AI Eyes on the Road: Cross-Cultural Perspectives on Traffic Surveillance
Preprint, 2025

AI-powered road surveillance systems are increasingly proposed to monitor infractions such as speeding, phone use, and jaywalking. While these systems promise to enhance safety by discouraging dangerous behaviors, they also raise concerns about privacy, fairness, and potential misuse of personal data. Yet empirical research on how people perceive AI-enhanced monitoring of public spaces remains limited. We conducted an online survey (N=720) using a 3×3 factorial design to examine perceptions of three road surveillance modes -- conventional, AI-enhanced, and AI-enhanced with public shaming -- across China, Europe, and the United States. We measured perceived capability, risk, transparency, and acceptance. Results show that conventional surveillance was most preferred, while public shaming was least preferred across all regions. Chinese respondents, however, expressed significantly higher acceptance of AI-enhanced modes than Europeans or Americans. Our findings highlight the need to account for context, culture, and social norms when considering AI-enhanced monitoring, as these shape trust, comfort, and overall acceptance.

Author

Ziming Wang

Chalmers, Computer Science and Engineering (Chalmers), Interaction Design and Software Engineering

Stanford University

Shiwei Yang

Ghent university

Rebecca Currano

Stanford University

Morten Fjeld

University of Bergen

Chalmers, Computer Science and Engineering (Chalmers), Interaction Design and Software Engineering

David Sirkin

Stanford University

Subject Categories (SSIF 2025)

Human Computer Interaction

Applied Psychology

Artificial Intelligence

More information

Latest update

10/10/2025