Archaeology of Self: Reflexivity in Data Activism to Address Systemic Injustices
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3757887.3763020.pdf
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1.39 MB
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Author(s)
Walker, Raechel
Cruse, Brady
Cora, Aisha
Rogers, Kantwon
D'Ignazio, Catherine
Brion-Meisels, Gretchen
Breazeal, Cynthia
Date Issued
November 4, 2025
Publisher
ACM|Equity and Access in Algorithms, Mechanisms, and Optimization
Citation
Raechel Dionne Walker, Brady Cruse, Aisha Cora, Kantwon Rogers, Catherine D'Ignazio, Gretchen Brion-Meisels, and Cynthia Breazeal. 2025. Archaeology of Self: Reflexivity in Data Activism to Address Systemic Injustices. In Proceedings of the 5th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO '25). Association for Computing Machinery, New York, NY, USA, 28–41.
Version
Final published version
Abstract
Traditional data science education often neglects the importance of identity and sociopolitical context—especially for African American students whose lived experiences and cultural insights are essential for building justice centered technologies. This paper presents findings from the Data Activism Program, which integrated Dr. Yolanda Sealey-Ruiz’s Archaeology of Self™ framework to foster critical self-reflection and racial identity development among African American high school and college students. Through technical training in data science, art-based learning, and partnerships with social justice organizations, students engaged in reflexive practices that positioned them as active agents in challenging systemic oppression. Interviews reveal that the Archaeology of Self™ deepened students’ reflexivity skills and strengthened their sound racial identity, enabling them to interrogate bias within themselves and the data science process. We argue that embedding frameworks such as the Archaeology of Self™ into algorithmic design offers a concrete, transferable method for operationalizing reflexivity in data science and AI. This study contributes to the AI and data science community by offering actionable strategies to center identity and power in AI development.
Description
EAAMO ’25, Pittsburgh, PA, USA
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Urban Studies and Planning
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1145/3757887.3763020
