Causality in Machine Learning

This chapter explores the multifaceted journey from gaming interest to a focus on statistical causality in machine learning. It discusses the historical perspective on causal inference, the cultural divide between traditional and causal modeling approaches, and the practical implications for AI. The importance of understanding causal relationships in improving model accuracy and addressing algorithmic fairness is emphasized through illustrative examples.