Project

Discriminating Data: Neighborhoods, Individuals, Proxies

Program

ACLS Fellowship Program

Department

Modern Culture and Media

Abstract

Discriminating Data—a monograph and series of digital projects—investigates the persistence and transformation of categories of race, gender, class, and sexuality in the era of network analytics. Analyzing the ways in which allegedly neutral machine learning algorithms merge methods to target individuals with those designed to group users into neighborhoods based on similar likes and dislikes, this project both reveals the assumptions underlying these algorithms and creates methods to desegregate them. By doing so, it produces a practice and theory of networked actions-as-speech that explores our potential as characters in a universe of unfolding dramas called “big data.”