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Partnering with technology: the importance of human machine teaming in future MDC2 systems
Author(s): J. Klamm; C. Dominguez; B. Yost; P. McDermott; M. Lenox
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Paper Abstract

To make progress in applying technological advancements towards multi-domain command and control (MDC2), including user-facing data collection and evaluation is critical but made more difficult by the lack of existing MDC2 systems. To address these challenges, we used a two-pronged approach that blended HMT Systems Engineering (SE) insights on designing user interfaces for artificial intelligence (AI) with MDC2 common operational picture (COP) research. We interviewed C2 operators using modified cognitive task analysis methods and analyzed data via thematic coding. User stories and future concept ideas were created from the interview data. The authors designed and delivered annotated mock-ups to reflect those concepts; they are in process of being incorporated into a software prototype. The designs were iteratively refined based on feedback from operators. The HMT SE guide, future concepts, annotated mockups, and prototypes are being shared with sponsors and used as foundational input for MITRE’s MDC2 exploration environment for FY19 and beyond. Products from this work include insights for how technology should support MDC2 planning and decision making, user stories capturing those insights and mock-up graphical concepts, and a set of design seeds for a future MDC2 Common Operational Picture, including layers, content, and other capabilities towards decision support.

Paper Details

Date Published: 10 May 2019
PDF: 8 pages
Proc. SPIE 11006, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 110060R (10 May 2019); doi: 10.1117/12.2518750
Show Author Affiliations
J. Klamm, The MITRE Corp. (United States)
C. Dominguez, The MITRE Corp. (United States)
B. Yost, The MITRE Corp. (United States)
P. McDermott, The MITRE Corp. (United States)
M. Lenox, The MITRE Corp. (United States)


Published in SPIE Proceedings Vol. 11006:
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications
Tien Pham, Editor(s)

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