(Photo: Keith Heywood)
On 15 December 2020, Artificial Intelligence (AI) driven algorithms controlled sensor and navigation systems on a United States Air Force (USAF) Lockheed Martin U-2S Dragon Lady Reconnaissance aircraft in a flight test. The service says that this is the first time that artificial intelligence has been “safely” put in charge of any United States military system and appears to be the first time it has been publicly utilised on a military aircraft. The test, involved a U-2S from the 9th Reconnaissance Wing at Beale Air Force Base in California. The Air Force has dubbed the AI software package as ARTUμ, in reference to the iconic droid from the Star Wars universe, who serves as a sort of robotic flight engineer and navigator. “ARTUμ’s ground breaking flight culminates our three-year journey to becoming a digital force,” Assistant Air Force Secretary Will Roper said in a statement. “Putting AI safely in command of a US military system for the first time ushers in a new age of human-machine teaming and algorithmic competition. Failing to realise AI’s full potential will mean ceding decision advantage to our adversaries.” “Call sign ‘Artuμ,’ we modified world-leading μZero gaming algorithms to operate the U-2›s radar,» Roper wrote in his tweet about the test. «This first AI co-pilot even served as mission commander on its seminal training flight!» The μZero algorithm, developed by AI Research Company ‘DeepMind’ has been used by computers to play chess, Go, and video games in the past, “without prior knowledge of their rules,” Roper further explained in a piece he wrote for Popular Mechanics about this test. The U-2 Federal Laboratory helped integrate the modified ARTUμ version of this software package onto the U-2S reconnaissance platform. And it is enabled by a publicly available, Google-developed system called Kubernetes, which allows the AI software to be ported between the plane’s on-board computer systems and the cloud-based one it was developed on. In Popular Mechanics, Roper described the flight test as follows: “Our demo flew a reconnaissance mission during a simulated missile strike at Beale Air Force Base. ARTUμ searched for enemy launchers while our pilot (call sign “Vudu”) searched for threatening aircraft, both sharing the U-2’s radar. With no pilot override, ARTUμ made final calls on devoting the radar to missile hunting versus self-protection. Luke Skywalker certainly never took such orders from his X-Wing sidekick!” “Like a breaker box for code, the U-2 gave ARTUμ complete radar control while ‘switching off’ access to other subsystems. Had the scenario been navigating an asteroid field—or more likely field of enemy radars—those ‘on-off’ switches could adjust. The design allows operators to choose what AI won’t do to accept the operational risk of what it will. Creating this software breaker box—instead of Pandora’s, has been an Air Force journey of more than a few parsecs”. Roper said the AI was trained against an opposing computer to look for oncoming missiles and missile launchers. For the purposes of the initial test flight, the AI got the final vote on where to direct the plane’s sensors.
The upgrades, highlighted in boxes above, will prepare the U-2 for additional modernisation efforts that will provide a quantum leap in capability for the warfighter and a bridge to capabilities needed in the future battlespace. (Image: LM)
Aperture Radar System-2 (ASARS-2) all weather day and night high resolution radar imaging system, which Dragon Ladies routinely carry and features two sideways-looking electronically-scanned array radar antennas on either side of a specially designed nose module. ASARS-2 can operate in search and spot modes against moving and stationary targets. In moving target indicator mode, the view of moving targets is presented against a Synthetic Aperture Radar (SAR) background or a cartographic background. Operation in spot mode against stationary targets provides a higher degree of detail and finer target discrimination. A recorder for the ASARS-2 is installed in the equipment bay forward of the main landing gear well. Data from the ASARS-2 is downloaded via a real-time wideband data link to the TR-1 ground station, TRIGS-1, supplied by Lockheed Martin. Upgraded Raytheon ASARS-2A radar has been developed which has an increase in coverage, more capable spot mode and enhanced ground moving target indicator, with a new on-board processor. U-2s also regularly carry powerful Senior Glass Signals Intelligence (SIGINT) suite that includes Senior Spear Communication Intelligence (COMINT) and Senior Ruby Electronic Intelligence (ELINT) payloads that can detect, categorise, and geolocate various emitters, including those from hostile radars, plus a formidable AN/ ALQ-221 defensive electronic warfare suite. A new software package allows a Dragon Lady to update its mission systems in flight including the addition of new target recognition algorithms onto the aircraft. The fleet is equipped with Senior Year electro-optical reconnaissance system (SYERS) sensor SYERS-2C supplied by Collins Aerospace. Surveillance function is one that has already incorporated the use of AI to analyse complex data. An USAF programme called Project Maven sought to rapidly analyse reams of drone footage in place of humans. Google famously declined to renew its Maven contract following an internal revolt from employees who didn’t want the company’s algorithms involved in warfare. The company later released a set of AI principles that disallowed the company’s algorithms from being used in any weapons system. In any case, AI in military application will take several decades to sufficiently mature.
Sayan Majumdar