For years, I’ve been waiting for a researcher to explain how music platforms compile personalized recommendations — like Spotify’s Discover Weekly, which has helped me find some of my favorite tracks.
A few months ago, I came across Nick Seaver on Twitter, who was writing “Computing Taste: Algorithms and the Makers of Music Recommendation,” a book about those algorithmic systems and the people who make them.
While the book isn’t completely what I expected — it incorporates lots of high-level anthropological and technological theory — it still grew my appreciation for music discovery.
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.”
This deep interest in music discovery is necessary to follow Seaver through his literature reviews. Readers who are at the top of the “listener pyramid” — whose “whole identity is wrapped up in music” — will stick through these denser sections.
Computer science majors will also enjoy this book and probably gain a greater understanding of algorithms than myself. Still, as someone with minimal experience studying artificial intelligence, I found these sections approachable and educational.
What sets this book apart from others in the artificial intelligence field is Seaver’s anthropological approach. As he reiterates, he is studying the humans behind these systems and how they think about their work.
“The thinking of the makers of music recommendation matters because, as they note, there is no such thing as an unaccompanied algorithm,” Seaver writes.
Periodically, readers are given glimpses of a notoriously secretive industry — though the main insights come from a company anonymized as “Whisper.” Seaver spent multiple years gaining “access” to these music platforms by interning, waiting around in lobbies, attending industry conferences and hounding down employees.
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.
Seaver is gifted at placing something as niche as music recommendation within larger sociologic frameworks. Readers who are truly passionate about music will appreciate how Seaver connects modern platforms back to “information overload” throughout history.
“Algorithmic recommender systems were just the most recent development in a species-spanning history of recommendation, dating back to the origins of human sociality itself,” Seaver writes.
In this book, you won’t find the specifics of how Spotify designs Discover Weekly playlists or how Pandora creates radio queues. But, you will find intriguing anecdotes and theories that will challenge the way you think about music, artificial intelligence and their cultural significance.
Hope Karnopp is the news manager and dabbles in music reviews at The Daily Cardinal. She previously hosted the Cardinal Call for WORT-FM and edited state news.