89 citations · 176 across the 4 of their papers we have counts for
4 papers
The Who in XAI: How AI Background Shapes Perceptions of AI Explanations
Upol Ehsan, Samir Passi, Q. Vera Liao +4
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-me…
Automated Rationale Generation: A Technique for Explainable AI and its Effects on Human Perceptions
Upol Ehsan, Pradyumna Tambwekar, Larry Chan +2
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…
The View from the Other Side: The Border Between Controversial Speech and Harassment on Kotaku in Action
Shagun Jhaver, Larry Chan, Amy Bruckman
In this paper, we use mixed methods to study a controversial Internet site: The Kotaku in Action (KiA) subreddit. Members of KiA are part of GamerGate, a distributed social movemen…
Rationalization: A Neural Machine Translation Approach to Generating Natural Language Explanations
Upol Ehsan, Brent Harrison, Larry Chan +1
We introduce AI rationalization, an approach for generating explanations of autonomous system behavior as if a human had performed the behavior. We describe a rationalization techn…