"“A lot of these techniques are designed to always make a prediction,” Dr Allen said. “They never come back with 'I don't know' or 'I didn't discover anything' because they aren’t made to.” " I found this paragraph especially interesting.
risks of trusting ML too much in biomedicinehttps://www.ft.com/content/e7bc0fd2-3149-11e9-8744-e7016697f225 …
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Worse, those algorithms probably don’t even make predictions, what they are good at is, by their evaluation metrics, classifying past data into groups, or generating overfitted regression models without appearing to be so. See
@f2harrell’s discussion threads.
End of conversation
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but do you trust AI to give pockets to women? is the question on everyone's mind... cc
#pockethonThanks. Twitter will use this to make your timeline better. UndoUndo
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there are risks, but not trusting them. Come on.
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Thinking a stone (hardened earth) is ever capable of doing as intended regardless of inherent human error in image it is given to run is the result of tech industry tunnel vision focus on $$$$. Tech industry is genuinely incapable of holistic (sum) POV of their creation results.
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