Assessing demand for intelligibility in context-aware applications

Intelligibility can help expose the inner workings and inputs of context-aware applications that tend to be opaque to users due to their implicit sensing and actions. However, users may not be interested in all the information that the applications can produce. Using scenarios of four real-world applications that span the design space of context-aware computing, we conducted two experiments to discover what information users are interested in. In the first experiment, we elicit types of information demands that users have and under what moderating circumstances they have them. In the second experiment, we verify the findings by soliciting users about which types they would want to know and establish whether receiving such information would satisfy them. We discuss why users demand certain types of information, and provide design implications on how to provide different intelligibility types to make context-aware applications intelligible and acceptable to users.