When(ish) is My Bus? User-centered Visualizations of Uncertainty in Everyday, Mobile Predictive Systems
ACM Human Factors in Computing Systems (CHI) 2016Abstract
Users often rely on realtime predictions in everyday contexts like riding the bus, but may not grasp that such predictions are subject to uncertainty. Existing uncertainty visualizations may not align with user needs or how they naturally reason about probability. We present a novel mobile interface design and visualization of uncertainty for transit predictions on mobile phones based on discrete outcomes. To develop it, we identified domain specific design requirements for visualizing uncertainty in transit prediction through: 1) a literature review, 2) a large survey of users of a popular realtime transit application, and 3) an iterative design process. We present several candidate visualizations of uncertainty for realtime transit predictions in a mobile context, and we propose a novel discrete representation of continuous outcomes designed for small screens, quantile dotplots. In a controlled experiment we find that quantile dotplots reduce the variance of probabilistic estimates by ~1.15 times compared to density plots and facilitate more confident estimation by end-users in the context of realtime transit prediction scenarios.
Citation
BibTeX
@inproceedings{when-ish-my-bus-2016, title = {When (Ish) is My Bus? User-Centered Visualizations of Uncertainty in Everyday, Mobile Predictive Systems}, author = {Kay, Matthew and Kola, Tara and Hullman, Jessica R. and Munson, Sean A.}, year = 2016, booktitle = {Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems}, publisher = {ACM}, series = {CHI '16}, pages = {5092–5103}, doi = {10.1145/2858036.2858558} }