通过众包和结构化分析技术改进分析推理

IF 2.2 Q3 ENGINEERING, INDUSTRIAL Journal of Cognitive Engineering and Decision Making Pub Date : 2020-08-17 DOI:10.1177/1555343420926287
T. van Gelder, Ariel Kruger, Sujai Thomman, Richard de Rozario, Elizabeth Silver, Morgan Saletta, Ashley Barnett, R. Sinnott, G. Jayaputera, M. Burgman
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引用次数: 6

摘要

如何实质性地改进情报报告中的分析推理?一种推测是,这可以通过众包和结构化分析技术(SAT)的结合来实现。为了探索这一猜测,我们开发了一个新的众包平台,支持团队使用一种新的SAT进行协作推理和情报报告起草,我们称之为“竞争分析”。“在这篇论文中,我们介绍了一项大型研究的结果,该研究旨在评估在平台上工作的专业分析师群体在使用其组织中通常使用的方法和工具时,是否会产生比这些分析师更合理的报告。次要问题是,在该平台上工作的专业分析师是否比在该平台工作的普通公众产生了更好的推理;以及平台的可用性。我们的主要发现是有利于在平台上工作的大效应大小(Cohen的d=1.37)。这为一般猜想提供了早期的支持。我们讨论了我们研究的局限性,对情报机构的影响,以及整个工作的未来方向。
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Improving Analytic Reasoning via Crowdsourcing and Structured Analytic Techniques
How might analytic reasoning in intelligence reports be substantially improved? One conjecture is that this can be achieved through a combination of crowdsourcing and structured analytic techniques (SATs). To explore this conjecture, we developed a new crowdsourcing platform supporting groups in collaborative reasoning and intelligence report drafting using a novel SAT we call “Contending Analyses.” In this paper we present findings from a large study designed to assess whether groups of professional analysts working on the platform produce better-reasoned reports than those analysts produce when using methods and tools normally used in their organizations. Secondary questions were whether professional analysts working on the platform produce better reasoning than the general public working on the platform; and how usable the platform is. Our main finding is a large effect size (Cohen’s d = 1.37) in favor of working on platform. This provides early support for the general conjecture. We discuss limitations of our study, implications for intelligence organizations, and future directions for the work as a whole.
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来源期刊
CiteScore
4.60
自引率
10.00%
发文量
21
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