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Fair for all
Google DeepMind: The Podcast
Women Also Snow Board
Image classifiers were shown images of people snow boarding, they were much more likely to label the person as il. When you trained models on thi data, it magnified an id this bias. And so whereas at train time, maybe you had a skew of 70, 30, men, women snow boarding, now at test time you have 90, ten. Once they recognized the image classifi as were biased, lisa anne and her colleagues shifted the garithm to focus on the subject of the photograph rather than their surroundings.
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