> This won't ever take off once the media finds that the machine learning is biased towards some specific sex or race (particularly if such demographics are normative historically for the country at large).

I'm not sure I understand. If it is discovered, or "found" (by the media, I guess), that "these systems" are biased, I suppose that should result in them, being fixed, even at the expense of them "tak[ing] off." In your view, is that a good thing or a bad thing? Is it better or worse that "the media" find it? Also, by "normative historically," did you mean "representative?" In other words, do you mean a mathematical norm, as in an average? Or an ethical norm, as in a rule? (Hetero-normative, normative ethics, and so on.) Surely we're not talking about "correct biases?" It's just that my impression is that the language of "normative" in this context, a context which reads as sociological, is most often associated with societal, cultural, or ethical "norms," which are things that are viewed as correct in an "ought" sense.

> Just look at the contentions of prison reform automated systems and the like.

Can you elaborate? Because I think very few of us have looked at these examples. Which "prison reform automated systems and the like" have failed to "take off" due to a discovery of bias by "the media?"

Sorry for all the scare quotes. I'm just trying to piece it together and am having no luck.