this post was submitted on 27 Feb 2024
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I would be curious what this would predict for trans (including those both on and off hormone therapy), intersex, or homosexual individuals. My guess is that at a minimum in those cases it's accuracy of predicting either their gender or sex would be very poor, although it would be absolutely fascinating if it accurately predicted their gender rather than their sex. The opposite result (predicting sex but not gender) would also be interesting but less so.
I'd be very interested in those results too, though I'd want everyone to bear in mind the possibility that the brain could have many different "masculine" and "feminine" attributes that could be present in all sorts of mixtures when you range afield from whatever statistical clusterings there might be. I wouldn't want to see a situation where a transgender person is denied care because an AI "read" them as cisgender.
In another comment in this thread I mentioned how men and women have different average heights, that would be a good analogy. There are short men and tall women, so you shouldn't rely on just that.
I don't think that's a fair comparison. Height is a single value. If you trained an AI on that, it would be guessing. A brain has many, many more parameters to take into consideration when going into an artificial neural network.
That just makes my point stronger, though. The basic gist of what I was saying is that even if there is a statistical clustering of data into two groups that seem correlated with some category, that doesn't mean that you can absolutely rely on that data to classify people into those categories.
The more data you have, the more confident you can be that the resulting categorisation is correct. If you're saying this is incorrect, I disagree with you. If you're saying absolute confidence that the categories themselves are correct is impossible, then I agree with you