[HTML][HTML] Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions
Understanding black box models has become paramount as systems based on opaque
Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response …
Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response …
A Critical Survey on Fairness Benefits of Explainable AI
In this critical survey, we analyze typical claims on the relationship between explainable AI
(XAI) and fairness to disentangle the multidimensional relationship between these two …
(XAI) and fairness to disentangle the multidimensional relationship between these two …
Explainable AI-driven IoMT fusion: Unravelling techniques, opportunities, and challenges with Explainable AI in healthcare
Abstract Background and Objective: Artificial Intelligence (AI) has shown significant
advancements across several industries, including healthcare, using better fusion …
advancements across several industries, including healthcare, using better fusion …
How well can large language models explain business processes?
D Fahland, F Fournier, L Limonad, I Skarbovsky… - arXiv preprint arXiv …, 2024 - arxiv.org
Large Language Models (LLMs) are likely to play a prominent role in future AI-augmented
business process management systems (ABPMSs) catering functionalities across all system …
business process management systems (ABPMSs) catering functionalities across all system …
Towards Balancing Preference and Performance through Adaptive Personalized Explainability
As robots and digital assistants are deployed in the real world, these agents must be able to
communicate their decision-making criteria to build trust, improve human-robot teaming, and …
communicate their decision-making criteria to build trust, improve human-robot teaming, and …
``It Is a Moving Process": Understanding the Evolution of Explainability Needs of Clinicians in Pulmonary Medicine
Clinicians increasingly pay attention to Artificial Intelligence (AI) to improve the quality and
timeliness of their services. There are converging opinions on the need for Explainable AI …
timeliness of their services. There are converging opinions on the need for Explainable AI …
Explanations in Everyday Software Systems: Towards a Taxonomy for Explainability Needs
Modern software systems are becoming increasingly complex and opaque. The integration
of explanations within software has shown the potential to address this opacity and can …
of explanations within software has shown the potential to address this opacity and can …
Explainable AI: to reveal the logic of black-box models
Chinu, U Bansal - New Generation Computing, 2024 - Springer
Artificial intelligence (AI) is continuously evolving; however, in the last 10 years, it has gotten
considerably more difficult to explain AI models. With the help of explanations, end users …
considerably more difficult to explain AI models. With the help of explanations, end users …
Enhancing Breast Cancer Diagnosis in Mammography: Evaluation and Integration of Convolutional Neural Networks and Explainable AI
The study introduces an integrated framework combining Convolutional Neural Networks
(CNNs) and Explainable Artificial Intelligence (XAI) for the enhanced diagnosis of breast …
(CNNs) and Explainable Artificial Intelligence (XAI) for the enhanced diagnosis of breast …
[HTML][HTML] C-XAI: A conceptual framework for designing XAI tools that support trust calibration
Recent advancements in machine learning have spurred an increased integration of AI in
critical sectors such as healthcare and criminal justice. The ethical and legal concerns …
critical sectors such as healthcare and criminal justice. The ethical and legal concerns …