Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are transforming the insurance industry by optimizing risk assessment, fraud detection, and customer service. However, the rapid adoption of these technologies raises significant ethical concerns, particularly regarding bias and fairness. This chapter explores the ethical challenges of using AI and ML in insurance risk management, focusing on bias mitigation and fairness enhancement strategies. By analyzing real-world case studies, regulatory frameworks, and technical methodologies, this chapter aims to provide a roadmap for developing ethical AI/ML systems in the insurance sector. It highlights the importance of transparency, accountability, and inclusivity in ensuring equitable outcomes.