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.

翻译：基于网页的活动通常涉及多个页面。然而，传统浏览器依赖标签页堆叠的方式，难以支持跨页面的大规模信息操作与综合。尽管近期的人工智能系统能够实现全自动的网页浏览与信息综合，但这些系统往往削弱了用户的主观能动性并阻碍对上下文的理解。我们探讨了人工智能应如何增强用户在跨网页内容交互中的能力，并减轻其认知与操作负担。通过对信息任务与网页浏览挑战的相关文献研究，并结合迭代设计过程，我们提出了基于原型网页浏览器Orca的新型交互方式。Orca借助人工智能技术，支持用户驱动的大规模网页内容探索、操作、组织与综合。为实现大规模浏览，网页被视为可塑材料，用户与人工智能可协同对其进行操控，并将其组合成一个位于浏览器层面的、可塑且动态的工作空间。我们的评估表明，该系统能够提升用户在更广泛网络信息空间中进行信息采集的“意愿”，增强其控制能力，并实现更灵活的跨信息感知与理解。