IBM hopes to fight bias in facial recognition with new diverse dataset

Bias is a big problem in facial recognition, with studies showing that commercial systems are more accurate if you're white and male. Part of the reason for this is a lack of diversity in the training data, with people of color appearing less frequently than their peers. IBM is one of the companies trying to combat this problem, and today announced two new public datasets that anyone can use to train facial recognition systems — one of which has been curated specifically to help remove bias.

The first dataset contains 1 million images and will help train systems that can spot specific attributes, like hair color, eye color, and facial hair. Each face is annotated with these characteristics, making it easier for programmers to hone their...

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