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Explainable artificial intelligence (XAI) allows human users to comprehend and trust the results and output created by machine learning algorithms.
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The main focus is usually on the reasoning behind the decisions or predictions made by the AI which are made more understandable and transparent. XAI counters ...
Despite some notable challenges, explainable AI/ML could provide insights into the decision-making process, making the outcomes of models more transparent.
The Explainable AI (XAI) program aims to create a suite of machine learning techniques that: Produce more explainable models, while maintaining a high level of ...
Jan 17, 2022 · Explainable artificial intelligence (XAI) is a powerful tool in answering critical How? and Why? questions about AI systems and can be used ...
The study starts by explaining the background of XAI, common definitions, and summarizing recently proposed techniques in XAI for supervised machine learning.
Jan 26, 2020 · Abstract:We are used to the availability of big data generated in nearly all fields of science as a consequence of technological progress.
Jun 22, 2020 · Definition 1.(explainable AI). (a) Produce more explainable models while maintaining a high level of learning performance (e.g., prediction ...
This paper presents a narrative review of XAI and a taxonomy of precepts and models to raise awareness about its potential opportunities for use in ...
Explainable artificial intelligence (XAI) is a crucially important aspect of improving trust and reliability of artificial intelligent and machine learning ...