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 it and serve relevant results.38 The task motivates the search, creating the problem that searchers attempt to solve, 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,15 personalizing and contextualizing search,4 and developing new search experiences, including those that span time and space.1,40 The recent emergence of generative artificial intelligence and the arrival of assistive agents based on this technology have the potential to offer further assistance to searchers, especially those engaged in complex tasks. These advances have profound implications for the design of intelligent systems and for the future of search itself. This article, based on a keynote given by the author at the 2023 ACM SIGIR conference, explores these issues and how AI agents are advancing the frontier of search-system capabilities, with a special focus on information interaction and complex task completion.
