AI bias occurs when models produce unfair or discriminatory results due to biased training data, flawed assumptions, or inadequate representation. This can affect hiring tools, loan approvals, content moderation, and more. Mitigating bias requires diverse training data, careful evaluation, bias auditing, and inclusive development teams.
AI Bias
Systematic errors in AI outputs that reflect prejudices present in training data or model design.
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