Organizers: Peter Brusilovsky (University of Pittsburgh), Marco de Gemmis (University of Bari), Alexander Felfernig (TU Graz), Marco Polignano (University of Bari), Giovanni Semeraro (University of Bari) and Martijn Willemsen (Eindhoven University of Technology)

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Recent research on Human-AI collaboration involves several critical areas of investigation, such as Human-in-the-loop, Symbiotic AI, Explainable AI, User-centered design, and Intelligent Interfaces. Overall, this area of research is aimed at developing systems that can work effectively with human users, considering their preferences, cognitive abilities, and ethical values. They should be transparent, interpretable, adaptable, and respectful of the user’s autonomy and privacy. The ultimate goal is to develop recommender systems that can support the user’s decision-making process, enhance their well-being, and promote social good. This means respecting cultural, social, and individual differences when crafting recommendations. Inclusive design translates to recommendations that truly represent the diverse individuals who use these systems. Human-AI collaboration and Human-Centered AI are pivotal in the development of recommender systems.