The Infinite Monkey Cage - Introducing... Uncharted with Hannah Fry Series 2

Episode Date: September 9, 2024

From exposing fraud to finding true love, mathematician Hannah Fry follows the numbers on thrilling adventures of data and discovery. Join her for Series 2 of Uncharted.

This is the BBC. This podcast is supported by advertising outside the UK. This is history at its grubbiest and funniest. Enjoy the complete TV soundtracks of all four Blackadder series, starring Rowan Atkinson, Tony Robinson, Miranda Richardson, Stephen Fry and Hugh Laurie. Got him with my subtle plan. I can't see any subtle plan. Well, Ricky, you wouldn't see a subtle plan if it painted itself purple and danced naked on top of a harpsichord singing, subtle plans are here again.

Start listening to Blackadder, the complete collected series from BBC Audiobooks, available to purchase wherever you get your audiobooks. Hello, it's Hannah Fry here and I am just dropping in your ears to let you know that my new series for BBC Radio 4, Uncharted, Tales of Data and Discovery, is out now. So for the next 15 minutes, I'm going to take over this feed to give you just a little taste of the podcast. Enjoy the first episode. The sun hangs low in the sky. A soft strain of jazz swells in the air, mingling with the gentle rustle of leaves in the breeze. Chris, our protagonist, stands tall under a canopy

of flowers, his blue eyes twinkling in the golden late light of a summer's day. But Chris is nervous. His heart is racing. And then, all of a sudden, there she is. Time seems to slurry and flex as the woman he loves walks towards him. In that moment, it dawns on him.

He's found his soulmate. That something is about to spoil it all. Chris wakes up. The meadow is gone, replaced instead by the cold underside of a computer desk. Would I describe myself as lucky in love? Um... No.

I'm Hannah Fry, a mathematician who studies patterns in human behaviour. And from BBC Radio 4, this is Uncharted, Tales of Data and Discovery. This is a series about how numbers and graphs can help you to map the invisible, about how plots can be rich with you to map the invisible, about how plots can be rich with hidden depths and unheard stories, and about how sometimes, if you know where to look, there is mystery and drama and intrigue to be found, all concealed within a few simple lines on a page. Our story starts in the city of Los Angeles, albeit far away from the glamour of Hollywood. Chris McKinley has woken up in a small cramped cubicle, a desktop computer, his only companion. In recent months Chris

has been spending almost 24 hours a day at this desk. He was in the final sprint of a six year PhD at UCLA and had been there so often that he'd done something drastic. Chris had given up his apartment and was living in his cubicle. I had like a little foam pad that I would roll out under my desk to sleep. And I would go to the UCLA gym to take a shower and being kind of a burnout workaholic type, which I don't recommend.

For five and a half years, he had been feverishly trying to advance a new technology called high-dimensional clustering. But the intense work was losing his luster. Chris had just turned 31. He was certainly not old, but he wasn't getting any younger. Surely, he thought, there's got to be more to life than this. By year six, I was wanting to actually meet someone and start a serious relationship. That's not what is happening. Chris had been making some effort to get out there. Like many of us, he had a carefully honed online persona, shinier, funnier, slightly taller version of the real thing. He knew how to write interesting messages, too.

A witty remark here, a flirtatious comment there, and a looped one-liner to open things up. There were two million women in LA, and they had no idea that he was sleeping in a cubicle. Maybe one of them would see some potential. And there's these many kind of emotional cycles of hype and disappointment, thinking, oh, wow, this person seems really cool.

And then, of course, you write them, and they don't write you back. In nine months of online dating, Chris had matched with less than a hundred women. This perplexed him. He had spent hours tweaking his profile, selecting pictures, answering the dating site's questions. He'd done everything he was supposed to do. And on paper, he was kind of a catch.

Just 31, six foot tall, blue-eyed, with a PhD and a love of music. But despite it all, his profile remained abysmally unloved. Over time, Chris started to wonder whether the problem lay not so much with him, but with the site itself. You know, I probably was not the top hit, even for someone in LA who was searching for nerdy guys six feet tall with blue eyes, I probably wasn't anywhere near the top. I had the visibility problem. If Chris wasn't coming up on other people's searches, his profile might as well be invisible.

And that would reduce his odds of matching, well, anyone, to practically zero. And then another thought hit him, something that tickled his mathematical brain. If you understand how the search engine works, well, you could plausibly just kind of short circuit like almost the whole dating application, you know. If I can just maximize my search ranking and the results to any search that's run, what if I could actually reach the top of every single search, not only for nerdy guys with blue eyes, but literally for like any heterosexual male? If it works, the results have to be interesting. It was a big ask, but if Chris could do it, he would stand a real chance of finally meeting

a stranger who might change the rest of his life. He starts with the basics. How does this algorithm actually work? What does it use to match people? This particular site promised Eager Singles that they could calculate your compatibility with potential partners before you'd even spoken to them. It was based on a series of multiple choice questions. You could answer as many or as few as you wanted, and the algorithm would preferentially show you people whose answers best matched your own. Like there were hundreds and hundreds and hundreds of them. I mean, maybe over 10 or 20,000. You know, 98% of questions like only had maybe 10 people sort of answering them.

But there were a few questions that almost every single person answered. Chris thinks of his own profile. When he had set it up, he had selected and answered questions at random. But what if he had unknowingly selected questions that were unpopular? Well, that could explain everything. If just 10 people had answered the same questions as him, his dating pool wasn't just small, it was tiny. No wonder his matches were so low. I had to know how they had answered these top questions. Two weeks later, Chris was gearing up to push a button. He was about to release an army of bots onto a group of unsuspecting women with just one aim.

To create profiles, gather data and then delete themselves. The dating site had a tiny vulnerability that Chris hoped he could exploit. If your questions and answers had matched someone else's perfectly, then their profile would appear on a list as you logged in. And that meant that if Chris built thousands and thousands of fake profiles, each trying different combinations of answers to different questions. Once their matches had been revealed, the dating site would effectively be telling him how many women had answered in the same way.

And not only that, because the site revealed who these women were, Chris could use his bots to visit each of their profiles and collect detailed data on what kinds of women were answering different types of questions. He had found a way to scrape thousands of profiles, logging every attribute, age, ethnicity, sexuality, height, smoker or nonsmoker, star sign and everything they each cared about and wanted in a partner. star sign and everything they each cared about and wanted in a partner. Now, I know what you're thinking. This feels dubious and probably illegal. I was probably in violation of the Computer Fraud and Abuse Act. I had no idea about any of that. I was just like, well, whatever, the information's online. I'll just go get it. So that's what I did. As the days ticked on, the bots were working overtime,

and the data was flooding in. By now, Chris's PhD had become a side project. And after six weeks, he had harvested six million questions and six million answers from over 20,000 women across LA. This started to take over. I spent more than a couple hundred hours on this. I probably worked on it full time for something like six weeks. You know we should probably get back to that PhD soon, but this was a collection unlike

any he'd ever seen. It was a catalogue of people's preferences, interests, plans, hopes, dreams and desires. And there must be patterns in there too, perhaps even a cluster of women that he would like to meet that might like to meet him in return if only he could find them. So the more I thought about that, the more compelling the idea seemed and I started using all of my time

to download and analyze match data. He turned to a little algorithm called K-Modes, which he'd used in his PhD. This program could take vast amounts of data, sprinkle it across a graph in many, many dimensions. It could search for patterns and create clusters. K-Modes had first been used to identify noxious soybeans, but Chris hoped that maybe it could find groups of like-minded singles too. K-Modes was up and running, the data was filtering through, but his computer was struggling. Its whirring fan had been getting louder. Please, he thought, don't crash now.

And then he saw something. Seven beautiful coloured clusters were waiting patiently between three axes on the screen. Each of them represented a distinct kind of woman, a personality type, a set of interests, and a unified idea of what their next relationship was going to look like. K-Modes had worked. When it actually worked, it quickly became a very, very exciting prospect. Chris immediately selected a sample of names from one of the larger clusters and clicked through to their dating profiles. All of them were highly religious. As an atheist, Chris thought he'd better leave that group well alone.

What would the second cluster hold? This group was clearly new to the dating scene and many of them were looking for one-night stands. But Chris was here for the long haul. The third, fourth and fifth clusters were all out of his age bracket, which was 25 to 45. They were either too young or too old. Now there were only two clusters left. Number six and number seven.

Could either of those be right? And what if they weren't? Number six certainly piqued his curiosity. These women were professional, working as editors or designers, but there was something about the seventh group that captured his imagination. Many of them had tattoos or liked them.

They were musicians or successful artists. They were creative, not for a living, but for themselves. Chris had found what he was looking for, A golden cluster, perhaps hidden somewhere inside it, would be the love of his life. Chris was of course initially pleased, but this wasn't his primary problem. What would be the point of identifying the women he liked if they didn't know he even existed? He needed his profile to get noticed by them. The only things I could really control were which questions I answered and how I answered them. But once I had each cluster, I had access to about a thousand questions, optimised for

each of these sort of clusters of like-minded people. And so Chris got to work on a new hero profile. On signing up, the site suggested question after question, but he would only answer the thousand questions that had also been answered by women in that golden cluster, and even then, only using answers he knew they were looking for. He didn't lie, he just leaned into the traits he now knew would make him appear most attractive. And now for the finishing touches, a short biography and a few pictures and this new all-star profile was finally done. Months of work had been building to this very moment and yet in the hours he'd spent answering the questions, the whole

thing had begun to feel a bit silly. The whole time I was doing that, I was like, this probably isn't going to work. This is a huge waste of time. What are you doing? Doubting himself, Chris closed the site. He shut down his laptop and he folded himself under the desk. It was time to get some sleep. What would he find the next morning? That's the point at which events started to take their own course. And I think I stopped really being in control of this and kind of getting swept along by it. His profile was being matched with women all over the city.

Messages and emails would not stop flooding in. He'd actually done it. So now what? I wasn't really prepared to sort through all the kind of human consequences. No longer were these profiles on a screen, but real people who could judge and reject him. And then there was the problem of the dates themselves.

How many could he take before he'd burn out completely? If you scale that up to like five nights a week, it's going to seriously affect you. I was so shocked that I actually managed to solve the problem. I was therefore obliged to like engage in the IRL portion of this like Odyssey, Carpe Diem, man. Chris decided he would go on one day to day. Some of the early ones were romantic, long walks down the Venice canals,

fancy dinners on rooftops. But as time went on, they were becoming downright wild. He began to meet women in sports cars and was invited to parties that would make Bret Easton Ellis proud. At first, it was fun. But that didn't last all that long. I burnt out after maybe a month of four or five nights a week going on like serious dates. Some dates seemed to go well, others not so much, but few made it to date number two. By July of 2012, Chris had gone on 80 first dates in just five weeks.

I was lagging, because you could often meet three or four people, even just in a single weekend, who are fairly similar. And like, you're meeting people all the time. You know, the question is, are you going to stop doing this? The novelty was wearing off. Where was all of this going? Chris would be going on his 88th first date. If this didn't work soon, the dream would be over.

He would shut everything down. And then, of course, like, I met someone worth shutting it down for. In a small coffee shop right next to the UCLA campus, Christine Tien-Wang had made an immediate impression. Honest to the point of bluntness, I could tell immediately she was extremely competitive and ambitious. It's like meeting someone who got out of Julliard and wanted to be the first chair of violinists for like, I don't know what, you know, Berlin Symphony Orchestra or something like,

I was infatuated by that. I don't wanna say it was love at first sight, but it was like a very strong magnetic attraction, very early. Maybe it's gonna be like a 50-50 call. Maybe it won't work and I'll be back here in six months. So did it work out? Did Chris actually hack one of the biggest dating sites in the world and find true love? Well, sounds a bit too good to be true.

We've been, you know, happily together for almost 11 years and like, thank God, you know, and it's good. like this good perhaps love really is a numbers game after all I love a happy ending don't you that is it for this episode but there are 10 fascinating stories in this series. Search for Uncharted and subscribe on BBC Sounds now. I'm Katie Adler from the Global Story Podcast, where we're looking at the US election and the huge sums of money, billions of dollars being spent by Republicans and Democrats hoping to win in November.

Who's donating the cash? And what impact does it all have on American democracy? The Global Story brings you fresh takes and smart perspectives from BBC journalists around the world. Find us wherever you get your podcasts.