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cs.HC2026
PersonaTeaming: Supporting Persona-Driven Red-Teaming for Generative AI
Wesley Hanwen Deng, Mingxi Yan, Sunnie S. Y. Kim +5
Recent developments in AI safety research have called for red-teaming methods that effectively surface potential risks posed by generative AI models, with growing emphasis on how r…
cs.HC2024
The Problems with Proxies: Making Data Work Visible through Requester Practices
Annabel Rothschild, Ding Wang, Niveditha Jayakumar Vilvanathan +3
Fairness in AI and ML systems is increasingly linked to the proper treatment and recognition of data workers involved in training dataset development. Yet, those who collect and an…
cs.HC2024
Farsight: Fostering Responsible AI Awareness During AI Application Prototyping
Zijie J. Wang, Chinmay Kulkarni, Lauren Wilcox +2
Prompt-based interfaces for Large Language Models (LLMs) have made prototyping and building AI-powered applications easier than ever before. However, identifying potential harms th…