CARE AND SCALE Decorrelative Ethics in Algorithmic Recommendation

The people who make algorithmic recommender systems want apparently incompatible things: they pride themselves on the scale at which their software works, but they also want to treat their materials and users with care. Care and scale are commonly understood as contradictory goals: to be careful is...

Full description

Saved in:
Bibliographic Details
Published in:Cultural anthropology Vol. 36; no. 3; pp. 509 - 537
Main Author: SEAVER, NICK
Format: Journal Article
Language:English
Published: Washington Wiley 01.08.2021
American Anthropological Association
Subjects:
ISSN:0886-7356, 1548-1360
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The people who make algorithmic recommender systems want apparently incompatible things: they pride themselves on the scale at which their software works, but they also want to treat their materials and users with care. Care and scale are commonly understood as contradictory goals: to be careful is to work at small scale, while working at large scale requires abandoning the small concerns of care. Drawing together anthropological work on care and scale, this article analyzes how people who make music recommender systems try to reconcile these values, reimagining what care and scale mean and how they relate to each other in the process. It describes decorrelation, an ethical technique that metaphorically borrows from the mathematics of machine learning, which practitioners use to reimagine how values might relate with each other. This “decorrelative ethics” facilitates new arrangements of care and scale, which challenge conventional anthropological theorizing.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0886-7356
1548-1360
DOI:10.14506/ca36.3.11