This is a good point, often missed or buried in the noise. It goes beyond recognition though (e.g. more general classification). Another area is when you have

This is a good point, often missed or buried in the noise. It goes beyond recognition though (e.g. more general classification). Another area is when you have fairly large sets with both breadth and depth, ML algorithms can sometimes pull out connections it is very difficult for analysts to even tackle. On a related note: I have no idea what Denmark is like for this, but I have seen other public sector analytics where the analysts themselves where good at what they did, but the whole system wasn’t very good at managing the data they consumed. This can introduce impressive delays and missed opportunities.