The Power of Absence: Thinking with Archival Theory in Algorithmic Design

TL;DR

The paper rethinks algorithmic bias by reframing it as absence, drawing on archival theory to expose how power, presence, and productive potential emerge from incomplete records. Using a genealogical, critical-humanist approach, it develops three analytic axes—absence as power, presence, and productive—and grounds them in Hartman, Trouillot, Muñoz, and other theorists. It then translates these ideas into four design speculations that pair AI translation and quilts to surface biases, non-existent data, and alternative computational practices, including the Freedom Quilts and Gee’s Bend quilts as exemplars of creolized data practices. The work aims to shift bias-focused interventions toward more capacious, hands-on engagements that attend to social, historical, and political structures, promoting care, accountability, and imaginative redesigns of algorithmic systems.

Abstract

This paper explores the value of archival theory as a means of grappling with bias in algorithmic design. Rather than seek to mitigate biases perpetuated by datasets and algorithmic systems, archival theory offers a reframing of bias itself. Drawing on a range of archival theory from the fields of history, literary and cultural studies, Black studies, and feminist STS, we propose absence-as power, presence, and productive-as a concept that might more securely anchor investigations into the causes of algorithmic bias, and that can prompt more capacious, creative, and joyful future work. This essay, in turn, can intervene into the technical as well as the social, historical, and political structures that serve as sources of bias.