50 citations · 62 across the 10 of their papers we have counts for
5 papers · 1 filter
Evaluating AI-Generated Images of Cultural Artifacts with Community-Informed Rubrics
Nari Johnson, Deepthi Sudharsan, Hamna +7
Measurement is essential to improving AI performance and mitigating harms for marginalized groups. As generative AI systems are rapidly deployed across geographies and contexts, AI…
What People See (and Miss) About Generative AI Risks: Perceptions of Failures, Risks, and Who Should Address Them
Megan Li, Wendy Bickersteth, Ningjing Tang +7
Despite growing concerns about the risks of Generative AI (GenAI), there is limited understanding of public perceptions of these risks and their associated failure modes -- defined…
Disclosure or Marketing? Analyzing the Efficacy of Vendor Self-reports for Vetting Public-sector AI
Blaine Kuehnert, Nari Johnson, Ravit Dotan +1
Documentation-based disclosure has become a central governance strategy for responsible AI, particularly in public-sector procurement. Tools such as model cards, datasheets, and AI…
Beyond the Single Turn: Reframing Refusals as Dynamic Experiences Embedded in the Context of Mental Health Support Interactions with LLMs
Ningjing Tang, Alice Qian, Qiaosi Wang +6
Content Warning: This paper contains participant quotes and discussions related to mental health challenges, emotional distress, and suicidal ideation. Large language models (LLMs)…
Toward Third-Party Assurance of AI Systems: Design Requirements, Prototype, and Early Testing
Rachel M. Kim, Blaine Kuehnert, Alice Lai +3
As Artificial Intelligence (AI) systems proliferate, the need for systematic, transparent, and actionable processes for evaluating them is growing. While many resources exist to su…