Ching-Yi Tsai will present his General Exam "Shaping Interaction with Situated AI through Representations of Uncertainty and Privacy" on Thursday, May 7, 2026 at 1:30 PM in CS 401 and via zoom.
Ching-Yi Tsai will present his General Exam "Shaping Interaction with Situated AI through Representations of Uncertainty and Privacy" on Thursday, May 7, 2026 at 1:30 PM in CS 401 and via zoom. Zoom link: https://princeton.zoom.us/j/98708013821?pwd=p5QPT9IYvKsQUwvcEq8fJPXCsJ2xab.1 Committee Members: Parastoo Abtahi (advisor), Andrés Monroy-Hernández, Janet Vertesi Abstract: Situated AI systems, including AR glasses, robots, and other embodied assistants, are increasingly entering everyday life. Yet interactions with these systems are still shaped by conventional designs that treat interpretations, controls, and consequences as static and deterministic, making alternative interpretations and actions difficult to perceive or refine in the dynamic conditions of everyday life. A single-target pointer, for example, can miss a user’s intended referent under noisy everyday conditions, while a simple camera on/off switch is too coarse to selectively regulate privacy-sensitive video content without sacrificing application functionality. My research investigates how interaction with situated AI can shift from static, implicit handling to in-situ, dynamic representations at the right granularity for both awareness and action. I study situated representations that bring ambiguity and privacy risks into users’ awareness while also allowing users to perceive, change, and resolve them in the moment. I will present two projects that explore scenarios for doing so: Uncertain Pointer, which investigates non-deterministic, situated feedforward visualizations for communicating and disambiguating ambiguity in users’ input, such as speech and gesture; and PrivacyLoupe, which explores a dynamic representation of privacy control that balances policy expressiveness and context sensitivity with interaction cost. I will also discuss future directions in in-situ dynamic abstraction and other interaction demands that could benefit from in-situ representation. Together, these projects examine how interaction with situated AI can be shaped by moving from static and implicit handling to situated representations that support user agency, awareness, and action. Reading List: https://docs.google.com/document/d/1chCb6CSHrHFQeaQiQUzavIZmrn6HczRD_3_bkQ2O... Everyone is invited to attend the talk, and those faculty wishing to remain for the oral exam following are welcome to do so.
participants (1)
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CS Grad Department