algorithm did a bad job...
0:53:43 > 0:53:48I think dates are a little bit like that. You know straight away if you're going to like someone or not.
0:53:48 > 0:53:51Ooh, there was locked eye contact and a smile right then!
0:53:56 > 0:54:00He could probably chat the hind legs off a donkey, I'm pretty sure.
0:54:00 > 0:54:03But, yeah, he seems like a nice, genuine guy.
0:54:03 > 0:54:06I think subtle personality traits meant that there wasn't a spark,
0:54:06 > 0:54:09but I don't know, is that the algorithm's fault? I suspect not.
0:54:09 > 0:54:13I think, I guess, if I met 50 people like her,
0:54:13 > 0:54:15one of them might be perfect.
0:54:15 > 0:54:18- The format of a date...- Yeah.- ..it is a terrible idea.
0:54:18 > 0:54:19Yeah, yeah. It is.
0:54:19 > 0:54:22Having watched both Xand's dates,
0:54:22 > 0:54:25I don't think either of us have won the bet.
0:54:25 > 0:54:27But there's one more date left.
0:54:30 > 0:54:33How are you doing? Oh, really nice to meet you.
0:54:33 > 0:54:35- Come in, this way.- Great.
0:54:35 > 0:54:39This date appeared on both the list of good matches,
0:54:39 > 0:54:43according to the algorithm and the list that we asked Xand to put
0:54:43 > 0:54:46together himself of people he'd like to meet and date.
0:54:46 > 0:54:48Because we both selected her,
0:54:48 > 0:54:53neither of us can claim this as a win if this date goes well.
0:54:53 > 0:54:56- Your username was Little Burp, wasn't it?- Yes.- Yeah.- That's right.
0:54:56 > 0:54:58Why was it Little Burp?
0:54:58 > 0:55:01Well, it's a bit silly really, I've got lots of bird tattoos, so
0:55:01 > 0:55:04for a long time my friends have called me Little Bird,
0:55:04 > 0:55:06which is a bit naff, so eventually that became Little Burp,
0:55:06 > 0:55:09because it's funnier and more appropriate.
0:55:09 > 0:55:13From behind, that basically could be my head!
0:55:13 > 0:55:16She looks really similar to me.
0:55:16 > 0:55:18Although, she's much cuter!
0:55:22 > 0:55:25I feel fairly convinced that they both fancy each other.
0:55:25 > 0:55:27I mean, Xand's very dishy.
0:55:32 > 0:55:35I was really bored with my hometown
0:55:35 > 0:55:37by the time I was about ten, I think.
0:55:37 > 0:55:39I'm from Beccles, which is right on the...
0:55:39 > 0:55:41Er, Beccles, just so you know,
0:55:41 > 0:55:44is where my family are from, where my English family are from.
0:55:44 > 0:55:47It's a tiny little town, it's where I'm spending Christmas!
0:55:47 > 0:55:50I've lived in London for 13 years this week.
0:55:50 > 0:55:53- Really? You have, like, a London anniversary.- I do, 17th September.
0:55:53 > 0:55:56I've lived in London for 13 years this week!
0:55:56 > 0:56:00- I deliberately didn't spend lots of time thinking about what you might be like.- OK.
0:56:00 > 0:56:03I had to make the choice, so maybe I'm a bit more...
0:56:03 > 0:56:04Maybe I'm a bit more invested.
0:56:04 > 0:56:06- Oh, bless you! - HE LAUGHS
0:56:06 > 0:56:09I think the date went pretty well.
0:56:09 > 0:56:12As soon as she arrived, I just thought she looked really great.
0:56:12 > 0:56:15Just everything about her was really nice.
0:56:15 > 0:56:17She has a great smile, she was really...
0:56:17 > 0:56:20She was just someone I quite fancied.
0:56:20 > 0:56:26He's a very, sort of, attractive character. He's very articulate.
0:56:26 > 0:56:28I think the more you like someone,
0:56:28 > 0:56:32the harder it is to tell what they think of you.
0:56:32 > 0:56:35So, yeah, maybe there is something in the algorithm.
0:56:40 > 0:56:42Are you texting someone there, Xand?
0:56:43 > 0:56:45SHE LAUGHS
0:56:45 > 0:56:47So, it went well, then?
0:56:49 > 0:56:52Yes. So, my date with Cindy was great,
0:56:52 > 0:56:55but I still have the nervousness of going, "Did she like me?"
0:56:55 > 0:56:57So, she hasn't responded to my text message saying,
0:56:57 > 0:56:59would she like to go for a drink?
0:56:59 > 0:57:01You sent it about three minutes ago!
0:57:01 > 0:57:04Well, no, but... I might check it again!
0:57:05 > 0:57:07No, still nothing.
0:57:07 > 0:57:10- Mate, that's still three-and-a-half minutes later!- Yeah.
0:57:10 > 0:57:13Very seriously, from watching it,
0:57:13 > 0:57:16it was like a completely different date.
0:57:16 > 0:57:20So, I think the algorithm does well,
0:57:20 > 0:57:25but I also think what it can't do is tell you about that spark.
0:57:26 > 0:57:30There's something extra, which you just can't define or capture,
0:57:30 > 0:57:33and you only know it when it's put in front of you.
0:57:33 > 0:57:37But I think that's still massively impressive.
0:57:37 > 0:57:41It's so hard to meet people - my life is so busy,
0:57:41 > 0:57:43my friends are so married.
0:57:43 > 0:57:46Prior to doing this, I'd never written a profile
0:57:46 > 0:57:49and I had never used an algorithm-driven site,
0:57:49 > 0:57:51I'd just used a swiping app,
0:57:51 > 0:57:54and I wouldn't bother with that any more.
0:57:54 > 0:57:57I think online dating is just an introductory service.
0:57:57 > 0:57:58So, it is just a numbers game.
0:57:58 > 0:58:01I wouldn't say it's JUST a numbers game, I think it's, like,
0:58:01 > 0:58:04the most important numbers game you can possibly play!
0:58:04 > 0:58:07I'm still rolling the dice, right? I'm like the last guy in the casino
0:58:07 > 0:58:10when they're trying to turn off the lights.
0:58:10 > 0:58:15I guess what I mean is, I think the internet dating websites
0:58:15 > 0:58:19and their algorithms do do something,
0:58:19 > 0:58:20but I think, ultimately,
0:58:20 > 0:58:23it doesn't guarantee that every date will be good,
0:58:23 > 0:58:27but it gives you a good solid basis on which to build.