Symposium on Human-AI Collaboration
The rapid integration of artificial intelligence (AI) into diverse areas of human activity is reshaping the ways in which people work, make decisions, and interact with technology. As AI systems increasingly perform complex tasks and support decision-making, the need for meaningful, effective human-AI collaboration is becoming more critical. This shift demands robust theoretical foundations, innovative methodologies, and practical solutions to ensure AI can act as a reliable, transparent, and ethical partner to human users. The intersection of human cognition, ethical considerations, and technological advancement lies at the heart of the future of AI.
Human-AI collaboration spans several domains, requiring us to rethink design principles to accommodate user-centred AI, where trust, transparency, and accountability are integral. Theoretical discussions in ethics and philosophy shed light on ensuring these technologies act in alignment with human values, while methodological advances like explainable AI and human-in-the-loop approaches, and immersive tools such as virtual and augmented reality (VR and AR) enhance interpretability, collaboration, and understanding in AI systems.
Applications are broad and include fields like healthcare, education, and creative industries, where AI-driven insights are increasingly impactful but must be used judiciously and responsibly.
Neuro-symbolic AI, which combines the symbolic reasoning and structured knowledge of traditional AI with the flexibility and adaptability of neural networks, offers an additional avenue for collaborative systems. This hybrid approach enables AI to adapt to specific domains by incorporating human knowledge in symbolic forms, enhancing interpretability, domain-specific adaptation, and the overall quality of human-AI interactions. Neuro-symbolic approaches join recent advances in large language models (LLMs), natural language processing (NLP), and VR/AR technologies to provide AI systems that can understand human inputs in intuitive ways while offering explanations aligned with human logic and expertise.
Additionally, human augmentation is emerging as a transformative area within human-AI collaboration. AI-driven systems that enhance human cognitive abilities, sensory perception, or physical performance hold immense potential across various domains, such as healthcare, education, and even creative fields. These systems empower individuals, improving health outcomes, enhancing decision-making, and augmenting human potential.
The symposium will address these themes through diverse contributions, from theoretical perspectives on 1 the societal implications of AI to cutting-edge methodological innovations and real-world applications. Researchers, practitioners, and scholars are invited to contribute insights that will further the understanding of the challenges and opportunities in human-AI collaboration, exploring how these systems can be both useful and aligned with human values.
This symposium aims to foster practical insights and skills for building ethical, effective, and user-centred AI systems. The focus is on methods of harnessing the diversity of human cognitive abilities and varied AI models to create more adaptable and effective hybrid intelligent systems. The symposium addresses the challenges of integrating diverse human inputs and perspectives, while discussing ethical considerations and strategies for designing inclusive, user-centered AI solutions. Attendees will benefit from discussions, hands-on training, and interdisciplinary exchanges, supporting the development of AI functions that act as transparent and trustworthy partner, to enhancing human expertise and decision-making across sectors.
The symposium will cover a range of theoretical, methodological, and applied aspects of human-AI collaboration, including but not limited to:
The organising committee is composed of three established academics with extensive experience in Artificial Intelligence research across various applications. They represent diverse countries and are connected to different academic communities, which will enhance the visibility of the symposium. Their broad network will also contribute to positioning ’Human-AI collaboration’ as a truly interdisciplinary field.
[email protected], University of Marseilles – France
Mohamed Quafafou is a professor, exceptional class, of computer science at Aix-Marseille University.For more than 25 years, he developed research on human learning, machine learning, web information extraction, and other topics. He led the development of the first French web mining system to discover emergent web communities. With French Agency of Artificial Intelligence, he proposed a research theme intitled “Human-Machine Interaction in Machine Learning” and animated a nationalresearch group on this topic from 1997 to 2002. He also developed research on Artificial Intelligence in Education proposing methods and algorithms for human-learning strategies, intelligent system for computer-aided education, and adapting the tutoring interaction to changing student interest. His current research is mainly on Perception in Human-AI Symbiosis with application to AI in education, projects management and predictive maintenance, considering the impact of human interaction and collaboration. He is the head of the research group Data Mining at Scale at LIS-CNRS, Aix-Marseille University and he is member of the International Advisory Board of Udayana University, Indonesia.
[email protected], University of Derby – UK
Farid Meziane is a professor of Data Science, Head of the Data Science Research Centre, the University’s lead for the Data Science academic research theme at the University of Derby, UK. He obtained a PhD in Computer Science from 4 the University of Salford, UK on his work on producing formal specification from Natural Language requirements. The work was considered at that time as pioneering in the area and paved the way for a large interest in automating the production of software specifications from informal requirements. He has authored over 200 scientific papers and participated in many national and international research projects. He is the co-chair of the international conference on application of Natural Language to information systems; co-chair of the international conference on Information Science and Systems. He is serving in the programme committee of over ten international conferences. He is an associate editor for the data and knowledge engineering (Elsevier) journal and the managing editor of the International Journal of Information Technology and Web Engineering. He was awarded the Highly Commended Award from the Literati Club, 2001 for his paper on Intelligent Systems in Manufacturing: Current Development and Future Prospects. His research expertise includes Natural Language processing, semantic computing, data mining and big data and knowledge Engineering.
[email protected], Heriot-Watt University – Dubai.
He is Associate Professor and Associate Director of Research at the School of Mathematical and Computer Sciences in Heriot-Watt University Dubai (HWUD). His combined experience in academia spans a total of 30 years across France, the UK, Malaysia and currently the UAE. His research interests mainly lie in the areas of Artificial Intelligence, Machine Learning, Medical Imaging, and Computer Vision. Throughout his academic career, has led large national and international research projects. He also organised workshops and conferences in his area. He is founder, regular orgniser and member of steering group of the ”International Conference on Digital Health Technologies”. He is reviewer to several journals in the field ”IEEE Image Processing”, ”Elsevier Digital Signal Processing”, ”Springer Signal Image and Video Processing”, and member of programme committes for many International conferences. He authored more than 160 papers and supervised 20 PhDs.