It isn't wrong to assume that strongest human are men, but I would argue it is not right to assume a professor is a man, Nobel Laureate is a man, nurse is a woman and so forth.
I don't think it is very high in the list of priorities, but I have no problem in making sure that those biases are not present in the ChatGPT output. This is not suppression of facts. The article is not talking about suppressing phrasing that right now you are more likely be a man if you have a Nobel prize, but it is talking about not assuming that you must be a man if you have a Nobel prize.
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I absolutely agree. Probabilistic statements are fine and useful. Assumptions X equals Y in speech probably not.
How to exactly address this is not quite clear, that's why I thought the article was quite interesting.
(and obviously fixing the labelling of professor = man in text generation is actually much less useful for gender equality say than dealing with actual issues that lead to the P(X|category1)!=P(X|category2))
This is borderline tyrannical and unreasonable. "Biases" can range from institutional discrimination to acceptable assumptions to literal facts. For example it isn't wrong to assume the strongest humans are men and the oldest people are women. But those are by definition "biases". Suppressing these are just outright denial of facts.
These "equality" pushes are getting dumb and dumber.