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An Ontology-Enabled Approach For User-Centered And Knowledge-Enabled Explanations Of AI Systems.pdf

ISWC2023_paper_388.pdf
Preview of An Ontology-Enabled Approach For User-Centered and Knowledge-Enabled Explanations of AI Systems
🔗 Source: iswc2023.semanticweb.org
📊 Size: 1.05 MB
📄 Pages: 8 pages
⬇️ Downloads: 82

Summary

This thesis proposes an ontology-enabled approach for user-centered and knowledge-enabled explanations of AI systems, focusing on bridging the gap between model and user-centered explainability. The approach involves creating an explanation ontology (EO) to represent literature-derived explanation types, implementing a knowledge-augmented question-answering pipeline for contextual explanations in a clinical setting, and designing a system to combine explanations from different AI methods and data modalities. The EO can represent 15 different explanation types and has been tested in six exemplar use cases, with results showing that knowledge augmentations improve the performance of base large language models in contextualized question-answering. Clinicians prefer explanations that include actionability, and the combination method plans to use similarity metrics to determine the similarity of explanations in a chronic disease detection setting.

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Description

This thesis proposes an ontology-enabled approach for user-centered and knowledge-enabled explanations of AI systems, focusing on bridging the gap between...

Technical Information

  • File Format: PDF
  • File Size: 1.05 MB
  • Pages: 8
  • Language: EN
  • Total Downloads: 82
  • Last Updated: 3 weeks ago

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