2 citations · 7 across the 19 of their papers we have counts for
4 papers · 1 filter
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…
A Comprehensive Framework to Operationalize Social Stereotypes for Responsible AI Evaluations
Aida Davani, Sunipa Dev, Héctor Pérez-Urbina +1
Societal stereotypes are at the center of a myriad of responsible AI interventions targeted at reducing the generation and propagation of potentially harmful outcomes. While these…
(Unfair) Norms in Fairness Research: A Meta-Analysis
Jennifer Chien, A. Stevie Bergman, Kevin R. McKee +5
Algorithmic fairness has emerged as a critical concern in artificial intelligence (AI) research. However, the development of fair AI systems is not an objective process. Fairness i…
Disentangling Perceptions of Offensiveness: Cultural and Moral Correlates
Aida Davani, Mark Díaz, Dylan Baker +1
Perception of offensiveness is inherently subjective, shaped by the lived experiences and socio-cultural values of the perceivers. Recent years have seen substantial efforts to bui…