A Special Issue on Causal and Explainable AI
The Applied Sciences Journal, MDPI (IF 2.7, CiteScore 4.5)
Submission deadline: 30 Apr 2024
URL: https://www.mdpi.com/journal/applsci/special_issues/TCEA528X18

Special Issue Information
Over the last decade, machine learning (ML) and artificial intelligence (AI) have been increasingly adopted in various domains. However, the lack of transparency and interpretability in AI/ML models has resulted in a growing demand to make them more understandable to humans. This is crucial for ensuring effective collaboration between humans and AI systems and for ensuring regulatory compliance.

This Special Issue will present a collection of cutting-edge research and recent real-world applications in causal inference/discovery and interpretable/explainable AI, with the aim of making complex or black-box AI/ML models understandable and supporting reliable, trustable and responsible decision making.

Keywords
- interpretable machine learning
- explainable artificial intelligence
- causal discovery
- causal inference
- counterfactual analysis

Guest Editors
Dr. Yanchang Zhao
Dr. Yun-Sing Koh

Contact
yanchang.zhao@csiro.au