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An argument for how understanding causality has revolutionized science and will revolutionize artificial intelligence. Illuminating. -New York Times Extraordinary. -Science Friday Correlation is not causation. This mantra, chanted by scientists for more than a century, once led to a virtual prohibition on causal talk. Today, with causal analysis taking center stage in AI and other applications, the old taboos are a thing of the past.The causal revolution, instigated by Judea Pearl and others, established causality on a firm scientific basis. Pearl showed how intuitive models can interface with data to help answer causal questions, such as whether a drug will cure an illness or, counterfactually, whether an illness would have persisted absent the drug. These models provide a blueprint for causal AI to learn and take responsibility for its mistakes.Updated with a new preface and summary of recent advances, The Book of Why outlines the basics of cause and effect for lay readers and...

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