DATA REFUSAL FROM BELOW: A FRAMEWORK FOR UNDERSTANDING, EVALUATING, AND ENVISIONING REFUSAL STRATEGIES

Abstract

Amidst calls for public accountability over large data-driven systems, feminist and indigenous scholars have developed refusal as a practice that challenges the authority of data collectors. However, because data affects so many aspects of daily life, it can be hard to see seemingly different refusal strategies as part of the same repertoire. Furthermore, conversations about refusal often happen from the standpoint of designers and policymakers rather than the people and communities most affected by data collection. In this paper, we introduce a framework for data refusal from below—writing from the standpoint of people who refuse, rather than the institutions that seek their compliance. We characterize refusal strategies across four constituent facets common to all refusal, whatever tactics are used: autonomy, or how refusal accounts for individual and collective interests; time, or whether refusal reacts to past harm or proactively prevents future harm; power, or the extent to which refusal makes change possible; and cost, or whether or not refusal can reduce or redistribute penalties experienced by refusers. We illustrate each facet by drawing on cases of people and collectives that have refused data systems. Together, the four facets of our framework are designed to help scholars and activists describe, evaluate, and imagine new forms of refusal.