The talk will give an overview of some of the existing approaches for visualizing recommendation mechanisms and eventually allowing users to control them. Starting with work from the area of open/scrutable learner models in the area of intelligent tutoring systems, through approaches for explaining recommendations to approaches visualizing aspects of collaborative, hybrid and social recommenders, as well as the filter bubble, the talk will be based both on the speakers' own work in this area and on a review of other work and will touch on some philosophical issues about how to evaluate recommendations.