[ColanR]

I agree with your first paragraph. However, a NN can't explain its reasoning. You start with a set of symptoms, and you end with a vector, and they're two representations of exactly the same thing. The problem is that NNs are representational, not explanatory, so they won't help a doctor get to a root cause any more than just thinking about the collection of symptoms and what they're associated with.

[dooglius]

I think what's implicit in the comment is that the output vector can correspond to things like dosages of drugs or recommended therapeutic treatments.

[deathgrips]

I'm not sure why but I wouldn't feel comfortable letting some tech bros decide what drugs people should take.

[9HZZRfNlpR]

Psychiatry works as a trial and error of different drugs so it wouldn't be far too off.

[ColanR]

Yeah, but at least a malpracticing psychiatrist can lose their license.

[ColanR]

Yes: but what was implicit in mine is that that output vector is no more or less informative than the current method of associating strong symptoms with specific diagnoses which have known drug dosages. Same idea, different representation.

The difference is whether the process can be automated, and that is where the problem of the black box comes in. With the current system, we know why the drug was prescribed. With an ML system, we would have no clue.