Data, A Love Story by Amy Webb

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Tuesday, October 4, 2016

I honestly don't know what to think about Data, A Love Story by Amy Webb. I'm a geek; I love math and data and statistics. The idea of tackling online dating using statistical analysis and profile optimization is intriguing.

I saw Webb's TED talk on this subject before I read her book. Her presentation is all about the numbers, the data crunching, and what she learned about how to game online dating systems. In her talk, she comes across as warm, funny, and approachable.

The book is less about data and math, and more a memoir of her romantic life. She also doesn't come across as quite so likable in her book and that occasionally put me off. She seems, by turns, neurotic, judgmental, and distant. Some of her dating horror stories are quite amusing, but I must confess: I don't care that much about her love life. I wanted more "data" and less "love story."

Want to make up your own mind about Data, A Love Story?

Read it and share your thoughts at our FYI Book Group meeting on February 24, 2015.

And don't forget to count your reading for our Adult Winter Reading Program: Love on the Rocks for which this is a suggested book!

Read any five books by March 20, 2015, and earn your limited edition tumbler glass and be entered in a drawing for a NOOK GlowLight eReader.

I admire Webb's commitment to finding a solution to her dating woes, her dedication to "out-think the problem." She's clearly very self-aware and willing to own up to her mistakes and shortcomings. For example, at the beginning of one chapter, she's insultingly judgmental toward other women on JDate, but by the end of it she's perfectly willing to admit that she's being unfair to them. I admire her honest self-criticism. But I can't bring myself to go all the way on this journey with her. As successful as her endeavor was for her, I'm not sure how well her approach will work for other people.

It makes sense for Webb to seek solutions to the failures of online dating by using data and math, as online dating sites are data-driven, algorithmically-determined services. Workable solutions can only be found in manipulable data.

I can't agree with one of the fundamental premises of her experiment, however. Everything starts with her "Mary Poppins" list, the 72 data points she creates to define her perfect husband. This list is what she uses to establish her methodology. The ultimate success of her experiment depends on the accuracy of that list and the relative values she assigns to each point.

Webb's fundamental premise is a belief that she can reliably define exactly who her perfect match should be. In the "Appendix" of the book, where she lays out specific guidelines for users of dating sites to follow, she starts by emphasizing the need for each user to define exactly what sort of person they're looking for. This is a necessary first step before anyone can begin to customize their profile appropriately. Without a "Mary Poppins" list, her strategy doesn't apply.

Webb evinces no awareness of the fact that people don't always know what they want. Too often, we convince ourselves that we want things when we really don't.

People frequently don't know what will make them happy. Sometimes, the things we're certain will make us happy end up disappointing. Sometimes, we find happiness in things we never anticipated. Moreover, what we want in our lives isn't always what we need. If many of us don't always know what we want, we know what we need even less.

Throughout the book, Webb makes no bones about the fact that she's a very unique woman—she knows that she's not typical. Somehow, though, it never seems to occur to her that her ability to create a "Mary Poppins" list in the first place might be something that other people can't do. I don't assume that any of us are objective enough to know with absolute certainty who our perfect partner should be before we meet them.

To her credit, this approach worked for her. She's sufficiently self-aware and capable of being brutally honest with herself. She has an ability to be objective about her emotions in a way that many people can't. I don't believe that her approach to online dating would work for me. I don't know how many people it would work for.