Reimagining Data Work: Participatory Annotation Workshops as Feminist Practice
Yujia Gao, Isadora Araujo Crux\^en, Helena Su\'arez Val, Alessandra Jungs de Almeida, Catherine D'Ignazio, Harini Suresh

TL;DR
This paper explores feminist-inspired participatory workshops for data annotation, emphasizing dialogue, community, and disrupting hierarchies to improve AI data practices through empirical case studies.
Contribution
It introduces feminist epistemology-based workshop methods for data annotation and analyzes their impact on fostering dialogue, community, and rethinking data labor.
Findings
Workshops foster dialogue and community among data workers.
Prioritizing context and pluralism may require bounding context and tactical consensus.
Addressing labor acknowledgment while resisting transactional dynamics is complex.
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…
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Taxonomy
TopicsEthics and Social Impacts of AI · Information Systems Theories and Implementation · Computational and Text Analysis Methods
