Plus, ML will allow us to classify and optimize at scale, and be better at it than humans potentially, but opaquely... Humans hire from alumni network, have gender/race biases in hiring and are credentialist. What is ML going to weed out? Don't even know where to begin to look.+
But you don't know which of the million outputs matter, how, and if they group and correspond to latent variables that you don't even know to look for because it's not an input by itself. The construct ML is using may not even yet exist in human understanding but be predictive.
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For the winning algorithm in Netflix Prize where they did exactly what you said, it seems the authors were able to explain how it works.
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