Special issue on “Trustworthy AI and Visual Analytics for Big Data” for the Journal of Visual Languages and Computing
• 大类 : 工程技术 - 4区
• 小类 : 计算机：软件工程 - 4区
We have witnessed a rapid boom of data in recent years from various fields such as infrastructure, transport, energy, health, education, telecommunications, and finance. Together with the dramatic advances in Machine Learning (ML) and Visual Analytics (VA), getting insights from these ``big data'' and data analytics-driven solutions are increasingly in demand for different purposes. While we continuously find ourselves coming across ML-based Artificial Intelligence (AI) and VA systems that seem to work or have worked surprisingly well in practical scenarios, these technologies still face prolonged challenges with low user acceptance of delivered solutions as well as seeing system misuse, disuse, or even failure. These fundamental challenges can be attributed to the nature of ``black-box'' of ML methods for domain experts and a lack of consideration of the human user aspects when offering ML and VA based solutions.
This special issue targets on novel principles, analytics techniques and evaluation methodologies that are to address issues surrounding trustworthy AI and VA especially from human user’s perspectives of visible, explainable, trustworthy and transparent. The primary objective is to foster focused attention in this emerging area and to serve as forum for researchers and professionals all over the world to exchange and discuss the latest advances.
Papers to be submitted to this special issue must focus on trustworthy AI (e.g. visualizations, evaluations, human responses, etc.) and visual analytics for big data. All submitted papers will be peer-reviewed and papers will be selected based on their quality and relevance to the theme of this special issue. Topics considered for this special issue include, but are not limited to, the following:
Innovative algorithms, visual processing, analytics systems and techniques for trustworthy AI
Case studies, user studies, and application systems of trustworthy AI and visual analytics
Cognitive aspects of trustworthy AI
Human-machine interfaces, frameworks, architectures, tools and systems for trustworthy AI and visual analytics