Special Issues
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Artificial Intelligence Current Perspectives and Alternative Paths: From eXplainable AI to Generative AI and Data Visualization Technologies

Submission Deadline: 31 December 2024 View: 481 Submit to Special Issue

Guest Editors

Prof. Cesar Maldonado Sanin, Australian Institute of Higher Education, Australia. / The University of Newcastle, Australia
Prof. Edward Szczerbicki, The University of Newcastle, Australia
Dr. Md Rafiqul Islam, Australian Institute of Higher Education, Australia

Summary

Artificial Intelligence (AI) is once again dominating conversations at the moment. Latest advances of AI have made again it to be at the top of research topics as it was when Deep Blue won against Garry Kasparov in 1997, or when IBM Watson won Jeopardy in 2011. Artificial intelligence’s latest advances are now at the hands of every person with access to internet, democratizing its exploration and experimentation. Everyone can “play” with it.


Responding to the challenges and uncertainties AI presents, government, industry, and researchers have to offer alternatives to develop forward-smart technologies that control unintended consequences, improve human life tyle, and decrease human inequalities, i.e., an AI that is human-centred, ethical, and aiming at society improvements.  This poses a plea for actions to investigate and develop AI under conditions of controlled environments that provide responsible, identifiable, and transparent AI technologies, supported by governmental and industrial regulations and policies.


Human Centred Artificial Intelligence (HCAI), Explainable AI (XAI), Generative AI (GenAI), Augmented Intelligence (AugI), and Data Visualization appear to be pivotal in the evolution of AI. Advancements in these domains are driving the development of increasingly sophisticated methods to augment human intelligence and refine decision-making models.  Consequently, there is a growing demand for advanced tools and techniques to represent, manage, and discover knowledge effectively.


This special issue is dedicated to exploring the latest innovations in AI methodologies and algorithms, particularly focusing on integrating of HCAI, XAI, GenAI, AugI and data visualization technologies as they pertain to real-world problems. Submissions are invited from all corners of the AI and smart information systems domain, provided they have a significant component related to the aforementioned fields. The primary goal of this issue is to assemble a diverse community of researchers, scientists, engineers, professionals, and academics from various disciplines to exchange and refine existing practices while pioneering new techniques.  Original contributions on algorithms, tool design, implementation, and real-world applications, especially those leveraging HCAI, XAI, GenAI, AugI, and data visualization technologies, are highly encouraged to address contemporary challenges effectively.


Keywords

• Generative Artificial Intelligence
• Augmented Intelligence
• eXplainable Artificial Intelligence
• Artificial and Computational Intelligence
• GenAI Web-based Systems
• Distributed Artificial Intelligence
• Human-centered Computing
• User-Centric Design in AI Systems
• Human-Centered Design in Data Visualization
• Data Science and Visualization Systems
• Data Analytics
• Model Explanation Techniques
• Explainability in Deep Learning Models
• Evaluation Metrics for XAI Systems
• Big Data and Visualization Systems
• Data Analysis and Pattern Recognition
• Cognitive Systems
• Machine Learning and Neural Networks
• Interpretability of Machine Learning Models
• Visual Analytics for Decision Support
• Human-AI Collaboration in Problem Solving
• Genetic Algorithms and Evolutionary Computing
• Hybrid Intelligent Systems
• Natural Language Processing
• Knowledge Discovery and Data Mining
• Knowledge Representation and Management
• Image Processing
• Visual Analytics
• Interactive Data Exploration
• Machine and Computer Vision
• User Interface Design for Explainable AI
• Context-aware and Affective (Emotional) Computing
• Business Intelligence Systems
• Intelligent Agents and Multi-Agent Systems
• Intelligent Techniques in Bioinformatics
• Intelligent Techniques in Optimization
• Intelligent Systems: Energy, Hybrid
• Robotics and Autonomous Robots
• Knowledge-Based Systems and Expert Systems

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