Warrior Maven Interview: Col. Douglas Matty - Army Artificial Intelligence Task Force Deputy Director

Warrior Maven: What is the primary purpose of the Army’s AI Task Force?

Matty: The Army AI Task Force was established with a Secretary of the Army directive in October of 2018. There are four thrusts or top initiatives from the Secretary’s directive. One component is we are leveraging AI to help our talent management in human resources. Our most valuable asset is our people. The second is our partnership with DoD with regard to our efforts, including an Army-led predictive maintenance effort. We are looking to apply AI toward predictive maintenance, specifically targeting the H-60 Black Hawk. The third is focusing on the Army’s top modernization priorities, which includes long-range precision fires. The fourth effort is looking at our Next Generation Combat Vehicle.

Warrior Maven: What are some of the Ways the AI Task Force Functions?

Matty: We are working under Army Futures Command (AFC) which was established in July 2018. They have focused on modernization efforts including Cross Functional Teams. We are looking at how we tap into an AI hub comprised of other elements of AFC -- the CCDC (Combat Capabilities Development Command). We are located at Carnegie Mellon, which is a world leader in AI and partner with other top universities to leverage their technical expertise for technology development and also working with other partners from industry. In addition to the Army labs, we are leveraging FFRDCs (Federally Funded Research and Development Center) such as the software engineering institute here at Carnegie Mellon.

Warrior: What are some of the key areas of focus?

Matty: We seek to draw upon cutting edge technology to explore the realm of the possible through partnerships working on transitioning the technologies. We are working through an initial set of mission analysis with the CFT. We are now aligning these efforts with research opportunities. We are working through an initial set of mission analyses with the CFTs. We are supporting two of the eight CFTs and looking ahead to the next 2 years, working to understand the mission space of the remaining CFTs and enhance their abilities.

Warrior: I understand the AI Task Force is working on Predictive Maintenance?

Matty: The Army has led a Conditioned-Based Maintenance effort for the last 15 years, looking at the appropriate sensors to collect data on the appropriate platforms. How can these be analyzed to understand maintenance status? This includes developing new algorithms and interfaces for maintenance and mechanics to address supply chain and logistics challenges and take advantage of recently-available data assets. The Army has pilot programs, I.e. Bradley. We are currently working on the H-60 and several other platforms in conjunction with the acquisition community and the AMC (Army Materiel Command).

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Warrior: What is the AI approach with the Black Hawks?

Matty: Helicopters are a vital part of our force structure, but aviation equipment is resource and maintenance intense. We are able to leverage expertise to develop and refine algorithms. We can get to the granular level of specificity, not just for the fleet but eventually for tail numbers. We are working to refine the analytics and machine learning to not only increase the specificity but also improve the time horizon to predict when maintenance needs will occur.

Warrior: How are your AI programs merging with real-time analytics?

Matty: AI is not just the algorithms but it also requires integrating a number of aspects. Our developments form an “AI Stack” regarding how we pull together the sensors, computing layer and analytics to manage the data and enhance systems support. This makes a recommendation for handling supply chain mechanisms to enhance the readiness of the fleet. With the H-60 we are able to pull together the modeling layers for capabilities to integrate with the acquisition details and the supply chain. We are building out the rest of the stack to engage a broader system of systems to support operations.

Warrior: How would you describe the impact of these Predictive Maintenance efforts?

Matty: The goal of this varies. First and foremost, we want to enhance readiness because that translates into mission success. There are sensors on board that are generating the data for analysis. As we flush out the rest of the stack, we will look for where analytics needs to be done. We take an iterative approach to find when platforms will be available for their mission. Some of what we may look at are UAS as we scale across platform; we are looking to enhance a crew’s ability to perform missions.

Warrior: What is the focus with the Next-Gen Combat Vehicle?

Matty: We are focusing on the Next Gen Combat Vehicle. As you know they are progressing with two different platforms - the optionally-manned vehicle and the robotic combat vehicle. How do we have AI-aided threat recognition? We have to be aware of how robotic and manned vehicles share information to conduct operations. We are working on prototypes and expect to have an integrated threat recognition sensor package in a January timeframe. We have mapped out the trade space to explore what this would look like. We are excited about what we are doing.

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Warrior: Where do some of these things stand in the developmental process?

Matty: There are a number of demos and research efforts which have been underway in Michigan Aberdeen Proving Grounds and Picatinny Arsenal. For a number of years, we have had semi-autonomous technology such as leader-follower systems. Now we are taking it to the next level where you have operationally relevant autonomy so things can maneuver in combat. This is what the warfighters and operational leaders excited because we see the potential with regard to multi-domain ops where we are changing things doctrinally. These are super challenging when it comes to merging passive and active entities to understand how systems would function in autonomous operations such as maneuver.

Warrior: I understand combining multiple sensors into a single “box” is a large benefit of AI?

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Matty: We are working on sensor consolidation. For fire control there are a number of processes that are conducted in advance of finding the entities that you want to generate effects on. How do we leverage enhanced capabilities based on longer-range types of systems and overhead commercial imagery or UAS so we can rapidly perform PED (Processing, Exploitation, Dissemination)? We are looking to leverage this with the CFT working on long-range precision fires using advanced capabilities like those developed in support of project MAVEN. MAVEN is focused upon supporting intel ops within DoD. With long-range fires, we are looking at how we extend the operational battlespace. We can enhance data sets using AI to generate and extract vital information to support combat against mission threats.