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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.
Data is too big to be left to the data analysts. Data: Now Bigger
and Better! brings together researchers whose work is deeply
informed by the conceptual frameworks of anthropology-frameworks
that are comparative as well as field-based. From kinship to gifts,
everything old becomes rich with new insight when the
anthropological archive washes over "big data." Bringing together
anthropology's classic debates and contemporary interventions, the
book counters the future-oriented speculation so characteristic of
discussions regarding big data. Drawing on long-standing experience
in industry contexts, the contributors also provide analytical
provocations that can help reframe some of the most important
shifts in technology and society in the first half of the
twenty-first century.
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.
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