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When they list the fears they forgot an important one: discrimination.

Of course, discrimination has always been a problem but I'd like to believe we see some progress in "classical areas" (for instance sexism). The problem with AI is that it is always pigeonholing. As a result myriads of new classes of minorities which are so small that they neither have a name nor a voice will emerge. For instance, you get rated for creditworthiness and somehow you're not typical re: attributes x,y and z. You get a bad rating but you can't really complain as the algorithm probably didn't take things like sex or race (directly) into account. However, it could be that your FB posts are enjoying above-average amounts of likes from people with low education and this may raise red flags etc...



Imagine when AI undoes all positive discrimination, like for minorities, women etc. because it would try to optimize for results, i.e. bringing its own type of meritocracy, going after biggest gains without political affection (survival of the fittest/strongest).


How do you measure those results? Especially in fuzzy fields where they very much influenced by "political affection"




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