The first international artificial intelligence (AI) and autonomy trial has been held with the aim of driving the technology into responsible military use.
The work saw the initial joint deployment of Australian, UK and US (AUKUS) AI-enabled assets in a “collaborative swarm” to detect and track military targets in a representative environment in real time.
Accelerating the development of these technologies will have a massive impact on coalition military capability.
The trial was organised by the UK’s Defence Science and Technology Laboratory (Dstl) and was attended by major figures in the world of defence from the three nations which lie under the AUKUS umbrella.
It was claimed it succeeded in the retraining of models in flight and the interchange of AI models between AUKUS nations.
The AUKUS collaboration is looking to rapidly drive these technologies into military capabilities.
The event was attended by senior AUKUS Advanced Capabilities pillar leaders – General Rob Magowan (UK), Deputy Chief of the Defence Staff (Financial and Military Capability), Abraham (Abe) Denmark (US), Senior Advisor to the Secretary of Defense for AUKUS, and Hugh Jeffrey (AUS), Deputy Secretary Strategy, Policy, and Industry.
UK Deputy Chief of Defence Staff, Military Capability, Lieutenant General Rob Magowan said it was a three-way co-operation.
He added: “This trial demonstrates the military advantage of AUKUS advanced capabilities, as we work in coalition to identify, track and counter potential adversaries from a greater distance and with greater speed.
“Service personnel, scientists and engineers from our three nations combined to develop and share critical information to enhance commanders’ decision making.
“Accelerating technological advances will deliver the operational advantages necessary to defeat current and future threats across the battlespace.
“We are committed to collaborating with partners to ensure that we achieve this while also promoting the responsible development and deployment of AI.”
Australian Deputy Secretary, Strategy, Policy and Industry, Hugh Jeffrey said: “The AUKUS AI and Autonomy trial in Salisbury Plains demonstrated AI algorithms working in a mission-tailored adaptive capability. The AUKUS research and operator teams collaborated to develop, test and evaluate joint machine-learning models, and operate our different national platforms on the battlefield.
“I was impressed to see AI models rapidly updated at the tactical edge to incorporate new targets, which were immediately shared among the three partners to deliver decision advantage and meet changing mission requirements.
“This cooperation under AUKUS Pillar II will deliver a capability greater than any one country could achieve alone, and this really is the rationale for the AUKUS partnership at work.”
US Senior Advisor to the Secretary of Defense for AUKUS, Abe Denmark said the trial had shows the potential to “transform” the approach to defence.
He added: “We recognise the immense importance of this collaboration in strengthening our collective national security of our nations. The development and deployment of advanced artificial intelligence technologies have the potential to transform the way we approach defence and security challenges.”
More than 70 military and civilian defence personnel and industry contractors were involved in the exercise in April 2023.
The trial utilised a variety of air and ground vehicles to test target identification capability, including: Blue Bear Ghost (UK) and Boeing/Insitu CT220 (AUS) uncrewed aerial vehicles (UAVs), Challenger 2 tank, Warrior armoured vehicle and Viking uncrewed ground vehicle (UGV), along with a commercially hired FV433 Abbot self-propelled gun and former Eastern Bloc BMP OT-90.
The trilateral teams collaborated to develop joint machine-learning (ML) models, apply test and evaluation processes, and fly on different national UAVs.
The ML models were quickly updated to include new targets and shared among the coalition and AI models retrained to meet changing mission requirements.
Click to Open Code Editor