In the dating market, people compete ferociously for mates with qualities that do not increase one’s chances of romantic happiness

Adapted from Don't Trust Your Gut: Using Data to Get What You Really Want in Life, by Seth Stephens-Davidowitz. Wired, May 2022. https://www.wired.com/story/data-marriage-behavior-love-psychology-romance/

Whom shoud you marry?

This may be the most consequential decision of a person’s life. The billionaire investor Warren Buffett certainly thinks so. He calls whom you marry “the most important decision that you make.”

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She recruited a large number of scientists who had collected data on relationships—her team ended up including 85 other scientists—and was able to build a dataset of 11,196 heterosexual couples.

The size of the dataset was impressive. So was the information contained in it. For each couple, Joel and her team of researchers had measures of how happy each partner reported being in their relationship. And they had data on just about anything you could think to measure about the two people in that relationship.

The researchers had data on:

demographics (e.g., age, education, income, and race)

physical appearance (e.g., How attractive did other people rate each partner?)

sexual tastes (e.g., How frequently did each partner want sex? How freaky did they want that sex to be?)

interests and hobbies

mental and physical health

values (e.g., their views on politics, relationships, and child-rearing)

and much, much more.

Further, Joel and her team didn’t just have more data than everybody else in the field. They had better statistical methods. Joel and some of the other researchers had mastered machine learning, a subset of artificial intelligence that allows contemporary scholars to detect subtle patterns in large mounds of data. One might call Joel’s project the AI Marriage, as it was among the first studies to utilize these advanced techniques to try to predict relationship happiness.

After building her team and collecting and analyzing the data, Joel was ready to present the results—results of perhaps the most exciting project in the history of relationship science.

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?

No.

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 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 increase the odds you will 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.

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If I had to sum up, in one sentence, the most important finding in the field of relationship science, thanks to these Big Data studies, it would be something like this (call it the First Law of Love): In the dating market, people compete ferociously for mates with qualities that do not increase one’s chances of romantic happiness.

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