Requirements Elicitation for Memory Preserving User Interfaces

Abstract

Through semi-structured interviews with analysts, this project aims to identify key requirements and desired features for user interface designs that support analyst memory traces. By investigating analysts’ current memory strategies and gathering their insights on pain points and opportunities for improvement, the work seeks to collect valuable input directly from the analysts. These findings highlight important considerations for creating user interfaces that better align with analysts’ cognitive processes and enhance their workflow. More specifically, this project identified the need for personalized memory supports and robust documentation systems that capture detailed information and provide context to aid memory retention and recall. Additionally, the collaborative nature of analytic work necessitates appropriately effortful documentation methods to prevent memory-related information loss. Lastly, the work suggests that analysts are open to using AI as a dynamic teammate to reduce cognitive load and support memory, provided they have access to the relevant information and the opportunity to understand the AI’s reasoning.