The most surprisingly reasonable lawsuit ever [part1]

When I set out to write this post, it was going to be called "The dumbest lawsuit ever". After some The Netflix challenge was a million dollar prize for anyone how could get 10% better movie recommendations than the internal netflix algorithm. They released the dataset, with names and other personal details redacted. What had been expected to engage a few hundred acedemic researchers became a cultural landmark, engaging a huge following of practitioners. It spurred maturity in the field of recommendation engines and led to a widespread dissemination of recomendation engine practices. It was deemed unbeatable after the first few months, until two team of researchers paired up and combined their ensemble-learning approach to make a mega-ensemble approach, with over 100 models. Some time later, though, there was a lawsuit. The claimants showed that they could use public comments on IMDB to Doe v. Netflix (the plaintiff was initially identified as “Jane Doe” in press coverage and in privacy-law blogs). The suit was filed in the United States District Court for the Northern District of California in December 2009 and alleged violations of, among other things, the Video Privacy Protection Act (18 U.S.C. § 2710) and related privacy and fair-trade claims. part 1