Defense Advanced Research Projects AgencyTagged Content List

Human-Machine Interface

Relating to the interaction between humans and machines

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Dramatic success in machine learning has led to a torrent of Artificial Intelligence (AI) applications. Continued advances promise to produce autonomous systems that will perceive, learn, decide, and act on their own. However, the effectiveness of these systems is limited by the machine’s current inability to explain their decisions and actions to human users (Figure 1). The Department of Defense (DoD) is facing challenges that demand more intelligent, autonomous, and symbiotic systems. Explainable AI—especially explainable machine learning—will be essential if future warfighters are to understand, appropriately trust, and effectively manage an emerging generation of artificially intelligent machine partners.
For the past 100 years of mechanized warfare, protection for ground-based armored fighting vehicles and their occupants has boiled down almost exclusively to a simple equation: More armor equals more protection. Weapons’ ability to penetrate armor, however, has advanced faster than armor’s ability to withstand penetration. As a result, achieving even incremental improvements in crew survivability has required significant increases in vehicle mass and cost.
What is opaque to outsiders is often obvious – even if implicit – to locals. Habitus aims to capture and make local knowledge available to military operators, providing them with an insider view to support decision making.
Coatings, thin films and advanced surfaces are important aspects of systems, devices and technologies critical to the mission of the Department of Defense. Despite decades of work, methods that enable atomic through millimeter-scale control over structure and properties of materials deposited on surfaces are still underdeveloped. For example, structural organization of high-value thin films is typically controlled by high-temperature deposition or annealing, but the temperatures employed during thin-film synthesis and deposition exceed the limits of many DoD-relevant substrates, restricting application opportunities.
The Next-Generation Nonsurgical Neurotechnology (N3) program aims to develop high-performance, bi-directional brain-machine interfaces for able-bodied service members. Such interfaces would be enabling technology for diverse national security applications such as control of unmanned aerial vehicles and active cyber defense systems or teaming with computer systems to successfully multitask during complex military missions.