When a person recommends a restaurant, movie or book, he or she is usually thanked for this recommendation. The person receiving the information will then evaluate, based on his or her knowledge about the situation, whether to follow the recommendation. With the rise of AI-powered recommender systems, however, restaurants, movies, books, and other items relevant for many aspects of life are generally recommended by an algorithm rather than a person. This volume aims to shed light on the implications of this transnational development from both legal and ethical perspectives and to spark further interdisciplinary thinking about algorithmic recommender systems.