Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification

What it is

Tested three commercial face-classification products and found error rates of up to 34.7% for darker-skinned women against 0.8% for lighter-skinned men. The study that turned algorithmic bias from a theory into a measured, published fact. Free to read in full.

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