A Human-Centered Approach to Data Privacy : Political Economy, Power, and Collective Data Subjects

TL;DR

This paper critiques current data privacy strategies, highlighting their practical failures and proposing a human-centered approach that considers broader social implications and collective data subjects.

Contribution

It introduces a sociocultural anthropological perspective to data privacy, moving beyond individual focus to include collective and contextual considerations.

Findings

Current privacy strategies often fail in practice.

Data reidentification remains a significant risk.

A broader, human-centered framework can improve privacy protections.

Abstract

Researchers find weaknesses in current strategies for protecting privacy in large datasets. Many anonymized datasets are reidentifiable, and norms for offering data subjects notice and consent over emphasize individual responsibility. Based on fieldwork with data managers in the City of Seattle, I identify ways that these conventional approaches break down in practice. Drawing on work from theorists in sociocultural anthropology, I propose that a Human Centered Data Science move beyond concepts like dataset identifiability and sensitivity toward a broader ontology of who is implicated by a dataset, and new ways of anticipating how data can be combined and used.