Seeing Like an Infrastructure: Avidity and Difference in Algorithmic RecommendationHow do the developers of music recommender systems think about the diversity of their teams, the differences between themselves and their users, and their technical consequences? This article, in a special issue of Cultural Studies edited by Blake Hallinan and James N. Gilmore, descibes how developers were generally reluctant to recognize demographic categories as technically meaningful. Instead, they came to understand the difference between themselves and their users primarily in terms of music enthusiasm, or avidity.