Over the last decade, machine learning (ML) and Artificial Intelligence (AI) have been increasingly adopted in various domains, such as healthcare, finance, and transportation. 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. Therefore, the upcoming CXAI workshop aims to address these challenges by providing a platform for AI/ML researchers and practitioners from various countries to share their recent research outcomes and experiences in causal inference/discovery and interpretable/explainable AI. The workshop will take place on 4 Dec 2023 and will focus on improving transparency and interpretability in AI/ML models for real-world applications.

Submission Guidelines

Authors are invited to submit original papers with a limit of 8 pages maximum plus a possible 2 extra pages for references and appendices, in the IEEE 2-column format. All submissions will be triple-blind reviewed. More detailed information can be found in the IEEE ICDM 2023 Submission Guidelines.

Manuscripts must be submitted electronically on the online submission system.

List of Topics

Topics of interest include, but are not limited to:

• Structure learning and causal discovery
• Causal inference and Bayesian networks
• Counterfactual reasoning
• Interpretable machine learning
• Explainable methods
• Model interpretability
• Feature importance
• Prediction interpretation and justification
• Responsible and trustable AI
• Ethical AI
• Causal models and other methods for ML model interpretation and justification
• Model visualisation and conveying decisions to end users
• Applications of causal and explainable AI in the environment, agriculture, energy, engineering, education, finance, marketing, medicine, health and other domains.

Committees

Program Committee

• David Alexander         CSIRO, Australia
• Ranran Bian               University of Sydney, Australia
• Jaesik Choi                 Korea Advanced Institute of Science and Technology (KAIST), Republic of Korea
• Luis Riera Garcia         CSIRO, Australia
• Andrey Kostenko         Eyos.one, Singapore
• Philippe Lenca             IMT Atlantique, France
• Xiaomei Li                   CSIRO, Australia
• Dan Mackinlay             CSIRO, Australia
• Timothy Miller              University of Melbourne, Australia
• Catarina Moreira          CSIRO, Australia
• Quang Vinh Nguyen     Western Sydney University, Australia
• Shoujin Wang             University of Technology Sydney, Australia
• Guanhua Yan              Binghamton University, USA
• Vithya Yogarajan         University of Auckland, New Zealand

* More PCs to be confirmed.

Organizing committee

• Yanchang Zhao                      CSIRO, Australia
• Ainura Tursunalieva               CSIRO, Australia
• Yun Sing Koh                         The University of Auckland, New Zealand
• Yan Liu                                   University of Southern California, USA
• Gilad Francis                          University of Technology Sydney, Australia

Publication

Accepted workshop papers will be published in the dedicated ICDMW proceedings published by the IEEE Computer Society Press.

Special Issue: Authors of accepted papers will be invited to submit extended versions for possible inclusion in a Special Issue on Causal and Explainable Artificial Intelligence in the Applied Sciences journal.

Venue

The workshop will be held in Shanghai, China, 4 Dec 2023, as a part of the IEEE ICDM 2023 conference.

Contact

• Yanchang Zhao <yanchang.zhao (at) csiro.au>
• Ainura Tursunalieva <ainura.tursunalieva (at) csiro.au>