LEADER 04469nam 22005775 450 001 9910735996703321 005 20251008152048.0 010 $a3-031-34804-4 024 7 $a10.1007/978-3-031-34804-4 035 $a(CKB)5700000000425935 035 $a(MiAaPQ)EBC30674572 035 $a(Au-PeEL)EBL30674572 035 $a(DE-He213)978-3-031-34804-4 035 $a(OCoLC)1396698110 035 $a(ODN)ODN0010055128 035 $a(EXLCZ)995700000000425935 100 $a20230803d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aRecommender Systems: Legal and Ethical Issues /$fedited by Sergio Genovesi, Katharina Kaesling, Scott Robbins 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (220 pages) 225 1 $aThe International Library of Ethics, Law and Technology,$x1875-0036 ;$v40 311 08$a3-031-34803-6 327 $aChapter 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. 330 $aThis open access contributed volume examines the ethical and legal foundations of (future) policies on recommender systems and offers a transdisciplinary approach to tackle important issues related to their development, use and integration into online eco-systems. This volume scrutinizes the values driving automated recommendations - what is important for an individual receiving the recommendation, the company on which that platform was received, and society at large might diverge. The volume addresses concerns about manipulation of individuals and risks for personal autonomy. From a legal perspective, the volume offers a much-needed evaluation of regulatory needs and lawmakers? answers in various legal disciplines. The focus is on European Union measures of platform regulation, consumer protection and anti-discrimination law. The volume will be of particular interest to the community of legal scholars dealing with platform regulation and algorithmic decision making. By including specific use cases, the volume also exposes pitfalls associated with current models of regulation. Beyond the juxtaposition of purely ethical and legal perspectives, the volume contains truly interdisciplinary work on various aspects of recommender systems. . 410 0$aThe International Library of Ethics, Law and Technology,$x1875-0036 ;$v40 606 $aTechnology$xMoral and ethical aspects 606 $aArtificial intelligence 606 $aEthics of Technology 606 $aArtificial Intelligence 615 0$aTechnology$xMoral and ethical aspects. 615 0$aArtificial intelligence. 615 14$aEthics of Technology. 615 24$aArtificial Intelligence. 676 $a174.96 686 $aPHI005000$2bisacsh 700 $aGenovesi$b Sergio$0804681 701 $aKaesling$b Katharina$01424183 701 $aRobbins$b Scott$01075840 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910735996703321 996 $aRecommender Systems$93553202 997 $aUNINA