Recommender Systems: Legal and Ethical Issues

This open access contributed volume examines the ethical and legal foundations of (future) policies on recommender systems and offers a transdisciplinary approach to tackle important issues related to their development, use and integration into online eco-systems. This volume scrutinizes the values driving automated recommendations - what is important for an individual receiving the recommendation, the company on which that platform was received, and society at large might diverge. The volume addresses concerns about manipulation of individuals and risks for personal autonomy. From a legal perspective, the volume offers a much-needed evaluation of regulatory needs and lawmakers' answers in various legal disciplines. The focus is on European Union measures of platform regulation, consumer protection and anti-discrimination law. The volume will be of particular interest to the community of legal scholars dealing with platform regulation and algorithmic decision making. By including specific use cases, the volume also exposes pitfalls associated with current models of regulation. Beyond the juxtaposition of purely ethical and legal perspectives, the volume contains truly interdisciplinary work on various aspects of recommender systems.

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 Ourselvesto 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.