Journal article
Using racial discourse communities to audit personalization algorithms
Communication, culture & critique, Vol.16(3), pp.158-165
09/01/2023
DOI: 10.1093/ccc/tcad015
Abstract
Personalization algorithms are the information undercurrent of the digital age. They learn users' behaviors and tailor content to individual interests and predicted tastes. These algorithms, in turn, categorize and represent these users back to society-culturally, politically, and racially. Researchers audit personalization algorithms to critique the ways bias is perpetuated within these systems. Yet, research examining the relationship between personalization algorithms and racial bias has not yet contended with the complexities of conceptualizing race. This article argues for the use of racialized discourse communities within algorithm audits, providing a way to audit algorithms that accounts for both the historical and cultural influences of race and its measurement online.
Details
- Title: Subtitle
- Using racial discourse communities to audit personalization algorithms
- Creators
- Ryan Stoldt - University of IowaRaven Maragh-Lloyd - Washington University in St. LouisTim Havens - Univ Iowa, Dept Commun Studies, Iowa City, IA USABrian Ekdale - University of Iowa, African Studies ProgramAndrew C. High - Pennsylvania State University
- Resource Type
- Journal article
- Publication Details
- Communication, culture & critique, Vol.16(3), pp.158-165
- DOI
- 10.1093/ccc/tcad015
- ISSN
- 1753-9129
- eISSN
- 1753-9137
- Publisher
- Oxford Univ Press
- Number of pages
- 8
- Grant note
- Obermann Center for Advanced Studies at the University of Iowa FA9550-20-1-0346 / Minerva Research Initiative
- Language
- English
- Date published
- 09/01/2023
- Academic Unit
- Center for Social Science Innovation; Public Policy Center (Archive); School of Journalism and Mass Communication
- Record Identifier
- 9984473214502771
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