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The garbage in garbage out cascading failure generally seems to crash pretty fast. Given the U.S. is a capitalistic society the companies / institutions that do this and don't achieve their goals through data science should be apparent and then fail accordingly.

Am I missing something here?

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The trail of devastation left by this process, in financial and human terms, when medical systems go awry or vendors to state judicial systems wrongly convict innocent people.

I agree about your latter example, but about your first example: isn't it the case that these faulty AI systems for medical diagnosis have been rejected? Doctors don't like them because they don't want to be replaced or one-upped, and because they just don't trust them (rightly so, as it turns out). So the systems, which were put out for use on a trial basis, don't get used.

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