Stephen Snow
School of Information Technology and Electrical Engineering, Brisbane, Australia
Smart energy technologies provide new opportunities for network demand management, while generating data that can provide inference into household activities and which is increasingly valuable for user profiling and targeted marketing. This paper explores the human values implicated by smart energy technologies as energy consumption emerges as a potentially sensitive and attributable data trail. Using a values-based approach involving semi-structured interviews with 39 Australians, we use speculative design to engage participants with the implications of high frequency household energy data and understand users’ values and attitudes towards curtailment, surveillance, accountability and consent. The principal contributions are (1) a nuanced understanding of user values around privacy, responsibility, trust, collectivism and curtailment in relation to interpersonal household energy use data and considerations for speculative designs in this space, and (2) reflections on the design of mechanisms for consumer participation in demand response for energy networks.
https://doi.org/10.1145/3411764.3445095
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)