5 papers
The Perils of Agency: How Developers Perceive, Prioritize, and Address Risks in Agentic AI Products
Hao-Ping Lee, Jessica He, David Piorkowski +3
Agentic AI systems act autonomously, use tools, adapt to context, and operate in complex real-world environments. However, these same characteristics can create or exacerbate produ…
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…
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…
How Well Can LLM Agents Simulate End-User Security and Privacy Attitudes and Behaviors?
Yuxuan Li, Leyang Li, Hao-Ping Lee +1
A growing body of research assumes that large language model (LLM) agents can serve as proxies for how people form attitudes toward and behave in response to security and privacy (…
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…