I want to agree with this; but a little knowledge of stats can be worse than none. (Whereas trig is just a painful waste of time.) Can the intro course explain its own limits, and the dangers of misuse?https://twitter.com/jessesingal/status/951282864498372608 …
Confidence in a belief must equal the weight of the evidence for that belief. This leads to understanding that information is epistemologically primary; to produce an observation means to create a change in information, and all observable changes can be produced by computation.
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When Dreyfus said "what computers cannot do", I thought he could not be talking about some hitherto unknown metaphysical truth of the noumenon, but must have been talking about what the classes of algorithms and models currently being used fall short of doing. And it made sense.
Thanks. Twitter will use this to make your timeline better. UndoUndo
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Yes, I realize that it probably needs to be filled with a book. A number of books on the other side of the inferential chasm that separates us computationalists from you inhabitants of weird hypercomputational and metacomputational universes exist, but there needs to be a bridge.
End of conversation
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