ETHICAL AI IN INFORMATION SYSTEMS: A CROSSDISCIPLINARY EXAMINATION OF BIAS AND FAIRNESS

Abstract

The rapid integration of Artificial Intelligence (AI) in information systems has raised concerns regarding the ethical implications of its deployment, particularly with respect to bias and fairness. This study aims to explore the ethical challenges posed by AI systems in various domains and investigates the interplay between algorithmic fairness and biases. The increasing use of AI in sensitive areas like hiring, healthcare, and law enforcement necessitates a critical examination of the extent to which these systems may inadvertently perpetuate societal biases. We adopt a cross-disciplinary approach, combining insights from computer science, ethics, and social sciences, to provide a comprehensive understanding of how biases manifest in AI algorithms and the steps necessary to ensure fairness in their design and implementation. By synthesizing relevant research and case studies, this paper provides valuable recommendations for policymakers and practitioners working to develop more ethical AI systems