CHIIR 2026 第一届面向交互式信息获取的以人为中心的主动式与个性化智能体研讨会报告
Report on The 1st Workshop on Human-Centered Proactive and Personalized Agents for Interactive Information Access at CHIIR 2026
浏览论文内容
中文总结 AI 辅助
该报告总结了CHIIR 2026第一届相关研讨会，探讨交互式信息获取向主动个性化智能体转变的机遇与问题，明确主动的核心内涵并梳理出相关设计挑战。
中文摘要 AI 辅助
交互式信息获取正日益从被动的查询-响应范式转向智能体系统，这类系统可实现交互个性化、保留上下文、推断潜在需求、推荐后续步骤并主动提供支持。这一转变为自适应且感知上下文的辅助带来了新机遇，同时也引发了关于自主性、隐私、信任、透明度、用户福祉及评估的重要问题。第一届面向交互式信息获取的以人为中心的主动式与个性化智能体研讨会提供了一个跨学科论坛，用于在信息检索、人机交互、对话系统、AI伦理、认知科学、学习技术及以人为中心的AI领域探讨这些问题。通过特邀报告、论文展示和公开讨论，研讨会探讨的主题包括：校准后的主动性、知识缺口导航、长期记忆、价值敏感设计、隐式个性化、AI介导的关怀、主动式对话以及超越任务准确率的评估。研讨会的核心主题是，主动性不应仅被理解为更早的行动或更优的预测，而应是一种必须时机恰当、透明、可被质疑且与用户目标一致的主动形式。本报告总结了该研讨会，并综合了其揭示的交互式信息获取领域中主动式与个性化智能体设计所面临的研究挑战。
英文摘要
Interactive information access is increasingly moving beyond reactive query-response paradigms toward agentic systems that can personalize interaction, retain context, infer latent needs, recommend next steps, and initiate support. This shift creates new opportunities for adaptive and context-aware assistance, while also raising important questions about autonomy, privacy, trust, transparency, user welfare, and evaluation. The First Workshop on Human-Centered Proactive and Personalized Agents for Interactive Information Access provided an interdisciplinary forum for examining these questions across information retrieval, human-computer interaction, dialogue systems, AI ethics, cognitive science, learning technologies, and human-centered AI. Through invited talks, paper presentations, and open discussion, the workshop engaged with topics including calibrated initiative, knowledge-gap navigation, long-term memory, value-sensitive design, implicit personalization, AI-mediated care, proactive dialogue, and evaluation beyond task accuracy. A central theme across the workshop was that proactivity should not be understood only as earlier action or improved prediction, but as a form of initiative that must be appropriately timed, transparent, contestable, and aligned with user goals. This report summarizes the workshop and synthesizes the research challenges it surfaced for designing proactive and personalized agents in interactive information access.
