[HTML][HTML] Notions of explainability and evaluation approaches for explainable artificial intelligence

G Vilone, L Longo - Information Fusion, 2021 - Elsevier
Abstract 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 …

[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 …

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 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 …

A multi-component framework for the analysis and design of explainable artificial intelligence

MY Kim, S Atakishiyev, HKB Babiker… - Machine Learning and …, 2021 - mdpi.com
The rapid growth of research in explainable artificial intelligence (XAI) follows on two
substantial developments. First, the enormous application success of modern machine …

What do we want from Explainable Artificial Intelligence (XAI)?–A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research

M Langer, D Oster, T Speith, H Hermanns, L Kästner… - Artificial Intelligence, 2021 - Elsevier
Abstract Previous research in Explainable Artificial Intelligence (XAI) suggests that a main
aim of explainability approaches is to satisfy specific interests, goals, expectations, needs …

Explainable artificial intelligence: an analytical review

PP Angelov, EA Soares, R Jiang… - … : Data Mining and …, 2021 - Wiley Online Library
This paper provides a brief analytical review of the current state‐of‐the‐art in relation to the
explainability of artificial intelligence in the context of recent advances in machine learning …

Classification of explainable artificial intelligence methods through their output formats

G Vilone, L Longo - Machine Learning and Knowledge Extraction, 2021 - mdpi.com
Machine and deep learning have proven their utility to generate data-driven models with
high accuracy and precision. However, their non-linear, complex structures are often difficult …

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 …

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) …