This article introduces a book titled "Why?", written by Judea Pearl, a prominent figure in artificial intelligence. The book explores the concept of causality, arguing that it is a new science essential for true AI, which currently functions more as a database. The text highlights a historical scientific rejection of causality in favor of correlation, citing Francis Galton's "regression to the mean" experiment and Karl Pearson's work. Pearl posits that causality is a fundamental, subjective human thinking pattern that enables us to transcend direct experience, and he offers two methods to improve one's causal reasoning: identifying confounding factors and finding mediating factors, exemplified by the Simpson's Paradox and scurvy prevention, respectively.