That was the question I asked when first hearing about the mobile app that ages you 30 years. The FaceApp went viral, and became even better known when some politicians proclaimed it unsafe because it was run by Russians.
It turns out FaceApp also allows users to make them look younger. It seems that the aged photos are more likely to be shared than the make-young photos. Why is that?
In my new 2-minute clip, I give an answer to this question.
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The issue raised in the clip is important for any machine-learning developer. Depending on your application, the errors made by the algorithm may be more or less visible to the users.
I discussed this aspect of decision-making in Chapter 4 of Numbers Rule Your World (link), the chapter about steroids testing. When the lab makes a false positive error, the falsely accused athlete will complain very loudly. When the lab commits a false negative, the cheating athlete will not make a sound. This creates a situation in which the lab's false-positive errors are highly visible while almost all false-negative errors are hidden from view.
It was/is generally believed that the athletes and the testing labs are playing a cat-and-mouse game. Given the above, is that really true?
For the sports stuff, you can read my book. For how this applies to FaceApp, play my video:
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