Explanation Ontology in Action: A Clinical Use-Case
Authors
Chari, Shruthi
Seneviratne, Oshani
Gruen, Daniel
Foreman, Morgan
Das, Amar
McGuinness, Deborah L.
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Issue Date
2020-11-01
Keywords
Health Empowerment by Analytics, Learning, and Semantics (HEALS)
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Abstract
We addressed the problem of a lack of semantic representation for user-centric explanations and different explanation types in our Explanation Ontology (https://purl.org/heals/eo). Such a representation is increasingly necessary as explainability has become an important problem in Artificial Intelligence with the emergence of complex methods and an uptake in high-precision and user-facing settings. In this submission, we provide step-by-step guidance for system designers to utilize our ontology, introduced in our resource track paper, to plan and model for explanations during the design of their Artificial Intelligence systems. We also provide a detailed example with our utilization of this guidance in a clinical setting.
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https://tw.rpi.edu/project/HEALS