Defense Advanced Research Projects AgencyTagged Content List

Artificial Intelligence and Human-Computer Symbiosis Technologies

Technology to facilitate more intuitive interactions between humans and machines

Showing 22 results for Artificial Intelligence + Automation RSS
Some of the systems that matter most to the Defense Department are very complicated. Ecosystems, brains and economic and social systems have many parts and processes, but they are studied piecewise, and their literatures and data are fragmented, distributed and inconsistent. It is difficult to build complete, explanatory models of complicated systems, and so effects in these systems that are brought about by many interacting factors are poorly understood.
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.
The Intelligent Neural Interfaces (INI) program seeks to establish “Third-Wave” artificial intelligence methods to improve and expand the application space of next-generation neurotechnology.
The U.S. Government operates globally and frequently encounters so-called “low-resource” languages for which no automated human language technology capability exists. Historically, development of technology for automated exploitation of foreign language materials has required protracted effort and a large data investment. Current methods can require multiple years and tens of millions of dollars per language—mostly to construct translated or transcribed corpora.
Driven by the rapidly evolving national security threat landscape, future defense systems will need access to low size, weight, and power (SWaP) artificial intelligence (AI) solutions that can rapidly transition from idea to practice. In recent years, the ability to learn from large datasets has advanced significantly due to increases in hardware performance, advances in machine learning (ML) algorithms, and the availability of high quality open datasets.