Computing Taste: Algorithms and the Makers of Music Recommendation

The people who design music recommender systems have lofty goals but face criticism for flattening culture, normalizing data collection, and profiling users for commercial ends. Computing Taste rehumanizes these algorithmic systems by bringing the thinking of programmers into conversation with anthropology, exploring the cultural world of computation and its implications for society.

Format: Paperback / softback
Length: 224 pages
Publication date: 06 December 2022
Publisher: The University of Chicago Press

Meet the individuals behind the algorithms that shape our musical preferences! These individuals have ambitious aspirations: they aim to broaden our musical horizons and assist lesser-known musicians in gaining exposure, leveraging the vast music catalogs provided by companies like Spotify, Apple Music, and Pandora. However, their critics argue that these recommender systems embody all the potential drawbacks of algorithms. They argue that they flatten culture into numerical representations, normalize the extensive collection of data, and exploit users for commercial purposes.

Drawing on extensive ethnographic fieldwork, anthropologist Nick Seaver delves into the complexities of creating music recommendation systems. He explores how product managers understand their relationship with the users they aim to assist and capture. He also examines how scientists perceive listening as a form of data processing and how engineers envision the world of music as a space they nurture and control.

Compute Taste rehumanizes the algorithmic systems that dominate our world, bringing attention to the individuals who build and maintain them. In this thought-provoking book, Seaver brings the perspectives of programmers into dialogue with the discipline of anthropology, offering a comprehensive exploration that spans from cosmology to calculation, myth to machine learning, and captivation to care.

Dimension: 229 x 152 x 15 (mm)
ISBN-13: 9780226822976
Edition number: 1