Judea Pearl: Causal Reasoning, Counterfactuals, and the Path to AGI | Lex Fridman Podcast #56

Turing Award winner Judea Pearl argues that artificial intelligence must evolve from statistical correlation to causal reasoning to achieve true intelligence, introducing the "do-calculus" to mathematically distinguish between observation and intervention. His framework utilizes causal graphs and counterfactuals to enable machines to understand responsibility, ethics, and self-modeling, thereby addressing the limitations of current deep learning systems. Pearl envisions a future where AI integrates human-provided qualitative models with quantitative data to solve complex problems, while warning of the existential risks posed by creating autonomous systems that could surpass human control.