Accelerating Workforce Training: Introducing the CTA in E/Affect Initiative

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Criminal Justice

Providing a foundation for interpretable autonomous agents through elicitation and modeling of criminal investigation pathways

Sub-domain:

Intelligence analysts

CTA Method(s):

Critical Decision Method

Application(s):

Technology

Publication Year:

2020

Lead Author:

Sam Hepenstal

Description:

Cognitive task analysis conducted to understand how criminal intelligence analysts question data as they sought to retrieve information to advance their investigations, specifically how questions lead to insights that triggered subsequent inquiries. Researchers interviewed four criminal intelligence analysts to generate an event tree simplified into a graph that serves as a foundation for transparant artificial intelligence autonomous investigations.

Full Reference:

Hepenstal, S., Zhang, L., Kodogoda, N., & Wong, B. L. W. (2020). Providing a foundation for interpretable autonomous agents through elicitation and modeling of criminal investigation pathways. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 64, 239-243. https://doi.org/10.1177/1071181320641057

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