Recommender Systems and Sustainability: Bridging Algorithmic Design and Societal Impact

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As outlined by the United Nations’ Sustainable Development Goals (SDGs), sustainability is a multidimensional concept aiming to meet present needs without compromising future generations. In this context, Recommender Systems (RS) play a dual role: they can serve as tools to nudge users toward sustainable behaviors (RS for Sustainability) and must themselves be designed to be energy-efficient and fair (Sustainability of RS). While these perspectives are crucial, current literature often addresses them in isolation. This tutorial provides a comprehensive and systematic review of this dual perspective, distinguishing between systems that promote SDGs and those that embed sustainability principles into their design. We offer a taxonomy classifying works across social, environmental, and economic pillars and outline a roadmap for developing holistic RS that use multi-objective optimization to balance performance with ethical and environmental costs. The material is available here https://sustainablerecsys.github.io/SustainabilityTutorial26/.