Getting into sort of pattern matching I think requires a certain optimism that things are "nice and symmetrical" after enough analysts. Of course, that can get

Getting into sort of pattern matching I think requires a certain optimism that things are "nice and symmetrical" after enough analysts. Of course, that can get us into trouble with e.g. "supersymmetry in physics", but usually I think that optimsim is a feature not a bug and necessary in any case. I think instilling this optomism in students --- following their curiosity won't lead deeper in a bottomless pit, if something doesn't make sense it's might be them but a lack of information, etc. --- is the essentially hard part, and requires undoing a lot alienation people experience. Conversely, I think messing around with block boxes like machine learning we don't understand is giving into the alienation. (Studying it to understand it rather than do things is fine.) I worry more use of machine learning like things will be a another nail in liberalism's coffin as do the equivalent of regressing back to alchemy from chemistry. Now, looking for patterns is what machine learning does, but while Rorschach-test-style grappling in the dark might be the basal "reptiling" instinct that lead to more high level theory-based pattern renegotiation, they should not be conflated.