As many of us in the information retrieval (IR) research community know and appreciate, search is far from being a solved problem. Millions of people struggle with tasks on search engines every day. Often, their struggles relate to the intrinsic complexity of their task and the failure of search systems to fully understand the task and serve relevant results. The task motivates the search, creating the gap/problematic situation that searchers attempt to bridge/resolve and drives search behavior as they work through different task facets. Complex search tasks require more than support for rudimentary fact finding or re-finding. Research on methods to support complex tasks includes work on generating query and website suggestions, personalizing and contextualizing search, and developing new search experiences, including those that span time and space. The recent emergence of generative artificial intelligence (AI) and the arrival of assistive agents, or copilots, based on this technology, has the potential to offer further assistance to searchers, especially those engaged in complex tasks. There are profound implications from these advances for the design of intelligent systems and for the future of search itself. This article, based on a keynote by the author at the 2023 ACM SIGIR Conference, explores these issues and charts a course toward new horizons in information access guided by AI copilots.

翻译：正如我们信息检索（IR）研究界的许多人深知并欣赏的那样，搜索远非一个已解决的问题。每天数以百万计的用户在使用搜索引擎时遇到困难。通常，这些困难源于用户任务本身的内在复杂性，以及搜索系统未能充分理解任务并呈现相关结果。任务驱动着搜索行为，它引发了用户试图弥合/解决的差距/问题情境，并在用户处理不同任务层面时驱动着搜索行为。复杂搜索任务需要的不仅是支持基础的事实查找或重新查找。关于支持复杂任务方法的研究包括：生成查询和网站建议、个性化和情境化搜索、以及开发新的搜索体验（包括跨越时间和空间的体验）。最近生成式人工智能（AI）的出现，以及基于此技术的辅助代理（或称“副驾”）的诞生，有潜力为搜索用户（尤其是从事复杂任务的用户）提供进一步帮助。这些进展对智能系统的设计以及搜索本身的未来具有深远的影响。本文基于作者在2023年ACM SIGIR会议上的主旨演讲，探讨了这些问题，并规划了一条在AI副驾引导下迈向信息获取新前沿的路径。