用推荐系统助力可持续发展目标，推动环保与社会公平
Recommender Systems for Sustainability: Overview and Research Issues
- 融合机器学习与可解释AI，智能推荐可持续选项
- 覆盖扶贫、环保等多领域，支持多元目标实现
- 适合关注AI与社会可持续性的研究者与实践者
可持续发展目标（SDGs）被视为全球共同行动的号召，旨在保护地球、消除贫困并确保所有人享有和平与繁荣。为实现这些目标，人工智能技术发挥关键作用。推荐系统通过整合机器学习、可解释AI（XAI）、基于案例推理和约束求解等技术，从大量选项中发现并解释对用户相关的替代方案，支持组织与个人达成可持续发展目标。本文综述了推荐系统在支持可持续发展目标方面的最新进展，并探讨未来研究中的开放性问题。
原文摘要 · Abstract (English)
Sustainability development goals (SDGs) are regarded as a universal call to action with the overall objectives of planet protection, ending of poverty, and ensuring peace and prosperity for all people. In order to achieve these objectives, different AI technologies play a major role. Specifically, recommender systems can provide support for organizations and individuals to achieve the defined goals. Recommender systems integrate AI technologies such as machine learning, explainable AI (XAI), case-based reasoning, and constraint solving in order to find and explain user-relevant alternatives from a potentially large set of options. In this article, we summarize the state of the art in applying recommender systems to support the achievement of sustainability development goals. In this context, we discuss open issues for future research.
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