The Ethics of Algorithmic Bias: Mitigating Discrimination in Automated Systems
When an artificial intelligence model makes a prediction, it is executing an automated judgment based on historical patterns. If those historical patterns reflect societal inequalities, structural racism, or uneven economic distribution, the AI does not fix these discrepancies; it codifies, accelerates, and legitimizes them under a veneer of mathematical objectivity. This phenomenon—algorithmic bias—has evolved from a theoretical ethical concern into an urgent socio-technical crisis. As machine learning algorithms automate critical infrastructure, from predicting criminal recidivism to allocating public housing and evaluating healthcare needs, the engineering community must treat bias mitigation not as an afterthought, but as a core mathematical requirement.…