On May 28, the National Security Commission on Artificial Intelligence (the “Commission”) invited public comments regarding "the methods and means necessary to advance the development of artificial intelligence, machine learning, and associated technologies by the United States to comprehensively address the national security and defense needs of the United States.” Comments are due by September 30, 2020 for consideration in the preparation of a report to Congress due March 2021.
The Commission was created by Congress in the John S. McCain National Defense Authorization Act for Fiscal Year 2019. The Commission seeks public comment on q) 10 topics identified by Congress, b) seven consensus principles from its November 2019 Interim Report, and c) 31 judgments in the Interim Report. Select items particularly pertinent for consideration by economists are excerpted below:
Topics Identified by Congress
A. “The competitiveness of the United States in artificial intelligence, machine learning, and other associated technologies, including matters related to national security, defense, public-private partnerships, and investments.”
B. “Means and methods for the United States to maintain a technological advantage in artificial intelligence, machine learning, and other associated technologies related to national security and defense.”
D. “Means by which to foster greater emphasis and investments in basic and advanced research to stimulate private, public, academic and combined initiatives in artificial intelligence, machine learning, and other associated technologies, to the extent that such efforts have application materially related to national security and defense.”
E. “Workforce and education incentives to attract and recruit leading talent in artificial intelligence and machine learning disciplines, including science, technology, engineering, and math programs.”
Consensus Principles from Interim Report https://www.nscai.gov/reports
3. Private sector and government share responsibility for our nation's future.
4. People matter more than ever in an AI competition.
5. Protecting our most valuable assets and ideas must not come at the expense of free inquiry and innovation.
Judgments from Interim Report https://www.nscai.gov/reports
Line of Effort 1—Invest in AI Research & Development and Software
1. Federal R&D funding for AI has not kept pace with the revolutionary potential it holds or with aggressive investments by competitors. Investments that are multiple times greater than current levels are needed.
2. Untapped opportunities exist to build a nationwide AI R&D infrastructure and encourage regional innovation “clusters.” Such AI districts for defense would benefit both national security and economic competitiveness.
Line of Effort 3—Train and Recruit AI Talent
14. DoD and the IC are failing to capitalize on existing technical talent because they do not have effective ways to identify AI-relevant skills already present in their workforce. They should systematically measure and incentivize the development of those skills.
18. American colleges and universities cannot meet the demand for undergraduate student interest in AI and computer science generally.
19. The American AI talent pool depends heavily on international students and workers. Our global competitiveness hinges on our ability to attract and retain top minds from around the world.
Line of Effort 4—Protect and Build Upon U.S. Technological Advantages & Hardware
20. The U.S. Government should continue to use export controls--including multilateral controls--to protect specific U.S. and allied AI hardware advantages, in particular those in semiconductor manufacturing equipment.
21. However, traditional item-based export controls and narrowly-scoped foreign investment reviews are by themselves insufficient to sustain U.S. competitiveness in AI.
22. The United States must continue leading in AI-related hardware, and ensure the government has trusted access to the latest technologies.
Line of Effort 5—Marshal Global AI Cooperation
24. The United States must enhance its competitiveness in AI by establishing a network of partners dedicated to AI data sharing, R&D coordination, capacity building, and talent exchanges.