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cs.HC2026
Towards Apples to Apples for AI Evaluations: From Real-World Use Cases to Evaluation Scenarios
Yee-Yin Choong, Kristen Greene, Alice Qian +6
AI measurement science has a wide variety of methodologies and measurements for comparing AI systems, resulting in what often appear to be "apples-to-oranges" comparisons across AI…
cs.HC2026
Supporting Informed Self-Disclosure: Design Recommendations for Presenting AI-Estimates of Privacy Risks to Users
Isadora Krsek, Meryl Ye, Wei Xu +3
People candidly discuss sensitive topics online under the perceived safety of anonymity; yet, for many, this perceived safety is tenuous, as miscalibrated risk perceptions can lead…