How Privacy Vanishes Online

[David Farber <dave () farber net>]

Begin forwarded message:

From: dewayne () warpspeed com (Dewayne Hendricks)
Date: March 17, 2010 11:49:03 AM EDT
To: Dewayne-Net Technology List <xyzzy () warpspeed com>
Subject: [Dewayne-Net] How Privacy Vanishes Online

March 16, 2010
How Privacy Vanishes Online
By STEVE LOHR
<http://www.nytimes.com/2010/03/17/technology/17privacy.html>

If a stranger came up to you on the street, would you give him your name, Social Security number and e-mail address?

Probably not.

Yet people often dole out all kinds of personal information on the Internet that allows such identifying data to be 
deduced. Services likeFacebook, Twitter and Flickr are oceans of personal minutiae — birthday greetings sent and 
received, school and work gossip, photos of family vacations, and movies watched.

Computer scientists and policy experts say that such seemingly innocuous bits of self-revelation can increasingly be 
collected and reassembled by computers to help create a picture of a person’s identity, sometimes down to the Social 
Security number.

“Technology has rendered the conventional definition of personally identifiable information obsolete,” said Maneesha 
Mithal, associate director of the Federal Trade Commission’s privacy division. “You can find out who an individual is 
without it.”

In a class project at the Massachusetts Institute of Technology that received some attention last year, Carter Jernigan 
and Behram Mistree analyzed more than 4,000 Facebook profiles of students, including links to friends who said they 
were gay. The pair was able to predict, with 78 percent accuracy, whether a profile belonged to a gay male.

So far, this type of powerful data mining, which relies on sophisticated statistical correlations, is mostly in the 
realm of university researchers, not identity thieves and marketers.

But the F.T.C. is worried that rules to protect privacy have not kept up with technology. The agency is convening on 
Wednesday the third of three workshops on the issue.

Its concerns are hardly far-fetched. Last fall, Netflix awarded $1 million to a team of statisticians and computer 
scientists who won a three-year contest to analyze the movie rental history of 500,000 subscribers and improve the 
predictive accuracy of Netflix’s recommendation software by at least 10 percent.

On Friday, Netflix said that it was shelving plans for a second contest — bowing to privacy concerns raised by the 
F.T.C. and a private litigant. In 2008, a pair of researchers at the University of Texas showed that the customer data 
released for that first contest, despite being stripped of names and other direct identifying information, could often 
be “de-anonymized” by statistically analyzing an individual’s distinctive pattern of movie ratings and recommendations.

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