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Creators/Authors contains: "Ashok Goel, Harshvardhan Sikka"

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  1. (, Procs. IJCAI-2022 Workshop on Explainable AI)
    We describe a human-centered and design-based stance towards generating explanations in AI agents. We collect questions about the working of an AI agent through participatory design by fo- cus groups. We capture an agent’s design through a Task-Method-Knowledge model that explicitly specifies the agent’s tasks and goals, as well as the mechanisms, knowledge and vocabulary it uses for accomplishing the tasks. We illustrate our approach through the generation of explanations in Skillsync, an AI agent that links companies and colleges for worker upskilling and reskilling. In particular, we embed a question-answering agent called AskJill in Skillsync, where AskJill contains a TMK model of Skillsync’s design. AskJill presently answers human-generated questions about Skillsync’s tasks and vocabulary, and thereby helps explain how it produces its recommendations. 
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    Accepted Manuscript Full Text Available