让推荐系统更懂人，关注信任、公平与福祉
The 2nd Workshop on Human-Centered Recommender Systems
- 从点击率转向理解人类价值，重构推荐逻辑
- 聚焦信任、安全、公平等人类核心需求
- 适合关注AI伦理与人机协同的研究者
推荐系统影响人们获取信息、形成观点及社会连接的方式。随着其影响力扩大，传统指标如准确率、点击量和参与度已无法反映对人类真正重要的方面。第二届以人为本的推荐系统研讨会（HCRS）呼吁从追求用户参与转向设计真正理解、融入并造福人类的系统。会议汇聚推荐系统、人机交互、AI安全与社会计算等领域研究者，探讨如何将信任、安全、公平、透明与福祉等人类价值观融入推荐过程。围绕‘人类理解’、‘人类参与’与‘人类影响’三大主题，涵盖基于大语言模型的交互式推荐、社会福祉优化等议题。通过促进跨学科协作，HCRS旨在引领未来十年负责任且以人为本的推荐研究方向。
原文摘要 · Abstract (English)
Recommender systems shape how people discover information, form opinions, and connect with society. Yet, as their influence grows, traditional metrics, e.g., accuracy, clicks, and engagement, no longer capture what truly matters to humans. The workshop on Human-Centered Recommender Systems (HCRS) calls for a paradigm shift from optimizing engagement toward designing systems that truly understand, involve, and benefit people. It brings together researchers in recommender systems, human-computer interaction, AI safety, and social computing to explore how human values, e.g., trust, safety, fairness, transparency, and well-being, can be integrated into recommendation processes. Centered around three thematic axes-Human Understanding, Human Involvement, and Human Impact-HCRS features keynotes, panels, and papers covering topics from LLM-based interactive recommenders to societal welfare optimization. By fostering interdisciplinary collaboration, HCRS aims to shape the next decade of responsible and human-aligned recommendation research.
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