DoD strategy for AI has implications ranging from intel to business reform

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There are a myriad of organizations in DoD that have a major interest in developing and using artificial intelligence, but until now, no coordinated strategy across the department to share lessons and avoid duplication of effort. That’s beginning to change, officials say.

The realization of the need for such a strategy set in last fall, when, as part of the process of developing the 2018 National Defense Strategy, DoD research leaders began to assess the specific AI and machine learning projects that were already underway throughout the department.

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“We were surprised by the breadth that this area has expanded, because everybody has a way to use artificial intelligence — they can envision it,” Mary Miller, the acting assistant secretary of Defense for research and engineering told the House Armed Services Committee last week. “We started doing weekly meetings with people within the Department of Defense, over 40 organizations, over 150 people typically in any given week, that come to talk about what they are doing and how they are investing in what their needs are. Through this effort, we have been trying to shape an understanding of what we are spending our resources on and then to trying to organize those efforts into something that would apply to the National Defense Strategy and where we need to go.”

The unclassified version of the strategy describes offers few specifics about DoD’s precise ambitions for AI, other than to say the department plans to make more investments in the field “including rapid application of commercial breakthroughs, to gain competitive military advantages.” The spending is part of an overall $18 billion increase for science and technology spending DoD requested in its 2019 budget proposal.

But Miller said the development of the new AI roadmap is being organized along several lines of effort, including developing a workforce that understands AI, employing it to improve the military’s command and control systems, conduct intelligence analysis and find ways to team humans with machines in pursuit of a given mission.

She said the ultimate goal is to increase the military’s lethality, but that that doesn’t mean the strategy won’t consider ways to use AI in back-office business areas.

“The more we can save through our business reform, the more we can spend on achieving and attaining that lethality that he desires of the Department of Defense,” Miller said. “So we’re looking at, how do you apply AI to not only training and education, but finances, the medical field, and what we do in contracts acquisition and legal activities?”

The development of a new strategy for AI is far from the first time the department has publicly raised it as a major priority. Artificial intelligence, machine learning and “human-machine teaming” were major cornerstones of the “third offset” strategy DoD officials first embarked on in 2014 amid concerns that the U.S. military was at risk of losing its technological edge to potential adversaries, including Russia and China.

But military officials have been speaking in increasingly worried tones about the prospect of other nations making critical advances in AI before the U.S. does, and then applying them to warfighting.

“Simply put, I would characterize it as what you may roughly know as a revolution in military affairs,” Lt. Gen. Paul Nakasone, President Trump’s nominee to be the next commander of U.S. Cyber Command said at a confirmation hearing earlier this month. “I mean, this is a game changer for our adversaries if they get to artificial intelligence, if they get to quantum computing before we’re there. This is why it’s so critical that we continue our research, continue our work towards it.”

What’s especially worrisome is that China in particular does not have the same bureaucratic impediments the U.S. does when it comes to transitioning new technologies from the private sector or academia into military use, said Rear Adm. David Hahn, the chief of naval research. That’s a fact of life in all areas of technology development, not just when it comes to machine learning and AI, he said.

“There are no structural impediments. They’ve lubricated their system to a point where if a direction is given to move it, it goes,” Hahn said. “By design, we don’t enjoy that same kind of streamlined system, and I’m not saying we need to change our design in the manner China has. But we certainly do need to think through how we’re going to do this differently so that the great work that’s done on the S&T side of the business — and that we see every single day in our personal lives – when it comes time to apply it to naval warfighting or the joint fight, we’ve got good pathways to get it there. That’s the part that worries me: our ability or inability to move at speed.”

Rep. Elise Stefanik (R-N.Y.), the chairwoman of the House Emerging Threats and Capabilities subcommittee said she intends to introduce legislation later this week that’s meant to begin that thinking process, and force a new look at how the U.S. government is organized to “understand and leverage AI.”

“Russia has increased their basic research budget by nearly 25 percent, and the Chinese have national-level plans for science and technology, as well as an approach to lead the world in artificial intelligence by 2030,” she said. “All of these signs point to top-down, government-driven agendas that provide resources and roadmaps for strategic collaboration between industry, academia, and civil society. These efforts could propel Russia and China to continue to leap ahead in many technology sectors, but adversarial dominance is not a forgone conclusion.”