Contexty: Capturing and Organizing In-situ Thoughts for Context-Aware AI Support

TL;DR

Contexty is a system that captures users' in-situ cognitive traces during complex tasks, enabling better organization and refinement of context for AI support, thereby improving task awareness and user control.

Contribution

The paper introduces Contexty, a novel system that captures, organizes, and allows users to refine in-situ cognitive context to enhance AI collaboration during knowledge work.

Findings

Contexty improved users' task awareness and thought structuring.

Participants preferred snippet-grounded AI responses over non-grounded ones (78.1%).

Capturing cognitive traces supports AI as a context-aware collaborator.

Abstract

During complex knowledge work, people engage in iterative sensemaking: interpreting information, connecting ideas, and refining their understanding. Yet in current human-AI collaboration, these cognitive processes are difficult to share and organize for AI. They arise in situ and are rarely captured without interrupting the task, and even when expressed, remain scattered or reduced to system-generated summaries that fail to reflect users' cognitive processes. We address this challenge by enabling AI context that is grounded in users' cognitive traces and can be directly inspected and revised by the user. We first explore this through a probe system that supports in-situ snippet memoing, allowing users to easily share their cognitive moves. Our study (N=10) highlights the value of capturing such context and the challenge of organizing it once accumulated. We then present Contexty, which supports users in inspecting and refining these contexts to better reflect their understanding of the task. Our evaluation (N=12) showed that Contexty improved task awareness, thought structuring, and users' sense of authorship and control, with participants preferring snippet-grounded AI responses over non-grounded ones (78.1%). We discuss how capturing and organizing users' cognitive context enables AI as a context-aware collaborator while preserving user agency.