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cs.HC2026
When Are LLM Inferences Acceptable? User Reactions and Control Preferences for Inferred Personal Information
Kyzyl Monteiro, Minjung Park, Alexander Ioffrida +6
Ask ChatGPT about vacation planning, and it may infer your income. Ask it about medication, and it may infer your medical history. Because such inferences can expose more informati…
cs.HC2026
Promoting Critical Thinking With Domain-Specific Generative AI Provocations
Thomas Åerban von Davier, Hao-Ping Lee, Jodi Forlizzi +1
The evidence on the effects of generative AI (GenAI) on critical thinking is mixed, with studies suggesting both potential harms and benefits depending on its implementation. Some…
cs.HC2026
Privy: Envisioning and Mitigating Privacy Risks for Consumer-facing AI Product Concepts
Hao-Ping Lee, Yu-Ju Yang, Matthew Bilik +7
AI creates and exacerbates privacy risks, yet practitioners lack effective resources to identify and mitigate these risks. We present Privy, a tool that guides practitioners withou…