10.3390/systems11120561">
 

Document Type

Article

Publication Date

11-29-2023

Abstract

This research addresses the data overload faced by intelligence searchers in government and defense agencies. The study leverages methods from the Cognitive Systems Engineering (CSE) literature to generate insights into the intelligence search work domain. These insights are applied to a supporting concept and requirements for designing and evaluating a human-AI agent team specifically for intelligence search tasks. Domain analysis reveals the dynamic nature of the ‘value structure’, a term that describes the evolving set of criteria governing the intelligence search process. Additionally, domain insight provides details for search aggregation and conceptual spaces from which the value structure could be efficiently applied for intelligence search. Support system designs that leverage these findings may enable an intelligence searcher to interact with and understand data at more abstract levels to improve task efficiency. Additionally, new system designs can support the searcher by facilitating an ‘Ambient Awareness’ of non-selected objects in a large data field through relevant system cues. Ambient Awareness achieved through the supporting concept and AI teaming has the potential to address the data overload problem while increasing the breadth and depth of search coverage.

Comments

©2023 by The Authors

This article is published by MDPI, licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Source Publication

Systems (eISSN: 2079-8954)

Share

COinS