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cs.CY2026
Can Data Work be Reparative?
Srravya Chandhiramowuli, Ding Wang, Alex Taylor
We present an ethnographic study of an alternative approach to data work, developed by a civic-tech initiative that builds datasets for training and benchmarking online safety syst…
cs.CY2026
Decoding Safety Feedback from Diverse Raters: A Data-driven Lens on Responsiveness to Severity
Pushkar Mishra, Charvi Rastogi, Stephen R. Pfohl +9
Ensuring the safety of Generative AI requires a nuanced understanding of pluralistic viewpoints. In this paper, we introduce a novel data-driven approach for analyzing ordinal safe…
cs.CY2026
The Case for "Thick Evaluations" of Cultural Representation in AI
Rida Qadri, Mark Diaz, Ding Wang +1
Generative AI model outputs have been increasingly evaluated for their (in)ability to represent non-Western cultures. We argue that these evaluations often operate through reductiv…