Brian Y. Lim

I will be defending my thesis in late April 2012 about my work in providing intelligibility in context-aware applications.

When:   April 23rd, Monday @ 9.30am
Where:  Newell Simon Hall 1507

THESIS DEFENSE
Improving Understanding and Trust with Intelligibility in Context-Aware Applications

COMMITTEE
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

DOCUMENTS
Flyer
Dissertation

ABSTRACT
To facilitate everyday activities, context-aware applications use sensors to detect what is happening, and use increasingly complex mechanisms (e.g., by using big rule-sets or machine learning) to infer the user’s context and intent. For example, a mobile application can recognize that the user is in a conversation, and suppress any incoming calls. 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 even abandon it. To counter this lack of understanding and loss of trust, context-aware applications should be intelligible, capable of explaining their behavior.

We investigate providing intelligibility in context-aware applications and evaluate its usefulness to improve user understanding and trust for context-aware applications. Specifically, this thesis supports intelligibility in context-aware applications through the provision of explanations that answer different question types, such as: Why did it do X? Why did it not do Y? What if I did W, What will it do? How can I get the application to do Y? Etc.

This thesis takes a three-pronged approach to investigating intelligibility by (i) eliciting the user requirements for intelligibility, to identify what explanation types end-users are interested in asking context-aware applications, (ii) supporting the development of intelligible context-aware applications with a software toolkit and the design of these applications with design and usability recommendations, and (iii) evaluating the impact of intelligibility on user understanding and trust under various situations and application reliability, and measuring how users use an interactive intelligible prototype. We show that users are willing to use well-designed intelligibility, and this can improve user understanding and trust in the adaptive behavior of context-aware applications.

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

THESIS PROPOSAL
Improving Understanding, Trust, and Control with Intelligibility in Context-Aware Applications

COMMITTEE
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

DOCUMENTS
Flyer
Proposal

ABSTRACT
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.