AI’s Power to Transform Command and Control

A soldier operates a virtual-reality headset in support of the Advanced Battle Management System.

Air Force photo by Senior Airman Daniel Hernandez

By securely connecting sensors, data, decision-makers and weapons across multiple domains, the Air Force’s Advanced Battle Management System will move warfighters from radios and classified chat capabilities to the ubiquitous connectivity and availability that has long been established in the civilian world. It also offers powerful capabilities for command and control.

Artificial intelligence applications across the systems infrastructure will allow the service to take advantage of today’s sensor proliferation and robust communications paths to synthesize and harmonize data into actionable information at machine speed. This improves command-and-control posture — and, crucially, creates strategic advantages — by enabling new capabilities in information detection, identification and synthesis across multiple domains.

How does this look in practice? Take for example anomalous traffic on a network, like a military patrol vessel sending signals associated with civilian freighters. A human analyst might believe based on traditional intelligence that a civilian freighter was using the route. In this case, the analyst would fail to view the patrol vessel’s signals as a threat.

An AI system, however, would detect underlying traffic patterns. It would more accurately flag the vessel’s signals as a cue to assemble nearby sea and air assets. In this scenario,

AI saw something a human might not have caught and enabled information across domains to respond to the threat faster.

There are more examples of how AI can support command and control at the strategic, tactical and operational levels, enabling commanders to more effectively direct forces and achieve desired actions such as faster and more accurate decision-making.

Warfighters and commanders live by the OODA loop: observe, orient, decide, act. AI shortens and sharpens this decision loop at every step.

The first step, observation, is perhaps the most familiar: how AI processes vast amounts of information faster and more accurately. A human geospatial analyst scanning images for a specific black truck is limited to observing a single screen. The analyst may take several hours to find that vehicle — and may spot a navy blue SUV by mistake. By contrast, an AI-enabled computer vision system can scan dozens of feeds simultaneously and more accurately identify discrete visual spectrums that the human eye can’t detect.

AI also sharpens the orientation stage of decision-making by exceeding human cognitive limitations and processing speed. For example, an algorithm can train on millions of images in a single day; whereas a human analyst would be trained through months of coursework and likely still not accumulate the same number of images. As a result, an algorithm can generalize and process information that it has never seen before more efficiently than a human.

Adding to its decision-making power, AI can predict the outcomes of a potential course of action and evaluate environmental or adversarial variables that would be beyond human capacity to assess. AI offers a capacity for course of action adjudication and dynamic reprioritization for a broader spectrum of risk while “red teaming” courses of action in real time.

At this critical decision step, commanders need to act in a timely fashion with precision and accuracy. Humans are limited in the time they have to read reports, watch data feeds and make connections between disparate inputs and outputs. An AI system, by contrast, can ingest, process and synthesize vastly more information at superhuman speed. This empowers decision-makers with a fuller view of the “ground truth” when they need it.

AI also strengthens the coordination of warfighting functions.

Through its prediction capabilities, the technology enables warfighters to coordinate functions in new and innovative ways.

For example, AI can identify and continue tracking a high-value target even when the target disappears from line of sight — like into a tunnel or behind buildings in a dense urban terrain. By computing using position, heading, speed of travel and similar factors, AI can not only maintain a track but also predict where the target will be 20 minutes from now to proactively mobilize assets.

Now imagine there are two drones in proximity to the target, two and two-and-a-half miles away, respectively. While distance to the target may seem like the primary factor to consider in determining which drone should be employed, AI can calculate a large range of additional factors using predictive maintenance. By using real time data ingestion to understand the fuel gauge, range, time on station and other relevant data points, it could be revealed that the more distant drone will make it to the target faster. In situations like this, AI offers huge potential for the dynamic retasking of assets.

AI can also see ahead of the battlespace. It gives commanders and warfighters the ability to see forward and respond proactively rather than reactively. For example, an analyst receives a pattern-of-life report that indicates an adversarial military asset, like an airplane, has moved from its normal position to a bordering airfield. Human intelligence on the ground confirms this new activity. AI has the potential to connect these traditionally siloed reports and scramble defensive assets while the enemy plane is still on enemy soil, rather than waiting until it is noticed entering friendly airspace.

AI empowers connections between disparate pieces of information. By coalescing data across domains and services into a single place, it makes information more discoverable, for swifter and sharper decisions.

It also allows learning and the application of knowledge across domains. It is particularly well-suited to addressing novel scenarios and changing mission requirements.

Artificial intelligence gives commanders and warfighters a cursory understanding of the environment beyond current capabilities. It filters through vast sums of data to “tip and cue” anomalies. As AI systems process data and “learn,” they then serve as “teachers,” reproducing new AI tangential intersections of similar data elements and creating self-learning clusters. This further reduces time to action for decision-makers and commanders.

Throughout, AI enables action across the collective body. For example, distributing resources and knowledge across multiple nodes for shared situational awareness. This means that something that one node learns can be applied across the entire “hive” in real time, so that lessons learned are immediately applicable, even in seemingly unrelated areas.

Artificial intelligence is an essential tool for the future operating environment. What capabilities will warfighters and commanders need next year, or even next month? Because today’s threat environment is constantly redefined by geopolitical factors, technological response to it must be similarly flexible. The military must evolve past industrial-age thinking to take on an information- and machine-age environment and rather see command and control as a continuously evolving state.

To keep pace and get the most out of this evolving mindset, increased computing powers and other technologies that complement AI, it is essential to adopt more accelerated acquisition processes and tactics, techniques and procedures. Command and control is ready for AI today, and needs to be integrated at a rate commensurate with the technology’s transformative potential.

Today’s operating environment is dominated by complex, nuanced adversaries who have access to the same technology, resources and innovation as the U.S. military. Through the Advanced Battle Management System, the Defense Department has a mechanism to accelerate the innovation and capabilities that keep it ahead of the game, including the artificial intelligence applications that give a sharper view of threats, adversaries, assets and potential actions.

A successful demonstration of ABMS-enabled AI capabilities occurred when the Air Force linked multiple sensors to multiple shooters in near-real time in early September.
Imagine the power of such applications across battlefields and domains as the operating environment continues to evolve.

Wes Haga is senior solutions architect and Courtney Crosby is chief AI solutions architect at Booz Allen Hamilton, which is supporting the Air Force’s ABMS program.

Topics: Robotics and Autonomous Systems