DataWorks
Can we design a more just and equitable form of data work?
Much has been written about the unfair labor conditions of data work, particularly in the context of AI. DataWorks was a program built inside of Georgia Tech to do something different: to hire and train Atlanta residents as entry level data wranglers, with fair wages, benefits, and a democratic workplace.
It was a massive undertaking in designing and sustaining an experimental work environment.
The result was a program that truly broadened participation in computing, fostered diverse approaches to data science, supported equitable labor practices, and developed just forms of engagement between universities and communities.
Income generated from contract-based projects from non-profit, government, and for-profit organizations helps sustain DataWorks. The data workers are hired as Georgia Tech employees with benefits and are paid hourly. Faculty and students do not receive compensation from our contract-based work.
Initial funding for DataWorks was graciously provided by the Constellations Center for Equity in Computing in the School of Computing at Georgia Tech. In 2020, DataWorks was awarded a 3-year Smart and Connected Communities grant from the National Science Foundation. This award focuses on developing an understanding of how historically minoritized communities can more fully participate in the design and use of processes, practices, and tools for preparing and analyzing data.
DataWorks continues to operate today. It is no longer run by faculty, but has been successfully integrated into the Georgia Tech Office of Sponsored Projects.
2020 - 2025
Director: Betsy DiSalvo
Co-Directors: Carl DiSalvo, Ben Shapiro, Ellen Zegura
Client Engagement: Cicely Garrett
Students: Annabel Rothschild, Lara Schenk, Emily Hodges, Priyanka Mohindra, Bang Tran, Amanda Wooten, Grace Barkuff, Britney Johnson
Related Publications
DiSalvo, Carl, Annabel Rothschild, Lara L. Schenck, Ben Rydal Shapiro, and Betsy DiSalvo. "When Workers Want to Say No: A view into critical consciousness and workplace democracy in data work." Proceedings of the ACM on Human-Computer Interaction 8, no. CSCW1 (2024): 1-24.