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Explainable Artificial Intelligence
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Author(s): Vanessa Keppeler (PwC, Germany), Matthias Lederer (Technical University of Applied Sciences Amberg-Weiden, Germany)and Ulli Alexander Leucht (PwC, Germany)
Copyright: 2023
Pages: 18
Source title:
Encyclopedia of Data Science and Machine Learning
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-7998-9220-5.ch100
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Abstract
The explainability of artificial intelligence (AI) is one of the central challenges for the wider use of the new technology in many industries and applications. The more powerful and efficient the algorithms of AI work, the less it is usually comprehensible to users. While there is widespread agreement on the basic requirement of explainability for AI applications, the design of an adequate AI explanation is rarely defined. This contribution presents basic concepts of explainability as well as current approaches to explanations for AI. It describes which methods are fundamentally suitable for considering an explanation to be complete and how it must be designed in order to be assessed as interpretable for AI.
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