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dc.contributor.authorChari, Shruthi
dc.contributor.authorSeneviratne, Oshani
dc.contributor.authorGruen, Daniel M.
dc.contributor.authorMcGuinness, Deborah L.
dc.identifier.citationChari, S., Seneviratne, O., Gruen, D.M.,McGuinness, D. L.,2020. Foundations of Explainable Knowledge-Enabled Systems. In Ilaria Tiddi, Freddy Lecue, Pascal Hitzler (eds.), Knowledge Graphs for eXplainable AI --Foundations.en_US
dc.identifier.isbn978-1-64368-080-4 (print) | 978-1-64368-081-1 (online)
dc.description.abstractExplainability has been an important goal since the early days of Artificial Intelligence. Several approaches for producing explanations have been developed. However, many of these approaches were tightly coupled with the capabilities of the artificial intelligence systems at the time. With the proliferation of AI-enabled systems in sometimes critical settings, there is a need for them to be explainable to end-users and decision-makers. We present a historical overview of explainable artificial intelligence systems, with a focus on knowledge-enabled systems, spanning the expert systems, cognitive assistants, semantic applications, and machine learning domains. Additionally, borrowing from the strengths of past approaches and identifying gaps needed to make explanations user- and context-focused, we propose new definitions for explanations and explainable knowledge-enabled systems.en_US
dc.description.sponsorshipThis work is partially supported by IBM Research AI through the AI Horizons Network.en_US
dc.publisherIOS Pressen_US
dc.rightsAttribution-NoDerivs 3.0 United States*
dc.subjectKG4XAI, Explainable Knowledge-Enabled Systems, Historical Evolutionen_US
dc.titleFoundations of Explainable Knowledge-Enabled Systemsen_US
dc.typeBook chapteren_US

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Attribution-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NoDerivs 3.0 United States