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Explainability of AI systems is critical for users to take informed actions. Understanding who opens the black-box of AI is just as important as opening it. We conduct a mixed-methods study of how two different groups—people with and without AI ...

Automated rationale generation is an approach for real-time explanation generation whereby a computational model learns to translate an autonomous agent's internal state and action data representations into natural language. Training on human ...

We introduce \em AI rationalization, an approach for generating explanations of autonomous system behavior as if a human had performed the behavior. We describe a rationalization technique that uses neural machine translation to translate internal state-...

Ecological Momentary Assessment (EMA) methods have emerged as an approach that enhances the ecological validity of data collected for the study of human behavior and experience. In particular, EMA methods are used to capture individuals' experiences (...

Active and passive sensing technologies are providing powerful mechanisms to track, model, and understand a range of health behaviors and well-being states. Despite yielding rich, dense and high fidelity data, current sensing technologies often require ...

Transmedia storytelling enables a narrative to traverse various media platforms in order to create a richer storyworld. To achieve this goal, our group envisioned a product called GameBridge, which builds upon the concept of transmedia storytelling by ...

PostScholar is a service that augments the results returned by Google Scholar, a search engine for academic citations. PostScholar detects the social media activity related to an article and displays that information on the search results page returned ...