Explore the concept of explainability in AI and its implications for individual justice in this thought-provoking lecture by Dr. Reuben Binns. Delve into the challenges of using large datasets to make statistical inferences about individuals and the limitations this presents for explaining and justifying data-driven decisions. Examine the tension between general justice and individual justice in machine learning applications, and consider how language plays a crucial role in negotiating these complex issues. Gain insights into the evolution of decision-making systems, from rules-based approaches to expert systems and modern machine learning algorithms, and understand their impact on discretion and automation in various contexts.