How AI can alter multi-domain warfare

Attend our webinar on AI/ML and the future battlefield

Military commanders often have very little time to make decisions – sometimes just seconds. And with threats like hypersonic missiles accelerating the pace of modern warfare, that window of time is shrinking.

Complicating things is the sheer volume of data flow. There are petabytes of intelligence information coming from sensors on land, at sea, in the air and in space, many using different formats.

The solution, according to experts at Raytheon Intelligence & Space, a Raytheon Technologies business, is clear: Artificial intelligence – specifically, teaming military commanders with intelligent systems to cull through data in seconds. This will be key to bringing the vision for the U.S. Department of Defense’s Joint All Domain Command and Control network, often called JADC2, to reality. That network will link military capabilities around the world and in every domain. 

With artificial intelligence and machine learning, those systems can define, combine and provide the right information to the right people at the right time – giving them the best possible chance to make the best possible decision.

“Manually processing all that data would require armies of analysts, but with AI/ML, we can task systems to cull through the data and produce higher level information useful to operators,” said Jim Wright, RI&S technical director for Intelligence, Surveillance and Reconnaissance Systems.

Experts from Raytheon Intelligence & Space discussed the concept further during a webinar on July 15, 2021 that is now available on-demand. Here’s a preview of what they discussed.

1. AI/ML makes sense of the complex

There’s a confluence of factors that are driving the need for autonomy and automation in data analysis – a proliferation of information and a shortage of analysts to start. AI and ML can help by doing the legwork – searching, processing and fusing larger amounts of data across the domains – and helping the humans save their brainpower for decision-making.

“A customer once told me that the military collects 22 football seasons worth of video every day,” Wright said. “There’s a colossal amount of information circling in today’s battlespace. We’re developing smart software, called Cognitive Aids to Sensor Processing, Exploitation and Response, to lighten the operator’s workload and use automation to help make decisions faster. The cognitive aids will do the groundwork and data analysis to provide recommended courses of action, leaving the operators to focus on making the best decision.”

The Department of Defense is also mobilizing combatant commands to use AI/ML for the future battlefield in a new effort called the Artificial Intelligence and Data Acceleration Initiative.

“Its goal is to rapidly advance data and AI-dependent concepts like Joint All-Domain Command Control,” Deputy Secretary of Defense Kathleen Hicks said during the department’s AI Symposium on June 22.

2. AI/ML counters threats more quickly and intelligently

Another factor is the speed of modern weapons.

“Think about hypersonic glide vehicles and similar types of weapons,” Wright said. “From the time you see them to the time when you must counter them is very short, and there isn’t time for operators to search multi-sensor data to optimize targeting solutions. Instead, AI/ML can automatically search across many sensor sources to accurately detect and classify threats, and then quickly evaluate multiple engagement alternatives to find the optimum weapons target pairing.”

AI and ML could even give combatant commanders insights into adversaries’ decision-making processes – information they can use to anticipate enemy actions and proactively outmaneuver them.

“At that point, the adversary won’t be able to respond in time because our commander is already way ahead of them,” said Chris Worley, director for Civil and Digital Solutions at RI&S.

Watch the on-demand webinar

3. AI and ML bring greater efficiency

Although the amount of data in the battlefield and the reliance on it are increasing rapidly, the workforce and budgets for analysts and operator support in intelligence and targeting are not.

Again, AI and ML can help.

“We can team with machine learning and teach it to look at imagery and flag which images that an operator may need to pay attention to,” Worley said. “That’s how we can maintain the same level of effort and resources required before data exploded and still complete the mission.”

Human-machine teaming, enabled by AI/ML technologies, will enable existing staff to access information and produce actionable information more efficiently and effectively.

“It is unrealistic to expect that throwing more personnel at the problem will work, so we need solutions that incorporate AI/ML to minimize their human dependency and allow the operators to concentrate on the big picture and critical information,” said Dr. Michael Fowler, assistant director for Autonomous & Multi-agent Systems at Virginia Tech.

Military officials have been clear in their discussions of AI/ML that they want to use the technology cautiously, and that machine learning isn’t simply going to take over. Rather, they want to use it to help people make better-informed decisions in a timely way.

“We are only at the dawn of what machine learning is going to enable us to do,” Worley said. “It is an inflection point where we’re identifying the realm of the possible. This will grow. This will change. The key is to have an underlying framework of how to approach bringing that into our customer environments. And that’s a partnered