Deceptive Design Patterns in Safety Technologies: A Case Study of the Citizen App
University of Washington
How they used Delve
Four members of a University of Washington HCI team used Delve to independently code 15 interviews with Atlanta users of the Citizen safety app, building a shared codebook over two weeks of discussion and ending with 36 codes grouped into six themes about deceptive design in safety technology.
“To identify themes in the first twelve interview transcripts, four members of the research team, including the first author, independently coded the transcripts using Delve Tool [35]. The research team met for two weeks to develop the codebook - all disagreements were resolved through discussion.”
- Field
- Deceptive design / safety and surveillance technology
- Data
- Fifteen semi-structured Zoom interviews with Citizen app users in and around Atlanta — twelve in September and October 2021, three more in June and July 2022 recruited to reach people of color — recruited through Nextdoor, Reddit and Facebook screener surveys, plus 18 researcher screen recordings of six scripted app-use scenarios
- Approach
- Team codebook development: four researchers independently coded the first twelve transcripts in Delve, met over two weeks to reconcile the codebook by discussion, then iterated weekly for five weeks; the second interview round was coded with the settled codebook and one new code prompted re-coding of the earlier transcripts, ending at 36 codes in six themes. A parallel interface analysis of 18 screen recordings was grouped by affinity diagramming in Miro and then integrated with the interview themes
- Data types
- Interviews, Observation
Abstract
Deceptive design patterns (known as dark patterns) are interface characteristics which modify users’ choice architecture to gain users’ attention, data, and money. Deceptive design patterns have yet to be documented in safety technologies despite evidence that designers of safety technologies make decisions that can powerfully influence user behavior. To address this gap, we conduct a case study of the Citizen app, a commercially available technology which notifies users about local safety incidents. We bound our study to Atlanta and triangulate interview data with an analysis of the user interface. Our results indicate that Citizen heightens users’ anxiety about safety while encouraging the use of profit-generating features which offer security. These findings contribute to an emerging conversation about how deceptive design patterns interact with sociocultural factors to produce deceptive infrastructure. We propose the need to expand an existing taxonomy of harm to include emotional load and social injustice and offer recommendations for designers interested in dismantling the deceptive infrastructure of safety technologies.
Citation
Ishita Chordia, Lena-Phuong Tran, Tala June Tayebi, Emily Parrish, Sheena Erete, Jason Yip, Alexis Hiniker (2023). Deceptive Design Patterns in Safety Technologies: A Case Study of the Citizen App. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3544548.3581258