The Difference Between Causation and Correlation in Machine Learning

In a machine learning approach, you just put in all these indicators into a model. With economists, what we like to do is really like to build really structural models. So with the structural model, essentially, I can make inflation go down by 2% and this is a counterfactual environment. If I use a black box model, and inflation goes down by 2%, this is a correlator. It doesn't work as well as I'm making it sound, but that's what the attempt is.