Why Causal Machine Learning is the Next Revolution in AI

Editor's note: Robert Ness is a speaker for ODSC East 2021. Check out his talk, "Causal Machine Learning Blitz," there! Causal modeling and inference are perhaps at the core of the most interesting questions in data science. A common task for a data scientist at a FAANG is to query users who had exposure to a feature and calculate the correlation between usage of that feature and engagement on the platform. However, the data scientist does not care about that correlation; they care about whether that correlation indicates that the feature drives engagement.