In our modern times, the biggest hope for people desperately looking for ideal partnerships are the notorious online dating and matchmaking sites. They promise to filter out Mr. or Mrs. Right from a dozen of million candidates, whom one would have otherwise never the chance to meet or to give them a trial. Even for the minimal version of real life check, the notorious One Night Stand, people on the search would had to spend decades of their life to test just a few thousands of potential partners, and already after the first few mornings-after would probably ruined their emotional integrity completely. And this is where the online matchmakers (like Parship, GMatch, Tinder etc) discovered their market: to promise everyone desparately hunting for an ideal partner the power of computer algorithms, big data and anonymous candidate lists, which ulimately will do the job better, safer, easier and more efficient. A recent study by Samantha Joel and colleagues from three US universities, however, raises serious doubts on this promise. They show that mutial attraction between girls and boys (student volunteers) during a recorded random dating survey had next to nothing to do with a wishlist of personal characteristics that the participants had to fill in in advance. It appears that throwing dices to pick a candidate date partner is not less succesful than having powerful computer programs doing the job.
In two of their speed-dating studies, romantically unattached individuals completed more than 100 self-report measures about traits and preferences that past researchers have identified as being relevant to mate selection. Each participant met each opposite-sex participant attending a speed-dating event for a 4-min speed date. Random forests models predicted 4% to 18% of actor variance and 7% to 27% of partner variance; crucially, however, they were unable to predict relationship variance using any combination of traits and preferences reported before the dates. These results suggest that compatibility elements of human mating are challenging to predict before two people meet.
It also raises the question if we really know what is good for us, or if we simply repeat stereotypes which the public and social media always show us. Do we know, what we want ? Do we know, what we need ? Do we know, what we know ? And if have already doubts about what is really good for us, and who is really good for us, how than should a simple computer algorithm know ?
What could remaine a funny trial and error experience for young people, however, remains to often the last hope even for candidates in their second half of life. It is disappointing to see people who should be life-experienced enough putting all their hope of finding a good partner in the hand of online algorithms.
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