We haven't been able to take payment
You must update your payment details via My Account or by clicking update payment details to keep your subscription.
Act now to keep your subscription
We've tried to contact you several times as we haven't been able to take payment. You must update your payment details via My Account or by clicking update payment details to keep your subscription.
Your subscription is due to terminate
We've tried to contact you several times as we haven't been able to take payment. You must update your payment details via My Account, otherwise your subscription will terminate.

Pentagon uses AI to predict enemy moves ‘days in advance’

The US military is harnessing computing power to analyse intelligence and have it make predictions
The US military is harnessing computing power to analyse intelligence and have it make predictions
GETTY IMAGES

The US military is testing an advanced artificial intelligence (AI) system that it hopes can predict an enemy’s next move days before it actually occurs.

Predicting the future is normally a hopeless task, but advances in technology and the increasing shift to using AI to assist decision-making have opened up possibilities for warfare that would once have felt like science fiction.

The US defence department has created a new acronym for the computerised crystal ball-gazing: GIDE, or global information dominance experiments.

The aim is to achieve “decision-making superiority”, said General Glen VanHerck, commander of Northern Command and the North American Aerospace Defence Command, both of which are intended to protect the US homeland from every form of enemy attack.

“What we’ve seen is the ability to get way further [than] being reactive into actually being proactive — and I’m talking not minutes and hours, I’m talking days,” he said at a Pentagon briefing.

Advertisement

The project outlined by the general, which has been in development for about a year, echoes the film Minority Report, based on a Philip K Dick story, where Tom Cruise was a cop in a “pre-crime” division where arrests are made based on predictions of a future criminal acts.

VanHerck said the system represented “a fundamental change in the way we use information and data” to accelerate decision-making at the tactical and strategic level at a time when both Russia and China are challenging the US on a daily basis.

In the latest of three experiments carried out by the Pentagon and all 11 US combatant commands, one of the focuses was on envisaging a threatened takeover of the Panama Canal by such a “peer competitor”, disrupting a crucial line of communication for US military logistics.

During the simulated attack, AI systems exploited a mass of data in a way no human could absorb to predict how the enemy might react, by examining patterns and changes. Once alerted to anything significant, commanders fed the information to orbiting satellites to “take a closer look at what might be going on in a specific location”, VanHerck said.

“The ability to see days in advance creates decision space,” he added.

Advertisement

In the past, secret information provided by intelligence sources such as satellites could take a long time for an analyst to pore over.

“Now the machine can take a look and tell you exactly how many cars are in a parking lot or how many aeroplanes are parked on a ramp, or if a submarine is getting ready to leave or if a missile’s going to launch. Where that may have taken days before, or hours, today it can take seconds or less than minutes,” the general said.

The project was not about new ways of gathering data: “This information exists from today’s satellites, today’s radar, today’s undersea capabilities, today’s cyber, today’s intelligence capabilities.

“What we’re doing is making that data available and shared into a cloud where machine learning and AI look at it and process it really quickly and provide it to decision-makers.

“This gives us days of advanced warning and ability to react. Where in the past, we may not have an analyst eyes-on with a satellite image, now we are doing that in near real-time.”