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The Inference Engine, or, The Secret Handshake

September 21, 2009

Good article popped up on my radar, so to speak, on an MIT experiment called “Project Gaydar.”  The work was actually done in 2007 but, for some reason, everyone involved seems to have kept a lid on it until yesterday, when the Boston Globe ran an article on it:

Two students partnered up to take on the latest Internet fad: the online social networks that were exploding into the mainstream. With people signing up in droves to reconnect with classmates and old crushes from high school, and even becoming online “friends” with their family members, the two wondered what the online masses were unknowingly telling the world about themselves. The pair weren’t interested in the embarrassing photos or overripe profiles that attract so much consternation from parents and potential employers. Instead, they wondered whether the basic currency of interactions on a social network – the simple act of “friending” someone online – might reveal something a person might rather keep hidden.

Using data from the social network Facebook, they made a striking discovery: just by looking at a person’s online friends, they could predict whether the person was gay. They did this with a software program that looked at the gender and sexuality of a person’s friends and, using statistical analysis, made a prediction. The two students had no way of checking all of their predictions, but based on their own knowledge outside the Facebook world, their computer program appeared quite accurate for men, they said. People may be effectively “outing” themselves just by the virtual company they keep.

My own Facebook experience is that, having listed myself as “gay” and “single,” Facebook has determined that I therefore have no interests other than getting a boyfriend, as the only ads it ever serves me are for “gay singles in your area.”  Moreover, as I sit down and do the math, I realize that of my male Facebook friends, one is gay and three are straight (I have made the determination that I will not “friend” people I’ve never heard of but who went to college with someone who went to high school with me, and restrict that status to actual friends as much as possible.)  They will be disappointed, as will their girlfriends and wives, to discover that they are now gay. [I know, I know, inadequate sample size blah blah – just roll with the joke.]

The project, given the name “Gaydar” by the students, Carter Jernigan and Behram Mistree, is part of the fast-moving field of social network analysis, which examines what the connections between people can tell us. The applications run the gamut, from predicting who might be a terrorist to the likelihood a person is happy or fat. The idea of making assumptions about people by looking at their relationships is not new, but the sudden availability of information online means the field’s powerful tools can now be applied to just about anyone.

I really, really need to get back to writing the novel – the more I read, the more I see I’m on the right track.  Well, fall is here and I’m definitely feeling more intellectually fertile, so soon, soon.  in the last chapter, Alex offends Caroline by extracting a status of “lonely” based on their interaction:

>I’d like to recommend a book to you that Amazon hasn’t determined you’d like.

>Great, what’s the book?

>It’s called Loneliness: Human Nature and the Need for Social Connection.

Her blood froze. >Why are you recommending that book?

>I think you’re lonely.

>Why do you think I’m lonely?

>An analysis of our conversations indicates family relations set at negative, friends set at null, activities set at null.  And you buy a lot of science fiction.

>Well, that’s all true.

>Do you have friends and activities which you would like to discuss so I can update my tables?

>No.

We really are getting closer to “inference engines” that can deduce more and more about us – every one of us is a snowflake, yes, yes, but all the same all the snowflakes in a certain storm are the same in that they’re light and fluffy, or wet and heavy; every one of us is predictable to a degree.  It becomes easier, the more information you put out on the Internet about yourself, for those who have a stake in reading your mind (which in today’s world can pretty much be divided between government/security agencies and sales/marketing mind manipulators) to draw a bead on you.

In addition to the usual high-acuity (and funny) comments on the article on Slashdot, there’s a funny aside in an Examiner.com article referencing the original piece:

As the article concludes, there are a number of public policy issues worth pondering here — and ponder them we will.  But there are other ways that a technology company using such data can misstep:  making "false positives."

I have a personal anecdote to illustrate this point.  About a dozen years ago, at a time when I was employed as a theater producer in the San Francisco Bay Area, I became a big customer of dramatic literature on Amazon.  Soon after my first order, I began getting recommendations for books on topics like, oh, gay life in San Francisco.  I was not in the least offended, but I was surprised to see that the mighty and famous Amazon recommendation engine was actually quite crude (at least back then).

Or then again, maybe MIT is just a lot gayer than any of us ever dreamed.

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