Data discrimination encompasses biases embedded within algorithms and data sets that can negatively affect women online. These biases may come from historical data patterns or subjective human inputs during algorithm development. To address this, a multifaceted approach including auditing algorithms for gender biases, diversifying development teams, and implementing more inclusive data collection practices is necessary.
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