Kopo M. Ramokapane
University of Bristol, Bristol, United Kingdom
Home energy management systems (HEMS) offer control and the ability to manage energy, generating and collecting energy consumption data at the most detailed level. However, data at this level poses various privacy concerns, including, for instance, profiling consumer behaviors and large-scale surveillance. The question of how utility providers can get value from such data without infringing consumers' privacy has remained under-investigated. We address this gap by exploring the pro-sharing attitudes and privacy perceptions of 30 HEMS users and non-users through an interview study. While participants are concerned about data misuse and stigmatization, our analysis also reveals that incentives, altruism, trust, security and privacy, transparency and accountability encourage data sharing. From this analysis, we derive privacy design strategies for HEMS that can both improve privacy and engender adoption.
https://dl.acm.org/doi/abs/10.1145/3491102.3517515
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)