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Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence

A research paper on the need for explainable AI methods to improve trust in AI models.

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Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence

By Sajid Ali, Tamer Abuhmed, Shaker El–Sappagh
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The authors discuss the challenges of understanding AI model decision-making and the importance of XAI. They review existing survey papers and highlight areas where further research is needed. The paper aims to provide a comprehensive overview of current knowledge and future directions in XAI.

Abstract

The authors discuss the challenges of understanding AI model decision-making and the importance of XAI. They review existing survey papers and highlight areas where further research is needed. The paper aims to provide a comprehensive overview of current knowledge and future directions in XAI.

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explainable aitrustworthy aixai methodsai model decision-makingAI AgentsLarge Language ModelsSemantic Interoperability
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