As the United States faces threats that are more complex and rapidly evolving than ever, the Defense Department's technological arsenal must be ready to face any challenge. Just as the dramatic innovation of info-tech systems and software capabilities have revolutionized the military's ability to execute its mission, successful formulation and implementation of an artificial intelligence strategy is critical to the success of the next-generation military.
The AI arms race is already underway amongst the United States, Russia, China and other more technologically advanced nations. In order to succeed in the global arena, the Pentagon must continue to make strategic investments to deploy AI systems that will strengthen the military and support the war-fighter.
The Defense Department must work with industry partners, including large contractors and startups who have the right capabilities and domain expertise, to harness the power of modern AI and further develop and tailor this technology to meet the unique and constantly evolving challenges faced by today's modem military. The AI systems must be robust, secure and explainable so they can perform as intended in a way that is consistent with the values of the nation.
Artificial intelligence has delivered on a number of its promises through advancements made in the past few years. Driverless cars, natural language translation, virtual assistants, and robots in homes, stores, factories and on the battlefield are just a few examples of this trend. The "AI winter" has ended--the success of AI methods has restored confidence in the approach, and funding for the field has increased in recent years in both the private and public sectors.
Several applications of the technology the Defense Department is working on are either already being explored or are within reach. These include automatic target recognition in intelligence, surveillance and reconnaissance, optimal resource allocation, cost reduction, improved maintenance scheduling for aircraft, vehicles, etc., physical and cyber threat detection, logistics and transportation, health care, training, combat simulations, human capital, energy consumption and data compression.
Applying AI methods to these problems requires leveraging a combination of structured and unstructured data. As an example, logistics data from structured databases as well as onboard vehicle sensors--likely unstructured--can be mined to learn patterns, optimize routes and...