Privacy Communication Patterns for Domestic Robots

Explore groundbreaking research on privacy concerns and communication patterns for domestic robots in this 13-minute conference talk from SOUPS 2024. Delve into findings from a comprehensive study that investigated how advanced robotic capabilities affect privacy concerns in home environments. Learn about 86 distinct patterns developed through focus groups to effectively communicate the status of microphones, cameras, and internet connectivity in domestic robots. Discover key insights from a large-scale survey of 1,720 participants that evaluated these patterns based on trust, privacy, understandability, notification qualities, and user preferences. Gain valuable knowledge about designing privacy-preserving features for future domestic robots, presented by researchers from LMU Munich, Munich Center for Machine Learning, and Rosenheim Technical University of Applied Sciences. The presentation, which won the IAPP SOUPS Privacy Award, offers essential guidance for developers and researchers working on the next generation of home robotics.