Cannot even reverse/engineer debug. I think a better grouping is that ML is opaque like humans, but as humans we have some insight into human foibles. Traditional databases (or programs) are like bureaucratic rules: they can be a maze, but you can potentially figure them out. 1/2
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We use ML because it can do things that we can not hand-code by writing rules or instructions. It's exactly because it's so different that it is so powerful and useful, and spread so widely in just a few years (once it had data to eat).
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One can also write a supra program that looks at results and tags, and reports anomalies, or things society deems are biases. Frequently, the problem with ML may be the mirror it holds up to us.
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It should be possible to get
#machineLearning models that are as explainable as human beings can explain themselves to others. Maybe not more than that, but at least that should be possible. But it will be a lot of work.Thanks. Twitter will use this to make your timeline better. UndoUndo
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