Evaluating the Impact of a Personal Data Communication Policy in Human-Robot Interactions

Personal companion robots are increasingly integrated into households, offering tailored experiences through personalisation. However, using multiple communication pathways heightens the risk of inadvertent personal data exposure. This paper presents a novel communication policy designed to mitigate such risks by dynamically adjusting communication strategies based on the sensitivity of the shared data. We measure participant preferences for these adaptive communication methods through empirical assessment. Our findings indicate that the proposed policy effectively minimises personal data exposure, fostering increased trust in the robot's handling of sensitive information.