While many nations, including Canada, China, France, and the United Kingdom, have developed national strategies to support the development and adoption of AI, the United States has not. It has no cohesive plan to support the competitiveness of the U.S. AI industry or to spur the widespread and rapid adoption of AI to all parts of the economy and society. Developing such a strategy will require more than modest increases in funding for AI research: It will require a multi-pronged approach that focuses on a wide array of policy areas, including data and skills, and more in-depth sectoral analysis. Failing to develop such a strategy will not only reduce America’s global competitiveness but slow its economic growth and impede societal progress.
On December 4, ITIF’s Center for Data Innovation hosted a panel discussion on Capitol Hill about the ways in which policymakers can make the United States more competitive in the global AI race. At the event, the Center released a new report, “Why the United States Needs a National Artificial Intelligence Strategy and What it Should Look Like,” providing a detailed breakdown of the United States’ AI policy and calling for a cohesive strategy. However Lynne Parker, Assistant Director of Artificial Intelligence at the White House Office of Science and Technology Policy, made the case that while the United States does not have a national AI strategy laid out all in one document, it does indeed have an AI strategy. Parker cited the White House’s 2016 National Artificial Intelligence Research and Development Strategic Plan, which outlines funding priorities for federal research dollars, as well as other efforts to support AI, particularly R&D, in the federal government. Parker also noted that while it is often difficult to implement AI in the federal government structure due to the prevalence of legacy systems, her team is working to overcome those challenges.
Although, as the Center’s senior analyst Joshua New explained, there are several areas where U.S. AI policy is lacking and that that there are several competitiveness and national security reasons to develop a cohesive AI strategy. For example, New pointed out that China has a plan to gain AI dominance by 2030 and that China is catching up to the United States in AI R&D spending. New highlighted some of the ways an AI strategy could boost U.S. competitiveness in AI, including through the creation of data trusts to share data with other companies and academics, funding programs to incentivizing academics to stay in academia instead of going into the private sector, and increasing funding for AI R&D.
Robert Hoffman, managing director of government relations for North America at Accenture, agreed that the United States must do more to maintain its leadership in AI development, especially over China. Hoffman stressed that while the United States is currently the world leader in AI, China is not far behind and is pursuing AI more aggressively. Mark MacCarthy, senior vice president for public policy at the Software & Information Industry Association, stressed the need to increase funding for AI and to grow the supply of workers with the necessary skills to support AI. MacCarthy also urged for more research to be conducted into where the United States should dedicate its funding for AI to identify where it would be the most effective. And Rachel Wolbers, policy director at Engine, a research and advocacy organization for the tech startup community, argued that to increase competitiveness in AI, the United States should not pursue a European-style approach to restrictive regulation that could harm the ability for U.S. firms to develop and use AI effectively. When it comes to national security, Lindsey Sheppard, associate fellow with the International Security Program at the Center for Strategic and International Studies, stated that the defense community has an advantage over other industries in AI development. To be successful, however, Sheppard argued that the defense community will have to continue to adapt AI applications to fit its needs rather than just forcing the use of AI into projects where it does not help.
All panelists agreed with the report’s conclusion that the United States should increase its efforts to support AI development and adoption. The widely-attended event signaled strong interest from the public and private sectors in how to advance U.S. competitiveness and national security with AI. As the 116th Congress and the administration begin their work in the new year, developing a comprehensive national AI strategy should be one of their top priorities.
Follow the discussion on Twitter with the hashtag #datainnovation.