The Air Force is hoping advances in artificial intelligence mean the abundance of data from its aircraft, weapons and satellites will be easier to access and analyze.
"There's certainly a data aspect piece" of artificial intelligence, Air Force Vice Chief of Staff Gen. Stephen "Seve" Wilson said Monday.
"I think we all would agree, maybe, that data is the 'renewable oil' of the 21st century," Wilson said during the Future of War conference hosted by New America and Arizona State University.
"With that data, we have to be able to have the right algorithms that connect the data, and understand the data, to a network. I think the cloud's a part of this, and I think 'compute on the edge' is a part of this," he said, referencing a streamlined approach to avoid stovepiping information flow needed at the speed of war.
- Air Force Needs AI, Better Technology to Gather Intel: Goldfein
- Air Force's New Intelligence Chief Explains Vision for Future of ISR
- Former B-2 Pilot to Air Force: Forget Drone Bombers
But humans will never be totally out of the loop, he said.
When asked by Peter Singer, senior fellow at New America and author of "Ghost Fleet: A Novel of the Next World War," how it could work, Wilson cited Project Maven, an algorithmic approach used to hunt and identify terrorists through video automation, as an example of a good way to leverage future "human-machine teaming."
Wilson said now is the time to accumulate data and "let computers do what computers are good at, and then let humans do what humans are good at. And then figure out the insights."
Ultimately, it will make the service more ready for the future battlefield, he said.
"How can we do things where I can take advantage of autonomous systems that can sense and report back," he said. "We're now looking at how we do that, how do we rapidly experiment and prototype with capabilities using those attributes moving forward."
To go up against capable adversaries such as Russia or China, Wilson said, the Air Force needs a "resilient” satellite network to better sense and provide appropriate effects on a timely scale.
"I need to build a network that connects from geosynchronous orbit all the way to subsurface [for] all of our different platforms," he said.
Wilson gave Elon Musk's Tesla vehicle brand as an example: When a Tesla hits a pothole, it takes into account where the pothole is and its size, among other characteristics. The data is then transferred to the Tesla network for other electric cars to avoid should they take the same road.
"If I can do that there, can I do the same thing in the air? Can I connect all the air vehicles so they're passing relevant information about threat adversaries and build an operating learning system?" he said.
Wilson added, "Can I do that with space? And then can I connect space, to air, to ground, to surface, to subsurface?"
Chief of Staff Gen. David Goldfein has also been advancing ideas of a networked approach, not just in Air Force technologies but in platforms that can be shared with coalition partners.
Goldfein has said automation can help streamline copious amounts of information.
"We all know there's a significant [amount] of data that we collect that hits the floor that we never actually look at because we don't have the analytical capacity ... to look at it," he said last year during an Air Force Association breakfast in Washington, D.C.
"What all the services are heavily leveraging -- and looking at industry as well for support -- is how do I take that very human-centric methodology that we have today and use artificial intelligence that uses automation, that uses some of the tools that are available, to be able to do that kind of analysis?" Goldfein said.
Last February, Military.com spoke with Lt. Gen. VeraLinn "Dash" Jamieson, the service's deputy chief of staff for intelligence, surveillance and reconnaissance on the Air Staff at the Pentagon, known as the A2. She is spearheading service efforts she believes will take intelligence gathering into the future.
"Before you get to artificial intelligence, you have to get to automation, and what does that mean? It means we're really developing algorithms, so we then have to build trust in the algorithms," Jamieson said during an interview.
She added, "Artificial intelligence is really going to be linked with human and machine getting me to projections, and where it can go to [narrow down] 20 billion faces, let's say, to the one in a nanosecond."
-- Oriana Pawlyk can be reached at firstname.lastname@example.org. Follow her on Twitter at @Oriana0214.