Users’ Expectations, Experiences, and Concerns With COVID Alert, an Exposure-Notification App
- Yue Huang ,
- Borke Obada-Obieh ,
- S. Lokam ,
- K. Beznosov
Proceedings of the ACM on Human-Computer Interaction | , Vol 6: pp. 1-33
We conducted semi-structured interviews with 20 users of Canada’s exposure-notification app, COVID Alert. We identified several types of users’ mental models for the app. Participants’ concerns were found to correlate with their level of understanding of the app. Compared to a centralized contact-tracing app, COVID Alert was favored for its more efficient notification delivery method, its higher privacy protection, and its optional level of cooperation. Based on our findings, we suggest decision-makers rethink the app’s privacy-utility trade-off and improve its utility by giving users more control over their data. We also suggest technology companies build and maintain trust with the public. Further, we recommend increasing diagnosed users’ motivation to notify the app and encouraging exposed users to follow the guidelines. Last, we provide design suggestions to help users with Unsound and Innocent mental models to better understand the app.