Bridging the Gender Data Gap in AI

One core issue at the heart of AI bias against women is the gender data gap. Historically, data has often been collected from male-centric perspectives, leading to algorithms that fail to accurately predict or understand female needs and behaviours. To remedy this, researchers and developers must prioritize the collection and incorporation of female-focused data and scrutinize existing data sets for gender biases.

One core issue at the heart of AI bias against women is the gender data gap. Historically, data has often been collected from male-centric perspectives, leading to algorithms that fail to accurately predict or understand female needs and behaviours. To remedy this, researchers and developers must prioritize the collection and incorporation of female-focused data and scrutinize existing data sets for gender biases.

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Fairness in AI Algorithms

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