The Role of Graph Theory in Explainable AI (XAI)

These days, deep neural networks (DNNs) are used widely in autonomous vehicles, healthcare, military and other mission-critical systems with direct effect on lives of people. Its use is challenged by the black-box problem of DNN, raising regulatory and ethical concerns like lack of trust. In “Artificial Intelligence (AI)”, “Explainable AI (XAI)” promotes a range of techniques, tools, and models to generate high-quality, intuitive, interpretable, and simple explanations of AI decisions.

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Publication Details

Journal
Journal of Informatics Education and Research
Published
2025-04-15
DOI
https://doi.org/10.52783/jier.v5i2.2519
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
0.00
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article

The Role of Graph Theory in Explainable AI (XAI)

Preeti Panwar
Journal of Informatics Education and Research
Explainable Artificial Intelligence (XAI)
article

The Role of Graph Theory in Explainable AI (XAI)

Preeti Panwar
article en

Abstract

These days, deep neural networks (DNNs) are used widely in autonomous vehicles, healthcare, military and other mission-critical systems with direct effect on lives of people. Its use is challenged by the black-box problem of DNN, raising regulatory and ethical concerns like lack of trust. In “Artificial Intelligence (AI)”, “Explainable AI (XAI)” promotes a range of techniques, tools, and models to generate high-quality, intuitive, interpretable, and simple explanations of AI decisions.

Journal of Informatics Education and ResearchVol. 5(2)
Baba Guru Nanak University (PK)
Openalex Percentile: Top 97%
Explainable Artificial Intelligence (XAI)
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The Role of Graph Theory in Explainable AI (XAI) — Preeti Panwar · Journal of Informatics Education and Research (2025) | TGRS Research Map | TGRS