I n the Summer of 2012, Chris McKinlay was finishing his maths dissertation at the University of California in Los Angeles. It meant a lot of late nights as he ran complex calculations through a powerful supercomputer in the early hours of the morning, when computing time was cheap.
The idea that technology can make difficult, even painful tasks – including looking for love – is a pervasive and seductive one, but are their matchmaking powers overstated?
One of his favourite sites, OkCupid, sorted people into matches using the answers to thousands of questions posed by other users on the site.
“One night it started to dawn on me the way that people answer questions on OkCupid generates a high dimensional dataset very similar to the one I was studying,” says McKinlay, and it transformed his understanding of how the system worked. “It wasn’t like I didn’t like OkCupid before, it was fine, I just realised that there was an interesting problem there.”
McKinlay started by creating fake profiles on OkCupid, and writing programs to answer questions that had also been answered by compatible users – the only way to see their answers, and thus work out how the system matched users. He managed to reduce some 20,000 other users to just seven groups, and figured he was closest to two of them. So he adjusted his real profile to match, and the messages started rolling in.
McKinlay’s operation was possible because OkCupid, and so many other sites like it, are much more than just simple social networks, where people post profiles, talk to their friends, and pick up new ones through common interest. Instead, they seek to actively match up users using a range of techniques that have been developing for decades.
Every site now makes its own claims to “intelligent” or “smart” technologies underlying their service. But for McKinlay, these algorithms weren’t working well enough for him, so he wrote his own. McKinlay has since written a book Optimal Cupid about his technique, while last year Amy Webb, a technology CEO herself, published Data, a Love Story documenting how she applied her working skills to the tricky business of finding a partner online.
Two people, both unsatisfied by the programmes on offer, wrote their own; but what about the rest of us, less fluent in code? Years of contested research, and moral and philosophical assumptions, have gone into creating today’s internet dating sites and their matching algorithms, but are we being well served by them?
While his work hummed away, he whiled away time on online dating sites, but he didn’t have a lot of luck – until one night, when he noted a connection between the two activities
In the summer of 1965, a Harvard undergraduate named Jeff Tarr decided he was https://besthookupwebsites.org/meetville-review/ fed up with the university’s limited social circle. As a maths student, Tarr had some experience of computers, and although he couldn’t program them himself, he was sure they could be used to further his primary interest: meeting girls. With a friend he wrote up a personality quiz for fellow students about their “ideal date” and distributed it to colleges across Boston. Sample questions included: “Is extensive sexual activity [in] preparation for marriage, part of ‘growing up?'” and “Do you believe in a God who answers prayer?” The responses flooded in, confirming Tarr’s suspicion that there was great demand for such a service among the newly liberated student population. Operation Match was born.
In order to process the answers, Tarr had to rent a five-ton IBM 1401 computer for $100 an hour, and pay another classmate to program it with a special matching operation. Each questionnaire was transferred to a punch-card, fed into the machine, and out popped a list of six potential dates, complete with address, phone number and date of graduation, which was posted back to the applicant. Each of those six numbers got the original number and five others in their response: the program only matched women with their ideal man if they fitted his ideal too.