3 citations · 8 across the 12 of their papers we have counts for
5 papers · 1 filter
Humanlike AI Design Increases Anthropomorphism but Yields Divergent Outcomes on Engagement and Trust Globally
Robin Schimmelpfennig, Mark Díaz, Vinodkumar Prabhakaran +1
Over a billion users globally interact with AI systems engineered to mimic human traits. This development raises concerns that anthropomorphism, the attribution of human characteri…
"Just a strange pic": Evaluating 'safety' in GenAI Image safety annotation tasks from diverse annotators' perspectives
Ding Wang, Mark Díaz, Charvi Rastogi +10
Understanding what constitutes safety in AI-generated content is complex. While developers often rely on predefined taxonomies, real-world safety judgments also involve personal, s…
Whose View of Safety? A Deep DIVE Dataset for Pluralistic Alignment of Text-to-Image Models
Charvi Rastogi, Tian Huey Teh, Pushkar Mishra +10
Current text-to-image (T2I) models often fail to account for diverse human experiences, leading to misaligned systems. We advocate for pluralistic alignment, where an AI understand…
Risks of Cultural Erasure in Large Language Models
Rida Qadri, Aida M. Davani, Kevin Robinson +1
Large language models are increasingly being integrated into applications that shape the production and discovery of societal knowledge such as search, online education, and travel…
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…