ETHICAL IMPLICATIONS OF AI IN DECISION-MAKING PROCESSES

Abstract

Artificial Intelligence (AI) is increasingly shaping decision-making processes across multiple domains, from criminal justice and healthcare to finance and employment. While AI promises efficiency and objectivity, it also presents profound ethical challenges. This study explores the key ethical implications of AI in decision-making, focusing on algorithmic bias, transparency, accountability, human oversight, and public trust. Through a qualitative analysis of academic literature, real-world case studies, and international ethical guidelines, the research highlights how AI systems can reinforce systemic inequalities, function opaquely, and erode human agency. The findings reveal a disconnect between the rapid advancement of AI technologies and the slower development of ethical and regulatory safeguards. The study concludes that embedding ethical principles into the design, deployment, and governance of AI is essential for ensuring fair and accountable decision-making. It calls for stronger regulatory frameworks, interdisciplinary collaboration, and transparent design to align AI systems with human values.