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I wonder what it would return for "Woman is to doctor as man is to ___". I'd bet money on the result not being "nurse".
by organsnyder 6y ago
I wonder what it would return for "Woman is to doctor as man is to ___". I'd bet money on the result not being "nurse".
- sqrt17 6y agoIt highly depends on the corpus and you can check for yourself. I'm being lazy, but the results for Gutenberg books you can check online at http://labs.statsbiblioteket.dk/dsc/ http://labs.statsbiblioteket.dk/dsc/ - man is to woman as doctor is to reprovingly (nurse is the first noun, on position 4) - woman is to man as doctor is to snodgrass (after a couple nonsense/rare words) The most important thing that teaches us is that big corpora (bigger than PG) are essential for this method.
- mattkrause 6y agoYou can monkey around with it here: http://bionlp-www.utu.fi/wv_demo/ http://bionlp-www.utu.fi/wv_demo/ (choose the English Google News model, but this may not be exactly the same set/model as the original report). Man is to Woman as Doctor is to ___ gives 1) gynecologist 2) nurse 3) doctors 4) physician 5) pediatrician Woman is to Man as Doctor is to ___ gives: 1) physician 2) doctors 3) surgeon 4) dentist 5) cardiologist These are just generally near "Doctor" though: the ten nearest terms are physician, doctors, gynecologist, surgeon, dentist, pediatrician, pharmacist, neurologist, cardiologist, and nurse. Some gender differences may persist (nurse is #2 for `woman`, but #68 for `man`, but it's also near `woman` generally and you could imagine it gets a bit of a boost from the verb ("to feed a baby") being attached exclusively to women too. Anyway, my point is not that there's no bias (there certainly can be--seed GTP-3 with a prompt about Muslims) but that one should be wary of thinking they know what the model is doing.