Joel scheduled a talk in October 2019 at the University of Waterloo in Canada with the straightforward title: “Can we help people pick better romantic partners?”
So, can Samantha Joel — teaming up with 85 of the world’s most renowned scientists, combining data from 43 studies, mining hundreds of variables collected from more than 10,000, and utilizing state-of-the-art machine learning models — help people pick better romantic partners?
The number one — and most surprising lesson in the data, Samantha Joel told me in a Zoom interview, is “how unpredictable relationships seem to be.” Joel and her coauthors found that the demographics, preferences, and values of the two people had surprisingly little power in predicting whether those two people were happy in a romantic relationship.
And there you have it, folks. Ask AI to figure out whether a set of two human beings can build a happy life together and it is just as clueless as the rest of us.
Well… that sure seems like a letdown. Does data science really have nothing to offer us in picking a romantic partner, perhaps the most important decision that we will face in life?
Not quite. In truth, there are important lessons in Joel and her coauthors ‘machine learning project, even if computers’ ability to predict romantic success is worse than many of us might have guessed.
For one, while Joel and her team found that the power of all the variables that they had collected to predict a couple’s happiness was surprisingly small, they did find a few variables in a mate that at least slightly increased the odds you would be happy with them. More important, the surprising difficulty in predicting romantic success has counterintuitive implications for how we should pick romantic partners.
Think about it. Many people certainly believe that many of the variables that Joel and her team studied are important in picking a romantic partner. They compete ferociously for partners with certain traits, assuming that these traits will make them happy. If, on average, as Joel and her coauthors found, many of the traits that are most competed for in the dating market do not correlate with romantic happiness, this suggests that many people are dating wrong.
This brings us to another age-old question that has also recently been attacked with revolutionary new data: How do people pick a romantic partner?
In the past few years, other teams of researchers have mined online dating sites, combing through large, new datasets on the traits and swipes of tens of thousands of single people to determine what predicts romantic desirability. The findings from the research on romantic desirability, unlike the research on romantic happiness, has been definitive. While data scientists have found that it is surprisingly difficult to detect the qualities in romantic partners that lead to happiness, data scientists have found it strikingly easy to detect the qualities that are catnip in the dating scene.
A recent study, in fact, found that not only is it possible to predict with great accuracy whether someone will swipe left or right on a particular person on an online dating site, it is even possible to predict, with remarkable accuracy, the time it will take for someone to swipe. (People tend to take longer to swipe for someone close to their threshold of dating acceptability.)