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24 Yale J.L. & Tech. 227 (2022)
Is Spotify Bad for Democracy? Artificial Intelligence, Cultural Democracy, and Law

handle is hein.journals/yjolt24 and id is 227 raw text is: Is Spotify Bad for Democracy? Artificial Intelligence, Cultural Democracy, and Law Jonathan Gingericht Much scholarly attention has recently been devoted to ways in which artificial intelligence (AI) might weaken formal political democracy, but little attention has been devoted to the effect of AI on cultural democracy-that is, democratic control over the forms of life, aesthetic values, and conceptions of the good that circulate in a society. This work is the first to consider in detail the dangers that AI-driven cultural recommendations pose to cultural democracy. This Article argues that AI threatens to weaken cultural democracy by undermining individuals' direct and spontaneous engagement with a diverse range of cultural materials. It further contends that United States law, in its present form, is ill equipped to address these challenges, and suggests several strategies for better ? Lecturer in Philosophy of Law and Member, Yeoh Tiong Lay Centre for Politics, Philosophy & Law, The Dickson Poon School of Law, King's College London and Faculty Member, Center for Transnational Legal Studies, London. For helpful discussions related to the ideas in this Article, I am grateful to Emine Akar, Filip Bialy, Daire Boyle, Margit Cohn, Davina Cooper, Daniela Dover, Markus Furendal, David Gamez, Chelsea Guo, Melissa Hughs, Perry Keller, Orit Kopel, Ted Lectherman, Jacques Lezra, Dominic McIver Lopes, S.M. Love, C. Thi Nguyen, Lucy O'Brien, Roger O'Keefe, Charles Petersen, Massimo Renzo, Elaine Scarry, Nick Schwieterman, Robert Mark Simpson, John Skorupski, Walter Stoffel, Hannah Sutherland, John Tasioulas, Carlos M. Vizquez, Lorenzo Zucca, and audiences at the Dickson Poon School of Law Research Seminar, the CTLS Transnational Law Colloquium, and the MANCEPT Governing Al Workshop. I thank Daniela Dover, Charles Petersen, Nick Schwieterman, and John Tasioulas for conversations that provided the impetus for this Article and Daniela Dover and Massimo Renzo for extensive written comments on earlier drafts. I am especially grateful for excellent research assistance from Maximilian Priebe, Sabrina Stewart, and Katarzyna Wesolowska, each of whose contributions led to significant substantive improvements to this Article.

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