Chapter 1: Introduction: Understanding and Regulating Al-Powered Recommender systems
Part I: Fairness and Transparency
Chapter 2: Recommender Systems and Discrimination
Chapter 3: From Algoritmic Transparency to Algorithmic Choice: European Perspectives on Recommender Systems and Platform Regulation
Chapter 4: Black Hole instead of Black Box? - The Double Opaqueness of Recommender Systems on Gaming Platforms and its Legal Implications
Chapter 5: Digital Labor as a Structural Fairness Issue in Recommender Systems
Part II: Manipulation and Personal Autonomy
Chapter 6: Recommender Systems, Manipulation and Private Autonomy - How European civil law regulates and should regulate recommender systems for the benefit of private autonomy
Chapter 7: Reasoning with Recommender Systems? Practical Reasoning, Digital Nudging, and Autonomy
Chapter 8: Recommending Ourselves to Death: values in the age of algorithms
Part III: Designing and Evaluating Recommender Systems
Chapter 9: Ethical and Legal Analysis of Machine Learning Based Systems: A Scenario Analysis of a Food Recommender System
Chapter 10: Factors influencing trust and use of recommendation AI: A case study of diet improvement AI in Japan
Chapter 11: Ethics of E-Learning Recommender Systems: Epistemic Positioning and Ideological Orientation.