I will be presenting my thesis proposal in early May 2011 about my work in providing intelligibility in context-aware applications.
When: May 2nd, Monday @ 1.30pm
Where: Gates-Hillman Center 6115
Improving Understanding, Trust, and Control with Intelligibility in Context-Aware Applications
Anind K. Dey (Chair), Carnegie Mellon University, Human-Computer Interaction Institute
Scott E. Hudson, Carnegie Mellon University, Human-Computer Interaction Institute
Aniket Kittur, Carnegie Mellon University, Human-Computer Interaction Institute
Margaret M. Burnett, Oregon State University
To facilitate everyday activities, context-aware applications use sensors to detect what is happening, and use increasingly complex mechanisms (e.g., by using machine learning) to infer the user’s context. For example, a mobile application can recognize that you are in a conversation, and suppress any incoming messages. When the application works well, this implicit sensing and complex inference remain invisible. However, when it behaves inappropriately or unexpectedly, users may not understand its behavior, and this can lead users to mistrust, misuse, or abandon it. To counter this, context-aware applications should be intelligible, capable of generating explanations of their behavior.
My thesis investigates providing intelligibility in context-aware applications, and evaluates its usefulness to improve user understanding, trust, and control. I explored what explanation types users want when using context-aware applications in various circumstances. I provided explanations in terms of questions that users would ask, such as why did it do X, what if I did W, what will it do? Early evaluation found that why and why not explanations can improve understanding and trust. I next developed a toolkit to help developers to implement intelligibility in their context-aware applications, such that they can automatically generate explanations. Following which, I conducted a usability study to derive design recommendations for presenting usable intelligibility interfaces of a mobile application. In the remaining work, I will evaluate intelligibility in more realistic settings. First, I shall explore the helpfulness and harmfulness of intelligibility for applications with high and low certainties. Finally, I shall investigate how intelligibility, through improving user understanding, can help the users to more effectively control a context-aware application.