US Air Force Pursues AI for Command and Control

The Air Force is seeking AI support in several key areas, including command and control optimization for mission-tailored AI.
US Air Force Pursues AI for Command and Control
Representative image. Source: United States Air Force Website

Officials of the Air Force Research Laboratory Information Directorate in Rome, N.Y., have called for the use of artificial intelligence tools for command and control, according to an agency announcement.

By expediting the research and development of innovative AI-based capabilities to bolster Joint All Domain Command and Control (C2), the Department of the Air Force (DAF) aims to gain a strategic decision-making edge.

The Air Force is seeking AI support in several key areas, including command and control optimization for mission-tailored AI; federated, composable autonomy; and AI toolbox development.

Additionally, the agency is exploring advanced wargaming agents, interactive learning for C4I, command and control complexity dominance using generative AI, software-defined distributed command and control, and tactical AI.

“AI holds great potential in transforming DAF capabilities across strategic, operational, and tactical levels by enabling decision makers to effectively assess the battlespace, rapidly explore, create, and select the best plan, and direct and monitor forces at pace and scale in a distributed setting. This BAA is interested in exploring new and advancing existing AI and distributed C2 concepts,” the announcement said.

Moreover, the announcement also acknowledges the challenges involved in deploying AI in a distributed and contested environment.

According to reports from last month, the U.S. Department of Defense (DoD) is also exploring ways to expedite the identification and deployment of highly effective military applications of Large Language Models (LLMs).

The Pentagon has initiated discussions with leaders in the tech industry to expedite the identification and implementation of highly valuable military applications.

LLMs possess the capability to rapidly analyze vast amounts of data and distill it into concise insights. This presents intriguing prospects for militaries and intelligence agencies faced with the challenge of navigating the expanding volumes of raw intelligence in the digital era.

Yet, the Pentagon acknowledges that these AI models are susceptible to generating inaccurate information, a phenomenon known as ‘hallucinations’- an issue that remains unresolved within the industry.

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