could you explain a little more about the lawsuit ? I don't understand why they'd have to stop using their recommendation system.
It might be surprising given how lax the US seems to be about privacy in general, but video rental records are protected differently from some other data because of the failed Supreme Court nominee Robert Bork (failed in part because reporters were able to get his video rental records whichI think show he had rented porn, but I don't remember all the details). As a result of the Bork situation, federal law was passed to protect video rental records. Facebook had to settle a thing with the FTC over something similar with its Beacon program.
Netflix wound up canceling the follow-up contest because of the class-action lawsuit. IIRC, a few years later they wound up settling a different lawsuit also related to the FTC stuff, but that wasn't tied to the algorithm or potentially "outing" anyone.
I recommend reading The Bork Tapes Saga when you get a chance: https://web.archive.org/web/20071009144531/http://www.theame...
The Video Privacy Protection Act should be expanded to include all PII.
if is_netflix_show() { return 0.95 + rand(0.00, 0.05) } else { hide_rating() }
I have to think that the real problem is that the things Netflix wanted to start to optimize for different things rather than recommendation accuracy. They have new metrics like watch time, time engaged with the app (binge watching), watch to completion, rewatch time, watch first weekend, etc. I don't think they care about offering the best recommendations anymore, just about doing whatever they can to keep you tuned into the app as long as possible. Those two things aren't necessarily at odds, but they aren't the same thing either.
Like, today Netflix is going to want to optimize for getting the most eyeballs on its originals versus content they've merely licensed from the catalog. When it was offering DVD rentals, it didn't have original content so having good recommendations was the sort of thing that would keep the service "sticky" and prevent subscriber churn.
Netflix' key metrics are basically around retaining subscribers and attracting new ones. Except to the degree it supports those goals (and there's obviously a correlation), they don't actually care how much you watch, how much you like the content, how easily you find content you like, etc. Correlated, yes. But not one and the same.
It's the opposite. The primary cause of churn is that there is nothing a subscriber wants to watch. You might assume that a recommendation helps a user maximise the amount of the library they will watch but it actually helps the user conclude there is nothing they want to watch and leave.
Netflix wants their library to be more like a one-armed bandit. Users have to gamble on whether they will like something and they will never know they have run out. They want the user to keep hanging on, to keep scrolling, assuming something great is just around the corner, never getting to "I'm done with this".
I noticed this effect with the DVD subscription. If you added 3 discs to your queue, they would send the first two but not the third, waiting for you to add some less desirable titles to your queue, which they would send before they sent your high priority title. If your needs get satisfied, your subscription ends. It's a fundamentally user hostile business.
People naturally respond to such things and use them to segue into another topic as part of conversation, and sometimes it is nice to have someone tell their recollection of a story instead of getting the wikipedia version.
I encourage you to stop doing this.
If you wouldn't mind reviewing https://news.ycombinator.com/newsguidelines.html and taking the intended spirit of the site more to heart, we'd be grateful.