Senate Hearing Highlights DoD AI Priorities, Goals

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Representatives from the Defense Department (DoD) presented the department’s artificial intelligence (AI) program initiatives and need for collaboration with the private sector to accomplish them in a hearing before the Senate Armed Services Committee today.

Deputy Director of the Defense Advanced Research Projects Agency Peter Highnam, DoD Defense Innovation Unit Director Michael Brown, and Lieutenant General John Shanahan, who also director of the Joint Artificial Intelligence Center (JAIC), broadly testified to senators that AI will significantly transform DoD’s capabilities and that it is critical the U.S. remain competitive with China and Russia in developing AI applications.

Highnam and Brown highlighted that working with JAIC in accomplishing AI goals has been a game-changer for DoD, but also said that working closely with commercial entities in advancing AI research and development is just as – if not more – critical. Brown said branches within DoD work with JAIC to look for commercially successful AI strategies, then seek to sign contracts with those private-sector organizations to help DoD with its AI initiatives.

Shanahan further emphasized that for the U.S. to become a leading country in AI – particularly against China – making AI a focus of society, not just DoD, is also important. He and the others testifying from DoD said this would mean prioritizing federally funded research and broad education in AI, but also a national purpose: How do we derive a national mission from the Trump administration’s February executive order to advance AI?

Senators also focused on ethical concerns in expanding AI during the hearing. Highnam said that there are currently two major concerns that DoD currently has: implicit bias and the dangers of deploying technology without fully understanding its failure modes. However, he added that much of the department’s current research currently focuses on making emerging technology robust enough to troubleshoot these problems.

Building explainable and trustworthy AI is part of not only developing ethical applications, Highnam said, but in building public-private partnerships and societal drive toward advancing AI.

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