Algorithmic Bias and Moral Responsibility: Ethical Challenges in AI-Driven Decision Systems

Abstract

Artificial Intelligence (AI) has become integral to modern decision-making systems, influencing areas such as healthcare, finance, criminal justice, and employment. However, the emergence of algorithmic bias — systematic and unfair discrimination resulting from biased data, flawed modeling, or human oversight — raises significant ethical challenges. This paper investigates the intersection of algorithmic bias and moral responsibility in AI-driven decision systems, exploring how developers, organizations, and policymakers can uphold ethical integrity while leveraging AI’s transformative potential. By analyzing real-world case studies, the paper identifies frameworks for ensuring fairness, transparency, and accountability in automated decision-making.