UK and US defence labs collaborate on mission-ready AI tech

Researchers from the US Air Force have demonstrated ways that the UK can partner with America to develop and deploy 'state of the art' machine learning algorithms to support ground troops.

The US Air Force Research laboratory (AFRL) has been working with the UK's Defence Science and Technology Laboratory (Dstl) since December 2020 to develop artificial intelligence (AI) systems for warfare.

The four-year partnership agreement is aimed at accelerating joint US-UK collaboration of AI technologies, which will largely focus on research and development for command and control capabilities for both nations.

The first project of the collaboration was demonstrated via dual virtual events in New York and Salisbury, UK. It featured an integrated system with the ability to share data and algorithms through a common development and deployment platform. The platform is said to enable the rapid selection, testing, and deployment of artificial intelligence capabilities.

This was the first in a series of events that will be hosted by the joint and international signatories of the Autonomy and Artificial Intelligence Collaboration (AAIC) Partnership Agreement, with more projects to improve combat technologies.

"We are dedicated to getting robotics and autonomous systems capability into the hands of the warfighters," ​​Dr Robert W Sadowski, US Army DEVCOM, said. "Advances in robotics and autonomy will make our formations more capable and mission-ready while providing protection to our warfighters through unprecedented stand-off while enabling enhanced lethality on the battlefield."

The demonstration featured a simulated scenario focusing on how the UK and US can cooperate and share AI capabilities to support troops. Where both countries operate in adjacent areas, they will be able to share data, AI algorithms "tightly" during missions.

Some of the technology on show included the UK's Model Cards, which are able to present to a commander the ability to quickly understand, explore, and select appropriate machine learning models to deploy in missions.