ALGORITHMIC BIAS AND DISCRIMINATION
INTRODUCTION Algorithmic systems increasingly influence decisions in employment, finance, healthcare, criminal justice, and beyond. These systems were designed to capture the knowledge and thought processes of legal experts and provide automated decision-making tools. While they promise efficiency and impartiality, their reliance on historical data and the biases embedded within these datasets often result in discriminatory outcomes. For instance, facial recognition technology has been criticized for higher error rates when identifying individuals of certain ethnic groups, and predictive policing algorithms may disproportionately target minority communities. The rapid integration of artificial intelligence (AI) and machine learning into decision-making processes has revolutionized industries. However, these systems are not immune to bias and discrimination, which can have significant social and legal implications. The integration of Artificial Intelligence into the legal system has...