Deceptive Design Patterns in Safety Technologies: A Case Study of the Citizen App

要旨

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 \textit{deceptive infrastructure}. We propose the need to expand an existing taxonomy of harm to include \textit{emotional load} and \textit{social injustice} and offer recommendations for designers interested in dismantling the deceptive infrastructure of safety technologies.

受賞
Best Paper
著者
Ishita Chordia
University of Washington, Seattle, Washington, United States
Lena-Phuong Tran
University of Washington, SEATTLE, Washington, United States
Tala June. Tayebi
University of Washington , Seattle, Washington, United States
Emily Parrish
University of Washington, SEATTLE, Washington, United States
Sheena Erete
University of Marylamd, College Park, Maryland, United States
Jason Yip
University of Washington, Seattle, Washington, United States
Alexis Hiniker
University of Washington, Seattle, Washington, United States
論文URL

https://doi.org/10.1145/3544548.3581258

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Digital Wellbeing

Hall G2
6 件の発表
2023-04-26 20:10:00
2023-04-26 21:35:00