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Interestingly, lots of children, at least until recently, learned implicitly that nurses are female.
Children learn by example. My mom is an engineer (and also my dad). So as a child, I never thought of engineering as a man's profession. It had a profound impact. I don't know if I would have pursued STEM without that encouragement and role models in formative years
So much depends on the statistical distribution of the examples in your environment. One of the most important functions in parenting, I think, is structuring the environment of your children more than explicit teaching.
Coincidentally a few hours ago I twitted that ML bias needs to be fix primarily by fixing the society. Even if you fix your model somewhat you cannot fix humans who learned that nurse has to be a female.
Sobering to think that AI could easily have missed out on @AnimaAnandkumar
Glad it didn't.
Very true.
Doesn't AI also learn by examples? Can we do the same with ML/AI, provide it with role-'models' so that historical steriotypical biases don't plague it? Or deliberately training by switching off features/nodes which correlate highly with these biases
Learning is part of the answer to reducing perpetuation of historical bias. But our argument in http://rebooting.ai is that the bias issue won't be well addressed until we invent a new generation of AI that has richer conceptual representations of the world & our values.
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