Meet the people who design the algorithms that capture our musical tastes.
 
The people who make music recommender systems have lofty goals: they want to broaden listeners’ horizons and help obscure musicians find audiences, taking advantage of the enormous catalogs offered by companies like Spotify, Apple Music, and Pandora. But for their critics, recommender systems seem to embody all the potential harms of algorithms: they flatten culture into numbers, they normalize ever-broadening data collection, and they profile their users for commercial ends. Drawing on years of ethnographic fieldwork, anthropologist Nick Seaver describes how the makers of music recommendation navigate these tensions: how product managers understand their relationship with the users they want to help and to capture; how scientists conceive of listening itself as a kind of data processing; and how engineers imagine the geography of the world of music as a space they care for and control.
 
Computing Taste rehumanizes the algorithmic systems that shape our world, drawing attention to the people who build and maintain them. In this vividly theorized book, Seaver brings the thinking of programmers into conversation with the discipline of anthropology, opening up the cultural world of computation in a wide-ranging exploration that travels from cosmology to calculation, myth to machine learning, and captivation to care.

"Artists and music journalists have been coining genres for decades, based on sounds shared between artists. This new era for genre is derived from listener data and labelled by engineers who, Seaver says, never expected to become authorities on the matter. This speaks to the contradiction at the heart of Computing Taste: it’s both easier and harder to pinpoint a person’s music taste than you might expect. It all depends on what you think taste is. Spotify can tell us how many times we loop a favorite song, make reasonable assumptions about the genres that speak to us, and deduce from GPS data what we might want to hear in the gym as opposed to the office. But Seaver stresses that a key anthropological question remains unwrapped: why do people love the songs that they do?" - Guardian

"Recommendations now 'drive close to half of all users’ streams', according to Spotify’s co-president Gustav Söderström. In Computing Taste, an ethnography of the data scientists and product managers working in 'the world of music recommendation', Seaver gives an account of the way this sort of technology operates. The job of his interviewees, who tend to work for private companies hired by streaming services, is to help their clients 'answer an apparently simple question: what’s next?'" - London Review of Books

"The central premise uniting these theories is that we can’t really tell an algorithm who we are; we have to show it. Platforms used to offer recommendations based on clear user inputs (consider that Netflix used to ask you to rate a movie out of five stars); now things have gotten murkier as our behavior is tracked and collated in complex, opaque ways. Consumers have learned to adjust their actions to get the content they want, according to Nick Seaver, an anthropology professor at Tufts University and the author of Computing Taste: Algorithms and the Makers of Music Recommendation. 'You were much more in control of how you represented yourself under those [earlier] systems,' Seaver told me. Now our behavior—even the embarrassing kind—generates our unique media world." - Atlantic

"A useful deep dive into precisely how these systems are built, the people who build them, their goals and aspirations, and much more." - Arts Fuse

"Computing Taste: Algorithms and the Makers of Music Recommendation is a pleasure to read. It is well-written, with nice turns of phrase. I commend it to anyone interested in how media works in the 21st century." - Metascience

"Streaming music services are the norm today, but people don't often think about how they work or how they recommend the next song. Seaver peeks behind the musical curtain in this book about the humans behind the algorithms. . . . Music lovers and those who like books about artificial intelligence will enjoy Seaver's deep dive into the culture, data, and science of music recommendation systems. Computing Taste offers insight into algorithmic music recommendations that's entertaining and easily digestible." - Library Journal

"I would recommend this book if you identify with the following phrase, which is taken from Seaver’s interview with one music company engineer: ‘I’m plagued by the idea that there’s something I haven’t heard yet.’ Music nerds will especially appreciate that Seaver proposes definitions for topics that are hard to describe, like taste and genre. They will enjoy identifying their habits in Chapter 3, ‘What are Listeners Like?’ and learning how music engineers define obscure subgenres like ‘shiver pop.’ . . . The peeks into these veiled companies are almost reminiscent of spy novels. If you’re interested in start-up culture and liked The Social Network, there’s something for you in this book. Throughout Computing Taste, Seaver comments on the balancing act between artificial intelligence and human expertise. He says the title ‘is meant to index that tension’—to probe how technological systems can coexist with something as personal as music taste." - Daily Cardinal

"The gap between technology and culture might not be as wide as we think, says Seaver in his analysis of how music recommender systems are produced. . . . You’ll come away from Computing Taste realizing that algorithms aren’t the enemy, ready to think again.“ - Engineering and Technology