User Preferences in Visualization-Based Choice-Making

This talk provides different perspectives on using data visualization to leverage user preferences in making choices. We face many choices in our personal and professional lives. Computing has made it easy to compile large numbers of options to choose from. Identifying the best solution among such a set is called multi-attribute choice. With no objectively optimal solution present, our human judgment is needed to trade off conflicting goals. Data visualization is a powerful tool to help us explore and make sense of available courses of action. While many interactive visualizations already live in the context of decision-making, how to design for humans who make decisions with visualized data continues to be a vibrant research area. In this talk, I will touch upon different properties of multi-attribute choices including subjectivity. I will particularly address the role of user preferences and how they might be elicited, expressed, and considered in visualization-based choice support. This will include some usage scenarios where our visualizations helped users apply their preferences to balance the levels of performance that are achievable under different conditions.