Advancing the Search Frontier with AI Agents

The IR and information science communities have long studied tasks in search26 and many information-seeking models consider the role of tasks directly.3,11 Prior research has explored the different stages of task execution (for example, pre-focus, focus formation, post-focus), task levels, task facets, tasks defined on intents (for example, informational, transactional, and navigational; well-defined or ill-defined; and lookup, learn, or investigate), the hierarchical structure of tasks, the characteristics of tasks, the attributes of task-searcher interaction (for example, task difficulty), and, a focus of this article, task complexity.8 As a useful framing device to help conceptualize tasks and develop system support for them, tasks can be represented as trees comprising macrotasks (high-level goals), subtasks (specific components of those goals), and actions (specific steps taken by searchers toward the completion of those components).26 Figure 1 presents an example of a "task tree" for a task involving an upcoming vacation to Paris. Included are examples of macrotasks, subtasks, and actions.