by Kris Osborn
The threat of drone swarms presents a serious problem for the U.S. military. The Pentagon will need to enterprise new methods of destroying them to protect forward operating bases, ground forces on the move or even air assets such as larger drones, fixed wing aircraft or helicopters.
The Army and its industry partners have been focusing closely on counter drone operations, in large measure because drone swarms present defenders with a host of complexities, including simple redundancy. Should an entire swarm of interconnected mini-drone explosives be approaching, how might hundreds of them be stopped, destroyed or rendered inoperable? Should several small drones be disabled by defenses, what about the remaining ones? How can large numbers of them be taken out at one time, all while an attack is underway and commanders have little time with which to respond.
This predicament raises an interesting and increasingly debated tactical military concept regarding autonomy, artificial intelligence (AI) and the need for a “human in the loop.” The technology wherein a sensor can find, track and then shoot and destroy a target without human intervention, is basically here, yet its application is understandably governed by prevailing Pentagon doctrine which specifies that human beings, not computers, must always make any decision regarding the use of “lethal force.” But what about automated or computer-enabled defensive force that is highly effective, fast yet also non-lethal?
“When you are defending against a drone swarm, a human may be required to make that first decision, but I’m just not sure that any human can keep up with a drone, defending against a drone swarm,” Gen. John Murray, Commander of Army Futures Command, said January 26 at a Center for Strategic and International Studies (CSIS) webinar on Army modernization.
The point Murray seems to be making here is that automated, AI-enabled computer systems could, when confronting drone swarm attacks, potentially succeed in targeting, tracking and destroying the drones without needing each individual step to be handled by a human decision-maker. After all, destroying drones is both highly effective and necessary as a combat technique, and is also non lethal as the systems are unmanned.
“How much human involvement do you actually need when you are talking about non-lethal decisions,” Murray said.
Perhaps a group of sensors could track, analyze, catalogue and specifically locate hundreds of attacking small drones at one time, determine that the entirety of the threat is unmanned and then, perhaps even in milliseconds, take decisive and immediate action. An advanced, pre-programmed computer, empowered with advanced AI-capable algorithms able to discern, gather analyze and organize otherwise disparate pools of sensor and targeting data, could respond to an attack. It could dispatch an area weapon, launch an electronic warfare jamming countermeasure or shoot off several proximity-fuse enabled explosives in the air to destroy or disable the drone swarm.
Perhaps sensor to shooter streamlining could be both sped up and optimized by an AI-capable computer system able to instantly pair sensors to effectors, or methods of counterattack. This was the case last Fall at the Army’s Project Convergence with Firestorm, an AI-empowered computer system which identified and paired sensors with shooters, instantly determining the optimal shooter to align with incoming sensor data. This would be a concept when it comes to using non-lethal, automated force for purely defensive reasons to simultaneously perform massive amounts of combat functions in response to an otherwise overwhelming drone swarm attack.
Kris Osborn is the defense editor for the National Interest. Osborn previously served at the Pentagon as a Highly Qualified Expert with the Office of the Assistant Secretary of the Army—Acquisition, Logistics & Technology. Osborn has also worked as an anchor and on-air military specialist at national TV networks. He has appeared as a guest military expert on Fox News, MSNBC, The Military Channel, and The History Channel. He also has a Masters Degree in Comparative Literature from Columbia University.
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