Fairness in Artificial Intelligence and Social Well-Being

This white paper discusses fairness in artificial intelligence (AI) and its implications for social well-being. It outlines the increasing reliance on AI decision support systems across various sectors, highlighting the potential negative impacts on individuals and society, especially in sensitive areas like criminal justice and healthcare. The paper details the introduction of bias in AI systems throughout their life cycle, from design to deployment, and emphasizes the importance of addressing these biases to avoid reputational damage and legal consequences. It presents various methods for evaluating and ensuring fairness in AI, categorizing them into pre-processing, in-processing, and post-processing techniques. The paper also identifies open issues and challenges in achieving fairness, such as the need for expertise in legal and ethical considerations and the difficulties in applying fairness methodologies across diverse cultural and legal contexts. Overall, it stresses the necessity for ongoing research and development in this critical area of AI.