AI AND ETHICS: INTERDISCIPLINARY PERSPECTIVES ON ALGORITHMIC TRANSPARENCY AND BIAS

Abstract

The rapid integration of Artificial Intelligence (AI) in socio-technical systems has amplified concerns regarding algorithmic bias and the lack of transparency in decision-making processes. This paper explores ethical dimensions of AI deployment, focusing on algorithmic accountability, interpretability, and fairness. By analyzing various interdisciplinary perspectives, we evaluate frameworks that support transparent AI and mitigate bias in automated systems. Real-world applications in healthcare, finance, criminal justice, and education are discussed, emphasizing the implications of unregulated AI systems. This study concludes with a call for actionable policy reforms and multi-stakeholder collaboration to ensure ethical AI adoption across domains.