The best recommendations I get on Spotify are usually via their users that listened to artist X, also listened to artist Y type recommendations. That combined with their list of most popular tracks per artist gives me a rich source of new things to listen to. Their regular recommendations aren't great; it falls into the same "more of the same shit" trap that most other recommendation systems fall into.

The reason this simple mechanism works so well is that it gets rid of personal biases and instead taps into a community of listeners listening to the same stuff. Confirmation bias is the core issue here. I don't want confirmation bias. I want my biases challenged with new things. Not randomly new but based on what others are listening to that listen to similar things. And not just randomly based on everything I listen to but on specific things that I'm playing.

Vector similarity of artists could be an interesting angle. But it would probably risk pulling out a lot of cover bands and imitators. You want stuff that is close but not too close.