Supporting Representation Management in Intelligence Analysis through Automated Decision Aids

摘要

Intelligence analysts—overloaded with complex and disparate data—must incorporate information intocohesive and convincing narratives and explanations. For analysts, data overload can result in developingpremature conclusions and limit their ability to effectively conduct comprehensive analyses. Historically,automated decision aids designed to help with these processes have largely failed analysts in managing afundamental work tradeoff between analytic narrowing and broadening because software tools too oftenattempt to supplant analyst reasoning, rather than support the iterative process as a whole. Instead of suchbrittle approaches, previous research suggests analysts would benefit from automation that supports a collaborativepartnership throughout the analysis process. The research and development described in thiswork began with a cognitive analysis of practicing analysts, entailing literature review, interviews, andwalkthroughs with a software prototype. Findings from the cognitive analysis were translated into designrequirements for decision aids that support representation management across multiple intelligence products.The findings provide insight into under-supported cognitive and collaborative work in modern intelligenceanalysis with implications for the future design of useful automated decision aids.