Pentagon getting ambitious about AI
Autonomous lethal weapons just years away
NATIONAL HARBOR, Md. — Artificial intelligence employed by the US military has piloted pint-size surveillance drones in special operations forces’ missions and helped Ukraine in its war against Russia. It tracks soldiers’ fitness, predicts when Air Force planes need maintenance, and helps keep tabs on rivals in space.
The Pentagon is intent on fielding multiple thousands of relatively inexpensive, expendable AI-enabled autonomous vehicles by 2026 to keep pace with China. The ambitious initiative, dubbed Replicator, seeks to “galvanize progress in the too-slow shift of US military innovation to leverage platforms that are small, smart, cheap, and many,” Deputy Secretary of Defense Kathleen Hicks said in August.
While its funding is uncertain and details vague, Replicator is expected to accelerate hard decisions on what AI tech is mature and trustworthy enough to deploy — including on weaponized systems.
There is little dispute among scientists, industry experts, and Pentagon officials that the US will within the next few years have fully autonomous lethal weapons. And though officials insist humans will always be in control, experts say advances in data-processing speed and machine-to-machine communications will inevitably relegate people to supervisory roles.
That’s especially true if, as expected, lethal weapons are deployed en masse in drone swarms. Many countries are working on them — and neither China, Russia, Iran, India, nor Pakistan have signed a US-initiated pledge to use military AI responsibly.
It’s unclear if the Pentagon is formally assessing any fully autonomous lethal weapons system for deployment, as required by a 2012 directive. A Pentagon spokeswoman would not say.
Replicator highlights immense technological and personnel challenges for Pentagon procurement and development as the AI revolution promises to transform how wars are fought.
“The Department of Defense is struggling to adopt the AI developments from the last machine-learning breakthrough,” said Gregory Allen, a former top Pentagon AI official now at the Center for Strategic and International Studies think tank.
The Pentagon’s portfolio boasts more than 800 AI-related unclassified projects, many still in testing. Typically, machinelearning and neural networks are helping humans gain insights and create efficiencies.
“The AI that we’ve got in the Department of Defense right now is heavily leveraged and augments people,” said Missy Cummings, director of George Mason University’s robotics center and a former Navy fighter pilot. “There’s no AI running around on its own. People are using it to try to understand the fog of war better.”
One domain where AI-assisted tools are tracking potential threats is space, the latest frontier in military competition.
China envisions using AI, including on satellites, to “make decisions on who is and isn’t an adversary,” US Space Force chief technology and innovation officer Lisa Costa told an online conference this month.
The US aims to keep pace. An operational prototype called Machina used by Space Force keeps tabs autonomously on more than 40,000 objects in space, orchestrating thousands of data collections nightly with a global telescope network.
Machina’s algorithms marshal telescope sensors. Computer vision and large language models tell them what objects to track. And AI choreographs drawing instantly on astrodynamics and physics datasets, Colonel Wallace “Rhet” Turnbull of Space Systems Command told a conference in August.
Another AI project at Space Force analyzes radar data to detect imminent adversary missile launches, he said.
Elsewhere, AI’s predictive powers help the Air Force keep its fleet aloft, anticipating maintenance needs of some 2,600 aircraft including B-1 bombers and Blackhawk helicopters.
Machine-learning models identify possible failures dozens of hours before they happen, said Tom Siebel, CEO of Silicon Valley-based C3 AI, which has the contract. C3’s tech also models the trajectories of missiles for the US Missile Defense Agency and identifies insider threats in the federal workforce for the Defense Counterintelligence and Security Agency.
Among health-related efforts is a pilot project tracking the fitness of the Army’s entire Third Infantry Division — more than 13,000 soldiers. Predictive modeling and AI help reduce injuries and increase performance, said Major Matt Visser.
In Ukraine, AI provided by the Pentagon and its NATO allies helps thwart Russian aggression.
NATO allies share intelligence from data gathered by satellites, drones, and humans, some aggregated with software from US contractor Palantir. Some data comes from Maven, the Pentagon’s pathfinding AI project now mostly managed by the National Geospatial-Intelligence Agency, say officials including retired Air Force general Jack Shanahan, the inaugural Pentagon AI director.
Maven began in 2017 as an effort to process video from drones in the Middle East – spurred by US Special Operations forces fighting ISIS and Al Qaeda — and now aggregates and analyzes a wide array of sensor- and human-derived data.
AI has also helped the UScreated Security Assistance Group-Ukraine organize logistics for military assistance from a coalition of 40 countries, Pentagon officials say.
To survive on the battlefield these days, military units must be small, mostly invisible, and move quickly because exponentially growing networks of sensors let anyone “see anywhere on the globe at any moment,” then-Joint Chiefs chairman General Mark Milley observed in a June speech. “And what you can see, you can shoot.”
To more quickly connect combatants, the Pentagon has prioritized the development of intertwined battle networks — called Joint All-Domain Command and Control — to automate the processing of optical, infrared, radar, and other data across the armed services. But the challenge is huge and fraught with bureaucracy.
Christian Brose, a former Senate Armed Services Committee staff director now at the defense tech firm Anduril, is among military reform advocates who nevertheless believe they “may be winning here to a certain extent.”
“The argument may be less about whether this is the right thing to do, and increasingly more about how do we actually do it — and on the rapid timelines required,” he said. Brose’s 2020 book, “The Kill Chain,” argues for urgent retooling to match China in the race to develop smarter and cheaper networked weapons systems.
To that end, the US military is hard at work on “human-machine teaming.” Dozens of uncrewed air and sea vehicles currently keep tabs on Iranian activity. US Marines and Special Forces also use Anduril’s autonomous Ghost mini-copter, sensor
‘There’s no AI running around on its own. People are using it to try to understand the fog of war better.’
MISSY CUMMINGS, director of George Mason University’s robotics center and a former Navy fighter pilot
towers, and counter-drone tech to protect American forces.
Industry advances in computer vision have been essential. Shield AI lets drones operate without GPS, communications, or even remote pilots. It’s the key to its Nova, a quadcopter, which US special operations units have used in conflict areas to scout buildings.
On the horizon: The Air Force’s “loyal wingman” program intends to pair piloted aircraft with autonomous ones. An F-16 pilot might, for instance, send out drones to scout, draw enemy fire, or attack targets. Air Force leaders are aiming for a debut later this decade.
The “loyal wingman” timeline doesn’t quite mesh with Replicator’s, which many consider overly ambitious. The Pentagon’s vagueness on Replicator, meantime, may partly intend to keep rivals guessing, though planners may also still be feeling their way on feature and mission goals, said Paul Scharre, a military AI expert and author of “Four Battlegrounds.”