Forget Privacy: You're Terrible at Targeting Anyway
Saved by Alex Dobrenko and
This is, by the way, the dirty secret of the machine learning movement: almost everything produced by ML could have been produced, more cheaply, using a very dumb heuristic you coded up by hand, because mostly the ML is trained by feeding it examples of what humans did while following a very dumb heuristic. There's no magic here. If you use ML to teach a computer how to sort through resumes, it will recommend you interview people with male, white-sounding names, because it turns out that's what your HR department already does. If you ask it what video a person like you wants to see next, it will recommend some political propaganda crap, because 50% of the time 90% of the people do watch that next, because they can't help themselves, and that's a pretty good success rate.
Saved by Alex Dobrenko and
IBM, for example, managed to fix the problem of poor gender identification that Joy Buolamwini discovered by building a new training set with more pictures of black women. Google solved its gorilla challenge in the opposite way: by removing pictures of gorillas from the training set. Neither solution is general; both are instead hacks, designed to
... See moreDeep learning is opaque.