The limits of machine learning. I thought the new
"FacialGender" option for
Classifier would be an amusing thing to explore.
It turns out you can confuse the classifier just by changing your facial expression. (Poking out your tongue is apparently male behaviour, by the way.)
I was interested in knowing if the classifier was picking out the more obvious facial differences between the sexes – the ones we can all subconsciously pick in a fraction of a second – or whether it was being bamboozled by mere gender presentation. So I checked it on photos of Riley J Dennis, a transgender woman with a rather obvious Adam's apple who writes for Everyday Feminism, and Lea DeLaria, a self-described butch lesbian, known for playing Big Boo on Orange Is the New Black. The classifier coded Riley as female and Lea as male. While some might argue the point on the former, the latter is clearly incorrect. (Lest you think I'm making a political statement here, I also tried a photo of Jon Bon Jovi in his 1987 big-hair days – the classifier says female!)
The classifier gets Ellen De Generes right, but is confused by Samira Wiley: the photo on her Wikipedia page gets classified as female, but this picture of her playing Poussey Washington from Orange Is the New Black codes as male. Here is that result along with the one for DeLaria.
At this point it became clear that the classifier has not been appropriately calibrated to detect sex. Since this is a Q&A site, I better phrase this as a question:
Is there a way to improve built-in classifiers, especially this one, with further training and feedback where it gets it wrong?
And when people mistakenly call me "Sir", do I just need to smile?