Algorithmic Bias and the Law: Ensuring Fairness in Automated Decision-Making

Algorithmic decision-making systems have become pervasive across critical domains including employment, housing, healthcare, and criminal justice. While these systems promise enhanced efficiency and objectivity, they increasingly demonstrate patterns of discrimination that perpetuate and amplify existing societal biases. This paper examines the evolving legal landscape governing algorithmic bias, analyzing recent regulatory developments, landmark litigation, and emerging compliance frameworks. T