469: Learning Deep Learning Together

This book provides a detailed analysis of causality, transforming it from a nebulous concept into a mathematical theory. It applies to various fields such as statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents simple mathematical tools for studying causal connections and statistical associations, making it a valuable resource for students and professionals in multiple disciplines. The book has led to a paradigmatic change in how causality is treated in several scientific fields and has been cited in over 5,000 scientific publications.

In 'The Book of Why', Judea Pearl and Dana Mackenzie delve into the causal revolution, which has transformed the way we distinguish between correlation and causation. The book introduces causal diagrams, such as Directed Acyclic Graphs (DAGs), and explains how to predict the effects of interventions. It addresses fundamental questions about causality and its implications in fields like medicine, economics, and artificial intelligence. The authors also discuss the potential of causal inference in enabling computers to understand counterfactuals and engage in moral decision-making.