Truly Explainable AI: Putting the “Cause” in “Because”

Most powerful machine learning models are too complicated for anyone to comprehend or explain, and “overfit” to the past in complex, dynamic environments. Causal AI solves both problems, building models that are highly accurate and inherently explainable.

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This paper sets out how Causal AI puts the “cause” in “because”, and explores the value of truly explainable AI.