Winners of the Netflix Prize for boosting Netflix's movie recommendation engine barely had a chance to start spending their £600,000 prize before controversy erupted over a second contest.
Privacy researcher Paul Ohm, an associate professor of law at the University of Colorado Law School, posted a recommendation of his own regarding the Netflix Prize 2 on the blog Freedom to Tinker: He called on Netflix to nix the project. Ohm writes that Netflix would be taking too big a risk with customer privacy given the sort of demographic and behavioral data it would need to share with contest participants:
"Netflix should cancel this new, irresponsible contest, which it has dubbed Netflix Prize 2. Researchers have known for more than a decade that gender plus ZIP code plus birthdate uniquely identifies a significant percentage of Americans (87% according to Latanya Sweeney's famous study.) True, Netflix plans to release age not birthdate, but simple arithmetic shows that for many people in the country, gender plus ZIP code plus age will narrow their private movie preferences down to at most a few hundred people. Netflix needs to understand the concept of 'information entropy': even if it is not revealing information tied to a single person, it is revealing information tied to so few that we should consider this a privacy breach."
Meanwhile, AT&T Labs-Research, Yahoo Research and other members of the Bellkor's Pragmatic Chaos team are celebrating their win in the initial 3-year-long Netflix Prize contest. They earned $1m (£600,000) in beating out 40,000 other teams from 186 countries to improve upon Netflix's Cinematch system for predicting which movies customers will like or dislike.
Netflix shared data with researchers for that contest too, and despite its efforts to do so without compromising customer privacy, researchers did find that piecing together identities from something as seemingly innocuous as movie preferences wasn't as difficult as first thought. Ohm argues that disclosing data such as gender, ZIP codes and ages makes people much too easy to identify.
Netflix says in its blog that Netflix Prize 2 "will focus more on helping customers early in their experience with Netflix, drawing on many more sources of data to try to find just the right movies."
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