Our supervisory approach also focuses on ensuring that data are of the right quality. That was a point that elicited a unanimous response in the consultation, although good and meaningful data have always been a key factor in the success of models, whether ML or not. Procedures which process huge amounts of data do not alter this principle. Another key criterion is explainability.
ML is often referred to as a “black box”, an opaque system in which data are fed in at one end and results are produced at the other without us being able to understand how one relates to the other. In this sense, dinosaurs, too, are a black box that we cannot fully comprehend, never having seen them. Did they have fur or feathers?