Ghosts in the Data: The Contested Politics of Absence in Data Infrastructures

2025/08/02 by Will Orr · 1 voice · 1 citation
Social Sciences · #Ethics and Social Impacts of AI

paper · doi:10.1177/08944393251365277

openalex publication_date 2025/08/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/22

Abstract

Absences are inescapable in data. Data collection always focuses on some elements while occluding others. Yet, how absences are considered and recorded within data infrastructures markedly transforms the inferences that can be made. Tracing a genealogy from early databases to contemporary AI datasets, this paper explores how data infrastructures have grappled with the inherent incompleteness of data. Specifically, I uncover a tension between a desire for certainty and acknowledging partiality at the foundation of data science that continues to pervade contemporary AI datasets. Drawing on archival studies and sociological perspectives, I argue that data science must embrace uncertainty by recognizing the “ghosts in the data”—the uncounted, the unrepresented, and the silenced—and how their absence shapes the outcomes of automated systems.

Citations

• "A veritable bucket of facts" origins of the data base management system
• A relational model of data for large shared data banks
• The Social Construction of Facts and Artefacts: or How the Sociology of Science and the Sociology of Technology might Benefit Each Other
• Measuring Massive Multitask Language Understanding
• Data Feminism
• Sorting Things Out

Cited by

• AI’s Sociological Era

Discussions

• My new paper examines the history of data infrastructures and how they grapple with absent and incomplete information. Exploring the tension between the desire for certainty and acknowledging partiali [bsky, 12 points, 2 comments]

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