>to predict certain users like to listen to happy upbeat tracks on Fridays, and sad songs sung in Romance languages on Mondays. This is still entirely superfic

>to predict certain users like to listen to happy upbeat tracks on Fridays, and sad songs sung in Romance languages on Mondays. This is still entirely superficial. There's no recommender system that could even tell what a 'sad track' is other than by human labelling, or distinguish say, a satirically sad track from the genuine thing, or accurately tell what any individual even perceives as happy or sad which is highly subjective. It's not about metaphysics but about a very practical fact that these statistical systems fail at. Making genuinely novel human recommendations requires and understanding of human nature in general, individual nature of the person in question, and understanding of context and meaning. In short a system like this needs to be able to reason about what it is that it's recommending and who it's talking to. There is no system that could invent a game like Go because it has nothing to do with data in any direct sense. It'd require being able to reason about what makes games compelling and aesthetically pleasing to human beings and that's not a question of mapping one button click to another.