“A Solution to a Problem that Didn’t Exist?”: Exploring Attitudes Towards Smart Streetlight Systems

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Abstract

We present the first exploration of individuals’ expectations for smart streetlights and associated urban data collection practices, with a focus on privacy implications. We conducted an anonymous online survey with 598 participants from across Canada. We found that participants were more accepting of data collection and usage when these were benefiting the community, and when data collection occurred through non-intrusive, privacy-preserving sensors. We also uncovered that participants lacked a coherent understanding of what constitutes a ‘smart’ streetlight. While unsurprising, these inaccurate mental models can unknowingly expose individuals to privacy risks. Our findings suggest that surveys about smart cities in general are not necessarily applicable to individual technologies such as smart streetlights because these surveys fail to account for the context in which residents encounter streetlights and the disparate impact smart streetlights can have on diverse populations. We highlight the need for cities in collaboration with smart streetlight creators to establish an iterative, resident-centered design approach and emphasize the importance for HCI designers to consider the social, cultural, and political contexts in which smart streetlights are introduced.

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APA

Theus, A. L., & Chiasson, S. (2023). “A Solution to a Problem that Didn’t Exist?”: Exploring Attitudes Towards Smart Streetlight Systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 14144 LNCS, pp. 205–238). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-42286-7_12

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