Alan Said: Recommender Systems in Tourism through a Fair and Sustainable Lens

Abstract: Recommender systems increasingly shape how people travel – what destinations are visited, where to stay, and which experiences to choose. These decisions carry significant environmental, social, and cultural consequences, from carbon emissions and over-tourism to the survival of local communities. This talk examines recommender systems in tourism through a fair and sustainable lens, highlighting the challenges of accountability, fairness, and transparency in guiding responsible travel choices. Drawing on a framework for tangible recommendations, it frames tourism recommendations as not just digital suggestions but embodied decisions with lasting consequences. The talk outlines pathways toward accountability-aware, fair, and consequence-sensitive recommender design that can support more sustainable and responsible forms of tourism.

Biography: Alan Said is an Associate Professor of Computer Science at the University of Gothenburg, Sweden, specializing in human-centered AI, recommender systems, user modeling, and AI sustainability. His research spans machine learning theory, health applications, personalization, and interdisciplinary work on fairness, transparency, and environmental impact. He earned his Ph.D. from TU Berlin on recommender system evaluation and held Marie Curie Fellowships at CWI and TU Delft, alongside industry roles in applied ML. Author of 100+ publications, he has received awards including the Springer Best Paper Award at UMAP. Said serves as ACM RecSys Steering Committee Chair and in multiple editorial and leadership roles.