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NSCAI Report: How the U.S. Can Maintain AI Leadership

Written by Steve Escaravage

Five keys for technology advantage

As the artificial intelligence (AI) landscape rapidly evolves, we can see new possibilities every day for harnessing machine learning to transform public-sector processes, serve citizens more effectively, and provide innovative support for defense missions. But there’s more to recognize in AI’s complex story. On the highway, it’s often said that “objects in the mirror are closer than they appear.” And it’s really no different for today’s AI race. When we look back, it’s increasingly clear that our adversaries have gained more ground than we would have imagined. In this way, the costs and risks of falling behind in the AI race have now become impossible to ignore.

Released on March 1, 2021, the final report of the National Security Commission on Artificial Intelligence (NSCAI) gives a realistic assessment of the current state of AI and the investment required for the United States to maintain leadership, especially when safeguarding against shifting, increasingly malign threats. Based on deep analysis, the report’s most critical message is simply this: “America is not prepared to defend or compete in the AI era.”

This stark statement is undeniably true. While the United States has enjoyed technology leadership in other areas, we’ll quickly fall behind if action is not taken to heed the call plainly made in the Commission’s report. And the challenge ahead cannot be solved by one company, industry, or government alone—it is critical that we come together and responsibly develop the future of AI.

Here are five keys to improving U.S. standing in the global competition for AI capabilities:

  1. Fully recognize that the United States is on a path to fall behind our global competitors in today’s technology race—and that rapid advancement in AI strategy is critical for the national security of the American people.
  2. Embrace the report’s recommendations and blueprints as a well-researched and timely course correction that calls for interrelated actions to safeguard America from AI-related threats, preserve existing technology advantages, and “organize to win” the global AI competition.
  3. Commit to dramatic new investments to accelerate the Government’s AI R&D efforts and build a National AI Research Infrastructure while creating commercial markets for AI innovations.
  4. Operationalize AI in the real world with an emphasis on ensuring responsible, human-centered uses of AI, better preparing U.S. workers and students for AI jobs, and integrating the tech ecosystem to scale AI operations across industries and enterprises.
  5. Ensure an “all-in” commitment by defense, big tech, startups, and academia in partnering with the Government to bring forward the best people, partners, and technology that will be the key to decisively winning the AI race.

Despite America’s vulnerable edge in the AI race, there is reason for optimism as we respond to the commission’s report. The United States can accelerate our response and grow our lead in AI if we channel the nation’s ingenuity—the public and private sectors working together with academia—into a coordinated, national push to responsibly develop and deploy AI at scale. As a trusted AI partner to the U.S. defense, intelligence, and civil sectors, Booz Allen strongly commits to enabling this critical work. And again, we believe that this effort must prioritize people as much as technology. Americans must understand the potential of AI to imagine and then bring to life its many possibilities. With the right blueprint to consistently embed important values and apply machine learning with trust, our government and its stakeholders can ensure the responsible, ethical development and use of AI to strengthen our national security.

About the Author: 
Steven Escaravage leads Booz Allen’s Analytics practice and Artificial Intelligence (AI) Services business, serving clients across the defense, civil, and intelligence sectors. As a leader of Booz Allen's strategic innovation initiatives, Steve also leads the firm's investments in data science, machine learning, and AI. Areas of focus include machine learning operations, cognitive automation, and high performance computing. He holds an M.S. in operations research from George Mason University and a B.A. in mathematics from Rutgers University.

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