Algorithmic Bias

Systematic and unfair discrimination in AI system outputs that arises from biases in training data, model design, or deployment context. Algorithmic bias can perpetuate or amplify existing social inequalities, for example when a hiring algorithm disadvantages certain demographic groups because historical hiring data reflected human prejudice. Identifying and mitigating it is a central concern in responsible AI development.
See also: automation bias, algorithmic accountability, AI ethics.