Balancing Ethics in AI: Overcoming Bias, Enhancing Transparency, and Ensuring Accountability

Abstract

As artificial intelligence (AI) becomes integral to decision-making processes, ethical concerns surrounding bias, transparency, and accountability have emerged. These issues not only affect the fairness and reliability of AI systems but also raise fundamental questions about the role of AI in society. This paper explores the sources of bias in AI models, the importance of transparency for trust and accountability, and the mechanisms through which accountability can be ensured in AI-driven decisions. Furthermore, the paper discusses the concept of trustworthy AI, offering strategies to foster trust in AI systems. By reviewing case studies, current research, and policy recommendations, this paper provides a comprehensive analysis of how to mitigate bias, enhance transparency, improve accountability, and build trustworthy AI systems.