Love Is Not Algorithmic
Love Is Not Algorithmic
There is no higher praise these days than being data-driven. A person who is data-driven is free of bias, and cuts through arguments with a sword of truth. No longer do we need to fumble through life. The answers will come. We will know how to respond, just what to do. We will let the data tell us!
And so it goes with Christian Rudder’s new book Dataclysm: Who We Are (When We Think No One’s Looking), a synopsis of insights he gleaned from analytics while working at the company he co-founded, OKCupid. His company, he tells us, could easily sport the tagline “Making the Ineffable Totally Effable.” Indeed, his book sets out to do this, yielding some gainful insights on dating expectations, along with other, more unsurprising findings: Men like younger women (no duh). These data are amusing, even charming.
But something more is at risk. What is troubling here, as we enter the Age of Big Data, the Age of the Internet, and the like, is that we are also entering an Age of the Axiomatic.
To be axiomatic, at its best, is to be deductive, but at its worst, it is to assume that a system is consistent and complete. For instance, in the field of genetics, we can look at aggregate data from 100,000 patients to deduce a mutation that is apt to cause a disease in any single patient. That is the power of deductive logic. But in assuming the system of logic is complete, we may fail to anticipate alternate causes, in this case “epigenetic” or biological mechanisms beyond DNA. Axioms work well in the realm of pure numbers and physics, but they are often superficially applied to biology, and especially so when applied to the social sciences.
Exactly the point we assume the data of a system to be both consistent and complete. This is when axiomatic logic at its most naïve and dangerous.
This dangerous kind of axiomatic logic is pronounced when we assume that a user is a collection of “data points” with a consistent or complete identity. In fact, online-dating services are notoriously complicated by users’ own impossible burden of fully representing themselves in a two-dimensional personality. Social media has struggled to contemplate the self-contradiction and inconsistency of its own users—to see them as more than flat profiles that can be targeted for advertising. Speaking of users who have multiple profiles, Mark Zuckerberg famously said “having two identities for yourself is an example of a lack of integrity.” Writer Curtis Sittenfeld quipped in The New York Times: “To which my only response is, ‘You’ve got to be kidding.’ I mean, I’m not even the same person with all the members of my immediate family.”
Cultural critics have been raising questions about the intrinsic value of such shallow data for years. Jonathan Franzen’s 2011 commencement address at Kenyon College was the most famous but not the only rebuttal. He suggested that “technology provides an alternative to love,” a pleasant distraction that derails our train of thought and drains our empathy. David Brooks’ 2013 column in The New York Times on “What Data Can’t Do” suggested that “network scientists can map your interactions with the six co-workers you see during 76 percent of your days, but they can’t capture your devotion to the childhood friends you see twice a year, let alone Dante’s love for Beatrice, whom he met twice.” The French philosopher Alain Badiou provided the most direct challenge to social networking in his 2012 book “In Praise of Love.” He suggested online dating was a form of “safety first” love, in which love becomes a commodity or a consumer product. He went so far as to suggest that the premise of the user experience is an affront to the spirit of love. According to Badiou, to enter a relationship is not to compliment your “likes,” but to undergo a confrontation to identity, to enter a process: “Personally, I have always been interested in issues of duration and process, and not only starting points.”
Indeed, writers have long described love through its challenge to identity, its contradiction and its process. They defy readers to embrace what philosophers call “alterity,” or otherness—the possibility of being totally blindsided by new facts, to achieve an experience that was before entirely foreign. They impose a stance to reading that embraces antagonism, and incompleteness, and is sunken in process. I admit, I equate books with love. The only way to approach a book as a serious reader is to approach it as a relationship, as something dense and partially submerged. One does not go into reading with an assumption of knowledge or completeness, but with humility, with a willingness to enter into a confrontation that may change you in the process. As the writer Junot Diaz has said, “Every serious reader knows that they don’t understand half of what they read; it’s true, that’s not a joke—because that’s how real life is really like. People you love say shit and you have no idea what they mean.”
In The Space of Literature, philosopher Maurice Blanchot wrote: “What threatens reading is this: the reader’s reality, his personality, his immodesty, his stubborn resistance upon remaining himself in the face of what he reads—a man who knows in general how to read.” Likewise, do we sell ourselves short by applying a scientific approach to love, one in which we become “prisoners of allusion,” reduced to our web profiles, cliches and guided by trite axioms? In his book, Rudder suggests the importance of a prominent tattoo; he says if you don’t know what to ask your date, the data suggests asking if they like scary movies; it may be a good indicator of your success. That sounds, to me, like someone grasping for straws. In truth, it is probably all a data-driven approach to love can ever do for us.
The data from online-dating platforms will never answer the toughest and most important questions. It cannot tell us why some people never recover from heartbreak, why we mimic some people and give short shrift to others, why some people fall in love too quickly, or why people who should care walk out on us. Part of us will never be “totally effable.” To feel safely assessed and under the control of numbers, you might read Dataclysm. As for me, I will read Badiou.