Future of industry 5.0 in society: human-centric solutions, challenges and prospective research areas
A Adel - Journal of Cloud Computing, 2022 - Springer
Industry 4.0 has been provided for the last 10 years to benefit the industry and the
shortcomings; finally, the time for industry 5.0 has arrived. Smart factories are increasing the …
shortcomings; finally, the time for industry 5.0 has arrived. Smart factories are increasing the …
Re-thinking data strategy and integration for artificial intelligence: concepts, opportunities, and challenges
A Aldoseri, KN Al-Khalifa, AM Hamouda - Applied Sciences, 2023 - mdpi.com
The use of artificial intelligence (AI) is becoming more prevalent across industries such as
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of …
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of …
[HTML][HTML] Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
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 …
applications, but the outcomes of many AI models are challenging to comprehend and trust …
Human-in-the-loop machine learning: a state of the art
E Mosqueira-Rey, E Hernández-Pereira… - Artificial Intelligence …, 2023 - Springer
Researchers are defining new types of interactions between humans and machine learning
algorithms generically called human-in-the-loop machine learning. Depending on who is in …
algorithms generically called human-in-the-loop machine learning. Depending on who is in …
Survey of explainable AI techniques in healthcare
Artificial intelligence (AI) with deep learning models has been widely applied in numerous
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …
Counterfactual explanations and how to find them: literature review and benchmarking
R Guidotti - Data Mining and Knowledge Discovery, 2024 - Springer
Interpretable machine learning aims at unveiling the reasons behind predictions returned by
uninterpretable classifiers. One of the most valuable types of explanation consists of …
uninterpretable classifiers. One of the most valuable types of explanation consists of …
Interpreting black-box models: a review on explainable artificial intelligence
Recent years have seen a tremendous growth in Artificial Intelligence (AI)-based
methodological development in a broad range of domains. In this rapidly evolving field …
methodological development in a broad range of domains. In this rapidly evolving field …
Trustworthy artificial intelligence: a review
Artificial intelligence (AI) and algorithmic decision making are having a profound impact on
our daily lives. These systems are vastly used in different high-stakes applications like …
our daily lives. These systems are vastly used in different high-stakes applications like …
Explainable artificial intelligence: a comprehensive review
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 …
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
[HTML][HTML] How can we manage biases in artificial intelligence systems–A systematic literature review
PS Varsha - International Journal of Information Management Data …, 2023 - Elsevier
Artificial intelligence is similar to human intelligence, and robots in organisations always
perform human tasks. However, AI encounters a variety of biases during its operational …
perform human tasks. However, AI encounters a variety of biases during its operational …