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Versatile and Interpretable System Explanations for AI in Multi-Domain Operations (VISION)

Award Information
Agency: Department of Defense
Branch: Army
Contract: W911NF-22-P-0066
Agency Tracking Number: A22B-T016-0094
Amount: $172,967.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: A22B-T016
Solicitation Number: 22.B
Solicitation Year: 2022
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-09-21
Award End Date (Contract End Date): 2023-03-31
Small Business Information
625 Mount Auburn Street
Cambridge, MA 02138-4555
United States
DUNS: 115243701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jeff Druce
 (617) 491-3474
Business Contact
 Mark Felix
Phone: (617) 491-3474
Research Institution
 Arizona State University
 Ekaterina Khaustova
975 S. Myrtle Ave
Tempe, AZ 85281-1601
United States

 (480) 965-7873
 Nonprofit College or University

As the Army pivots to larger combat operations, the increased scale and complexity of multi-domain operations (MDO) has heightened the difficulty of synchronizing collection and operations across domains. Commanders conducting planning are limited by “human bandwidth,” which can degrade the quality of plans and desynchronize operations. Unfortunately, the policies learned from many current AI approaches are not yet interpretable, meaning planners have no effective way of understanding how decision recommendations are informed by the current situation, future predicted situations, or AI training data. To address this need and improve military planning in MDO using the power of AI systems, Charles River Analytics, in collaboration with Dr. Paulo Shakarian at Arizona State University, propose to design and demonstrate the feasibility of Versatile and Interpretable System Explanations for AI in Multi-Domain Operations (VISION). VISION is an XAI middle layer that provides a suite of techniques to extract comprehensible data representations of the AI system decision space. VISION will realize the full potential of AI systems to aid military planning and MDO by enabling Commanders to better understand the decision-making process behind AI recommendations and how it is predicated on future outcome predictions and past training.

* Information listed above is at the time of submission. *

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