Machine learning is not a concept that is fundamentally incompatible with interpretability, and indeed research is being done in this area. One method for exam

Machine learning is not a concept that is fundamentally incompatible with interpretability, and indeed research is being done in this area. One method for example is occlusion, removing pieces of input to assemble statistical representations of which parts your model cares about. It's all still baby steps, but with time the theory will catch up. > If you had something bigger you'd call it "artificial intelligence research" Usually called just Data Science, and does deal with that (we had lectures on interpratibility of models at university)