Orca让网页像可塑材料一样协同操作，实现跨页面信息的高效探索与整合。
Orca: Browsing at Scale Through User-Driven and AI-Facilitated Orchestration Across Malleable Webpages
- 将网页视为可塑材料，人机协作动态构建浏览器级工作区
- 用户对信息探索的意愿提升，控制感与理解力显著增强
- 适合需要跨页处理复杂信息的研究者与知识工作者
网络活动通常涉及多个网页，但传统浏览器的标签页堆叠难以支持跨页面的信息操作与整合。尽管现有AI系统可实现全自动浏览与信息合成，却常削弱用户自主性并影响上下文理解。本文通过文献分析与迭代设计，提出新型交互原型Orca，利用AI辅助用户在大规模网页间进行探索、操作、组织与综合。关键创新在于将网页视作可塑材料，由人类与AI协同操控，构建动态、灵活的浏览器级工作空间。评估表明，用户在信息搜寻中的主动性增强，对信息环境的掌控力提高，且能更灵活地完成复杂认知任务。
原文摘要 · Abstract (English)
Web-based activities span multiple webpages. However, conventional browsers with stacks of tabs cannot support operating and synthesizing large volumes of information across pages. While recent AI systems enable fully automated web browsing and information synthesis, they often diminish user agency and hinder contextual understanding. We explore how AI could instead augment user interactions with content across webpages and mitigate cognitive and manual efforts. Through literature on information tasks and web browsing challenges, and an iterative design process, we present novel interactions with our prototype web browser, Orca. Leveraging AI, Orca supports user-driven exploration, operation, organization, and synthesis of web content at scale. To enable browsing at scale, webpages are treated as malleable materials that humans and AI can collaboratively manipulate and compose into a malleable, dynamic, and browser-level workspace. Our evaluation revealed an increased "appetite" for information foraging, enhanced control, and more flexible sensemaking across a broader web information landscape.
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