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Book Review: Dataclysm: Who We Are (When We Think No One’s Looking) by Christian Rudder
The popularity and usefulness of online dating services is hard to dispute. Rare is the person nowadays who does not know at least one happy couple brought together by a computer algorithm that suggested they might get along. The nature of online dating is roughly the same from service to service: person A submits a questionnaire and a personal statement. The computer considers preferences, both spoken and assumed, and returns a small number of possible matches. In a world where it can seem difficult to find “the one,” computers now wield their power to sort through millions of possible “ones” to get people moving in the right direction: toward their mutual “one.”
Christian Rudder, author of Dataclysm: Who We Are (When We Think No One is Looking) (Crown Publishing, 2014) is a founder of one of these successful services, so he has access to questionnaire responses, personal statements, user ratings on others’ attractiveness, and countless other data related to who people are. Clients may say they’re open-minded, but when they actually respond positively to twenty consecutive prospective matches who fit the same profile, open-mindedness appears to be the kind of thing one claims but doesn’t demonstrate. However, the power of Rudder’s data is in its massiveness. Where the user is concerned with his “one,” the scientist is concerned with removing any concept of oneness and taking the broad view. The original question have been, “Are you attracted to Asians?” but when five million people have responded to it, people who’ve self-identified as being a member of some ethnic or racial demographic, the singular “you” isn’t nearly as interesting (or revealing) as the collective “you.” Forget John H. in Omaha; what do three million people like him find attractive? “If Big Data’s two running stories have been surveillance and money, for the last three years I’ve been working on a third: the human story,” he writes, and his aim is to use the data to take a look at what the numbers say about what brings us together, what pulls us apart, and what makes us who we are.
Readers who tend to look the other way when math is brought into a discussion might be tempted to do so here, and the author’s proclivity for charts and graphs might encourage this response, but the numerically averse are urged to hang in there. Rudder’s explanations of the data turn dots on a graph into fascinating generalizations, such as what single members of one race think about single members of other races, and which races are least and most popular among the service’s clientele, or how different men and women are in their stated (and actual) romantic preferences, or which words we are most likely to use in describing ourselves for others (“pizza” is number two across demographics, believe it or not). Probably best of all, Rudder’s narrative is loaded with wit and humor, sometimes turned on the analysis itself and other times turned just on some of the weirdness we all encounter when we study people.
It’s easy nowadays to think of Big Data as a weapon to be used against us. Everyone’s got a friend or two who makes the utmost effort to leave no digital footprint, lest some malicious entity as large as the government or as small as the teenage hacker club on the next block use some kind of collected data against them. Yet one of the strengths of Dataclysm is the way it reveals to us what Big Data can be: a magnifying glass for zooming in on particulars or a glass mirror for looking at ourselves. “Practically as an accident,” writes Rudder, “digital data can now show us how we fight, how we love, how we age, who we are, and how we’re changing.”
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