Recommender Systems (RS) influence everyday decisions, yet most remain optimized for short-term engagement or commercial gain. RS4SD: Workshop on Recommender Systems for Sustainable Development using responsible nudging aims to reorient this focus by exploring how RS can promote sustainable development through behavioral change and nudging strategies. Aligned with the UN Sustainable Development Goals (SDGs), RS4SD will highlight RS applications that encourage responsible consumption, sustainable mobility, healthy eating, and digital well-being. Particularly, we focus on how AI and RS can be designed to promote sustainable behaviors through multi-objective/criteria optimization and ethically aligned interventions. All contributions aligned with the UN SDGs are welcome.

A central theme is the integration of behavioral science and AI to design interventions that guide users toward more sustainable and healthier choices—without compromising autonomy. RS4SD brings together researchers and practitioners from RS, AI, sustainability, and behavioral science to share models, datasets, frameworks, and real-world use cases. The workshop encourages interdisciplinary collaboration and aims to build a community dedicated to responsible, behavior-aware RS that benefit both individuals and society.

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Submission Guidelines

The Recommender Systems for Sustainable Development through Responsible Nudging (RS4SD) workshop explores how recommender systems (RS) can be reoriented as tools for social good, shifting away from short-term engagement toward long-term sustainability, well-being, and ethical influence. Rooted in the United Nations Sustainable Development Goals (SDG), the workshop welcomes contributions that integrate AI, behavioral science, and personalization to drive responsible consumption, sustainable mobility, health-aware decision-making, and digital well-being. RS4SD aims to bring together researchers, practitioners, and interdisciplinary thinkers to share algorithms, models, datasets, and real-world applications that promote sustainable behaviors through multi-objective optimization and ethically aligned interventions.

Submission Types

We welcome the following types of submissions:

• Full Research Papers (up to 9 pages, excluding references): Present mature, original research with validated results.
• Short Papers / Work-in-Progress (up to 6 pages, excluding references): Present early-stage ideas, prototypes, or findings.
• Vision / Position Papers (4–6 pages, excluding references): Present provocative ideas, future directions, or thought leadership.
• Demo Papers (up to 4 pages, excluding references): Showcase system prototypes, software tools, or datasets.
• Extended Abstracts (up to 2 pages, excluding references): Include experience sharing, novel concepts, or preliminary results. Prior or concurrently submitted work is also accepted under this category (non-archival).

List of Topics

• Recommender Systems aligned with the UN Sustainable Development Goals (SDGs)
• Multi-objective RS: balancing user preferences with sustainability, health, and societal impact
• Behavior-aware RS: integrating behavioral modeling, nudging strategies, and digital interventions
• Responsible and ethically aligned personalization frameworks
• Domain-specific RS for Sustainability: health-aware food recommendation, eco-conscious consumption, and sustainable travel/mobility (e.g., green product RS, low-carbon tourism)
• Generative AI and LLM-powered explainable RS for behavior influence and social good
• Evaluation metrics beyond accuracy: behavior change, long-term value, environmental and ethical impact
• Real-world case studies and industrial applications in food, mobility, health, and e-commerce
• Energy-efficient RS models: developing recommendation algorithms that minimize computational cost and energy consumption to reduce the carbon footprint of AI systems and support environmental sustainability

Organizing committee

• Mehrdad Rostami, University of Oulu, Finland
• Alexander Felfernig, Graz University of Technology, Austria
• Avishek Anand, Delft University of Technology (TU Delft), Netherlands
• Wolfgang Wörndl, Technical University of Munich, Germany
• Mourad Oussalah, University of Oulu, Finland
• Mahdi Jalili, RMIT University, Australia
• Ashmi Banerjee, Technical University of Munich, Germany

Venue

Workshops will complement the main CIKM conference to be held in Seoul, Korea on November 14, 2025. 

Contact

All questions about submissions should be emailed to: Mehrdad Rostami (mehrdad.rostami@oulu.fi) and Ashmi Banerjee (ashmi.banerjee@tum.de).