A review of taxonomies of explainable artificial intelligence (XAI) methods

T Speith - Proceedings of the 2022 ACM conference on fairness …, 2022 - dl.acm.org
The recent surge in publications related to explainable artificial intelligence (XAI) has led to
an almost insurmountable wall if one wants to get started or stay up to date with XAI. For this …

Explainable artificial intelligence: a comprehensive review

D Minh, HX Wang, YF Li, TN Nguyen - Artificial Intelligence Review, 2022 - Springer
Thanks to the exponential growth in computing power and vast amounts of data, artificial
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …

Survey on explainable AI: From approaches, limitations and applications aspects

W Yang, Y Wei, H Wei, Y Chen, G Huang, X Li… - Human-Centric …, 2023 - Springer
In recent years, artificial intelligence (AI) technology has been used in most if not all domains
and has greatly benefited our lives. While AI can accurately extract critical features and …

A comprehensive taxonomy for explainable artificial intelligence: a systematic survey of surveys on methods and concepts

G Schwalbe, B Finzel - Data Mining and Knowledge Discovery, 2023 - Springer
In the meantime, a wide variety of terminologies, motivations, approaches, and evaluation
criteria have been developed within the research field of explainable artificial intelligence …

How cognitive biases affect XAI-assisted decision-making: A systematic review

A Bertrand, R Belloum, JR Eagan… - Proceedings of the 2022 …, 2022 - dl.acm.org
The field of eXplainable Artificial Intelligence (XAI) aims to bring transparency to complex AI
systems. Although it is usually considered an essentially technical field, effort has been …

From anecdotal evidence to quantitative evaluation methods: A systematic review on evaluating explainable ai

M Nauta, J Trienes, S Pathak, E Nguyen… - ACM Computing …, 2023 - dl.acm.org
The rising popularity of explainable artificial intelligence (XAI) to understand high-performing
black boxes raised the question of how to evaluate explanations of machine learning (ML) …

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

S Ali, T Abuhmed, S El-Sappagh, K Muhammad… - Information fusion, 2023 - Elsevier
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …

Explainable artificial intelligence: a systematic review

G Vilone, L Longo - arXiv preprint arXiv:2006.00093, 2020 - arxiv.org
Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few
years. This is due to the widespread application of machine learning, particularly deep …

Explainability of artificial intelligence methods, applications and challenges: A comprehensive survey

W Ding, M Abdel-Basset, H Hawash, AM Ali - Information Sciences, 2022 - Elsevier
The continuous advancement of Artificial Intelligence (AI) has been revolutionizing the
strategy of decision-making in different life domains. Regardless of this achievement, AI …

Explainable AI: current status and future directions

P Gohel, P Singh, M Mohanty - arXiv preprint arXiv:2107.07045, 2021 - arxiv.org
Explainable Artificial Intelligence (XAI) is an emerging area of research in the field of
Artificial Intelligence (AI). XAI can explain how AI obtained a particular solution (eg …