Recommender systems usually rely on behavioral similarity, but trust and delegation also structure how people share taste. This project introduces Liquid FM, a music recommender based on viscous democracy, where users vote for experts whose preferences propagate through the network. By turning recommendation into a collective decision process, it experiments with new forms of democratic influence and accountability in algorithmic systems.