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Scientists at the US Army Research Laboratory (ARL) are developing a technology that has promise for both medical as well as deep machine learning systems uses, potentially in military applications. The work is part of an effort to improve the ability of humans and machines to manage information by working together. For now, research in his field is being mostly used to further medical research but could eventually feed into the Department of Defense’s plans for human-machine teaming, which the department has said is its primary goal for using AI.

“This work is part of a larger research program at ARL that focuses on understanding the principles that govern the application of neuroscience-based research to complex operational settings,” said Dr. Vernon Lawhern, an ARL mathematical statistician and one of the leaders of the joint project.

Researchers from ARL and DCS, which works with defense and national security agencies on advanced technologies, used an in-house tool called EEGNet for brain-computer interfaces using electroencephalogram (EEG) signals, according to Incorporating a machine-learning neural network builds off of recent advances in AI and machine learning and, in this case, achieved tangible results.

A lot of BCI research has focused on medical applications, such as helping people who can only move their eyes to communicate. Recent advancements include writing, making a phone call, controlling a robotic arm, and greatly improving typing speeds for people with paralysis and conditions such as ALS. But ARL has touted the potential for improving human interaction with machines, which could manifest itself in improving the way soldiers communicate on the battlefield and control military systems.