Deceptive Design Patterns in Safety Technologies: A Case Study of the Citizen App Ishita Chordia, Lena-Phuong Tran, Tala June Tayebi, Emily Parrish, Sheena Erete, Jason Yip, Alexis Hiniker CHI 2023: The ACM CHI Conference on Human Factors in Computing Systems Session: Digital Wellbeing 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. Web:: https://programs.sigchi.org/chi/2023/program/content/96441 Pre-recorded presentation videos for papers at CHI 2023