Reimagining Data Work: Participatory Annotation Workshops as Feminist Practice
🤖 AI Summary
This work addresses the persistent invisibility and undervaluation of labor in data annotation, where annotators are often treated as interchangeable tools rather than skilled collaborators exercising professional judgment. Through multilingual, iterative, and participatory annotation workshops co-designed with journalists and activists engaged in narratives of gender-based violence, the project integrates feminist epistemologies into data practices. It introduces novel conceptual frameworks—such as “marginalized contextualization” and “strategic consensus”—to develop an annotation approach grounded in care, reflexivity, and cross-cultural collaboration. This methodology not only reconfigures power dynamics inherent in annotation processes but also reconceptualizes AI development as a political space that acknowledges difference, affirms the value of labor, and enacts solidarity.
Application Category
📝 Abstract
AI systems depend on the invisible and undervalued labor of data workers, who are often treated as interchangeable units rather than collaborators with meaningful expertise. Critical scholars and practitioners have proposed alternative principles for data work, but few empirical studies examine how to enact them in practice. This paper bridges this gap through a case study of multilingual, iterative, and participatory data annotation processes with journalists and activists focused on news narratives of gender-related violence. We offer two methodological contributions. First, we demonstrate how workshops rooted in feminist epistemology can foster dialogue, build community, and disrupt knowledge hierarchies in data annotation. Second, drawing insights from practice, we deepen the analysis of existing feminist and participatory principles. We show that prioritizing context and pluralism in practice may require ``bounding'' context and working towards what we describe as a ``tactical consensus.'' We also explore tensions around materially acknowledging labor while resisting transactional researcher-participant dynamics. Through this work, we contribute to growing efforts to reimagine data and AI development as relational and political spaces for understanding difference, enacting care, and building solidarity across shared struggles.
Problem
Research questions and friction points this paper is trying to address.
data work
participatory annotation
feminist practice
AI development
knowledge hierarchies
Innovation
Methods, ideas, or system contributions that make the work stand out.
participatory annotation
feminist epistemology
tactical consensus
data labor
relational AI
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