HCI
GenAI Advertising: Risks of Personalizing Ads with LLMs
(Submission) Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Brian Tang, Kaiwen Sun, Noah T. Curran, Florian Schaub, Kang G. Shin
A research project examining the risks of embedding personalized advertisements within chatbot responses. We developed a system that generates targeted ads in LLM chatbot conversations and conducted a user study to assess how ad injection impacts user trust and response quality. I created and evaluated the chatbot's ad personalization engine while running the user study. Our findings revealed that users struggle to detect chatbot ads, and undisclosed ads are rated more favorably, raising ethical concerns about AI-driven advertising.
GenAI Advertising: Risks of Personalizing Ads with LLMs
(Submission) Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
A research project examining the risks of embedding personalized advertisements within chatbot responses. We developed a system that generates targeted ads in LLM chatbot conversations and conducted a user study to assess how ad injection impacts user trust and response quality. I created and evaluated the chatbot's ad personalization engine while running the user study. Our findings revealed that users struggle to detect chatbot ads, and undisclosed ads are rated more favorably, raising ethical concerns about AI-driven advertising.
Eye-Shield: Real-Time Protection of Mobile Device Screen Information from Shoulder Surfing
32nd USENIX Security Symposium (2023)
Brian Tang, Kang G. Shin
A novel defense system against shoulder surfing attacks on mobile devices. We designed Eye-Shield, a real-time system that makes on-screen content readable at close distances but blurred or pixelated at wider angles to prevent unauthorized viewing. I created and evaluated the system, ensuring it met real-time constraints while maintaining usability and minimal power consumption. Our findings demonstrated that Eye-Shield significantly reduces shoulder surfers’ ability to read on-screen information.
Eye-Shield: Real-Time Protection of Mobile Device Screen Information from Shoulder Surfing
32nd USENIX Security Symposium (2023)
A novel defense system against shoulder surfing attacks on mobile devices. We designed Eye-Shield, a real-time system that makes on-screen content readable at close distances but blurred or pixelated at wider angles to prevent unauthorized viewing. I created and evaluated the system, ensuring it met real-time constraints while maintaining usability and minimal power consumption. Our findings demonstrated that Eye-Shield significantly reduces shoulder surfers’ ability to read on-screen information.
CONFIDANT: A Privacy Controller for Social Robots
17th ACM/IEEE International Conference on Human-Robot Interaction (2022)
Brian Tang, Dakota Sullivan, Bengisu Cagiltay, Varun Chandrasekaran, Kassem Fawaz, Bilge Mutlu
A research project exploring privacy management in conversational social robots. We developed CONFIDANT, a privacy controller that leverages NLP models to analyze conversational metadata. I theorized, implemented, and evaluated the privacy controller, integrating speech transcription, sentiment analysis, speaker recognition, and topic classification systems. Our findings demonstrated that robots equipped with privacy controls are perceived as more trustworthy, privacy-aware, and socially aware.
CONFIDANT: A Privacy Controller for Social Robots
17th ACM/IEEE International Conference on Human-Robot Interaction (2022)
A research project exploring privacy management in conversational social robots. We developed CONFIDANT, a privacy controller that leverages NLP models to analyze conversational metadata. I theorized, implemented, and evaluated the privacy controller, integrating speech transcription, sentiment analysis, speaker recognition, and topic classification systems. Our findings demonstrated that robots equipped with privacy controls are perceived as more trustworthy, privacy-aware, and socially aware.
