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A Brief Review of Explainable Artificial Intelligence (XAI) Techniques
The increasing use of artificial intelligence (AI) in various domains has led to a growing need for AI systems to provide interpretable and understandable results. This need has given rise to the field of explainable artificial intelligence (XAI). XAI refers to the development of AI systems that can provide a clear and interpretable explanation of their decision-making processes to the end-users. In this paper, we provide a comprehensive review of the state-of-the-art techniques in XAI. We start by proposing a classification of the different XAI techniques, from the moment of application to the extent of the explanation and other specific properties of the methods. We then review multiple XAI methods, including ad-hoc techniques, local and global explanations, and other subgroups. Not only the theory behind them is explained, but also their practical application, so as to show the different outputs that can be obtained with different python implementations. Finally, we conclude the paper by highlighting the future lines of research in XAI and its potential impact on society.
A Brief Review of Explainable Artificial Intelligence (XAI) Techniques
The increasing use of artificial intelligence (AI) in various domains has led to a growing need for AI systems to provide interpretable and understandable results. This need has given rise to the field of explainable artificial intelligence (XAI). XAI refers to the development of AI systems that can provide a clear and interpretable explanation of their decision-making processes to the end-users. In this paper, we provide a comprehensive review of the state-of-the-art techniques in XAI. We start by proposing a classification of the different XAI techniques, from the moment of application to the extent of the explanation and other specific properties of the methods. We then review multiple XAI methods, including ad-hoc techniques, local and global explanations, and other subgroups. Not only the theory behind them is explained, but also their practical application, so as to show the different outputs that can be obtained with different python implementations. Finally, we conclude the paper by highlighting the future lines of research in XAI and its potential impact on society.
A Brief Review of Explainable Artificial Intelligence (XAI) Techniques
Lect. Notes in Networks, Syst.
Castillo Ossa, Luis Fernando (editor) / Isaza, Gustavo (editor) / Cardona, Óscar (editor) / Castrillón, Omar Danilo (editor) / Corchado Rodriguez, Juan Manuel (editor) / De la Prieta Pintado, Fernando (editor) / Martínez, Daniel López (author) / de Benito Fernández, Marco (author) / González-Briones, Alfonso (author) / Chamoso, Pablo (author)
Sustainable Smart Cities and Territories International Conference ; 2023 ; Manizales, Colombia
2023-09-02
11 pages
Article/Chapter (Book)
Electronic Resource
English
Explainable Artificial Intelligence (XAI) , ProtoDash , DIP-VAE , SHAP , LIME , TREPAN , ProfWeight , TED Engineering , Computational Intelligence , Transportation Technology and Traffic Engineering , Environmental Policy , Sociology, general , Sustainable Architecture/Green Buildings , Urban Studies/Sociology
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