揭示智能体与人沟通的12大挑战,助力更透明可控的交互设计。
Challenges in Human-Agent Communication
- 从沟通接地视角系统梳理人机交互中的核心难题
- 识别出信息传递、用户反馈与整体协调三类共12个关键挑战
- 为提升智能体透明度与可控性提供研究方向和设计指引
现代生成式基础模型推动了高度自主智能体的发展,它们能感知环境、调用工具并与其他智能体协作解决问题。尽管这些智能体可通过自然语言与用户交互,但其复杂性和多样化的失效模式带来了全新的挑战。基于前期研究和沟通接地理论,本文系统识别并分析了12项关键的人机沟通挑战,涵盖智能体向用户传递信息、用户向智能体传达信息,以及贯穿所有交互场景的总体性难题。通过具体案例说明每项挑战,并指出开放的研究方向。研究揭示了当前人机沟通研究中的关键空白,呼吁建立新的设计模式、原则与指南,以增强系统的透明性与可控制性。
原文摘要 · Abstract (English)
Remarkable advancements in modern generative foundation models have enabled the development of sophisticated and highly capable autonomous agents that can observe their environment, invoke tools, and communicate with other agents to solve problems. Although such agents can communicate with users through natural language, their complexity and wide-ranging failure modes present novel challenges for human-AI interaction. Building on prior research and informed by a communication grounding perspective, we contribute to the study of \emph{human-agent communication} by identifying and analyzing twelve key communication challenges that these systems pose. These include challenges in conveying information from the agent to the user, challenges in enabling the user to convey information to the agent, and overarching challenges that need to be considered across all human-agent communication. We illustrate each challenge through concrete examples and identify open directions of research. Our findings provide insights into critical gaps in human-agent communication research and serve as an urgent call for new design patterns, principles, and guidelines to support transparency and control in these systems.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。