A survey on the explainability of supervised machine learning

N Burkart, MF Huber - Journal of Artificial Intelligence Research, 2021 - jair.org
Predictions obtained by, eg, artificial neural networks have a high accuracy but humans
often perceive the models as black boxes. Insights about the decision making are mostly …

Principles and practice of explainable machine learning

V Belle, I Papantonis - Frontiers in big Data, 2021 - frontiersin.org
Artificial intelligence (AI) provides many opportunities to improve private and public life.
Discovering patterns and structures in large troves of data in an automated manner is a core …

[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 (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

AB Arrieta, N Díaz-Rodríguez, J Del Ser, A Bennetot… - Information fusion, 2020 - Elsevier
In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if
harnessed appropriately, may deliver the best of expectations over many application sectors …

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 …

Peeking inside the black-box: a survey on explainable artificial intelligence (XAI)

A Adadi, M Berrada - IEEE access, 2018 - ieeexplore.ieee.org
At the dawn of the fourth industrial revolution, we are witnessing a fast and widespread
adoption of artificial intelligence (AI) in our daily life, which contributes to accelerating the …

Recent advances in trustworthy explainable artificial intelligence: Status, challenges, and perspectives

A Rawal, J McCoy, DB Rawat… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Artificial intelligence (AI) and machine learning (ML) have come a long way from the earlier
days of conceptual theories, to being an integral part of today's technological society. Rapid …

A survey of methods for explaining black box models

R Guidotti, A Monreale, S Ruggieri, F Turini… - ACM computing …, 2018 - dl.acm.org
In recent years, many accurate decision support systems have been constructed as black
boxes, that is as systems that hide their internal logic to the user. This lack of explanation …

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 …

An explainable deep learning framework for resilient intrusion detection in IoT-enabled transportation networks

A Oseni, N Moustafa, G Creech… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The security of safety-critical IoT systems, such as the Internet of Vehicles (IoV), has a great
interest, focusing on using Intrusion Detection Systems (IDS) to recognise cyber-attacks in …