AI助知识工作者整合碎片信息，但需注意控制与透明度
Generative AI in Knowledge Work: Design Implications for Data Navigation and Decision-Making
- 设计可自适应的AI系统，支持用户灵活控制
- 实测发现用户易过度依赖AI，且缺乏协作透明性
- 适合产品管理等需跨平台决策的知识工作场景
对20名知识工作者的研究发现，他们在多平台分散的非结构化信息中难以做出有效决策。基于理想工具愿景，我们开发了Yodeai——一个由AI驱动的系统，探索生成式AI在知识工作中的潜力与局限。通过16名产品经理的用户研究，识别出三项关键需求：可调节的用户控制、透明的协作机制，以及将背景知识与外部信息融合的能力。但同时也发现显著问题：用户对AI过度依赖、个体孤立，以及超出AI处理范围的情境因素。随着AI在职场日益普及，我们提出设计原则：强调适配多样化工作流、个人与协作情境下的责任归属，以及上下文感知的互操作性，以指导面向产品经理和知识工作者的人本化AI系统开发。
原文摘要 · Abstract (English)
Our study of 20 knowledge workers revealed a common challenge: the difficulty of synthesizing unstructured information scattered across multiple platforms to make informed decisions. Drawing on their vision of an ideal knowledge synthesis tool, we developed Yodeai, an AI-enabled system, to explore both the opportunities and limitations of AI in knowledge work. Through a user study with 16 product managers, we identified three key requirements for Generative AI in knowledge work: adaptable user control, transparent collaboration mechanisms, and the ability to integrate background knowledge with external information. However, we also found significant limitations, including overreliance on AI, user isolation, and contextual factors outside the AI's reach. As AI tools become increasingly prevalent in professional settings, we propose design principles that emphasize adaptability to diverse workflows, accountability in personal and collaborative contexts, and context-aware interoperability to guide the development of human-centered AI systems for product managers and knowledge workers.
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