CEI Comments on Office of Science and Technology Policy’s request for comments on updating the National Artificial Intelligence Research and Development Strategic Plan


On behalf of the Competitive Enterprise Institute (CEI), I respectfully submit these comments in response to the Office of Science and Technology Policy’s request for comments on updating the National Artificial Intelligence Research and Development Strategic Plan.1 Founded in 1984, the Competitive Enterprise Institute is a non-profit research and advocacy organization that focuses on regulatory policy from a pro-market perspective. CEI works to promote policies that can help boost technological innovation and American leadership in areas such as artificial intelligence and machine learning and emerging technologies that depend on such innovation.

The Competitive Enterprise Institute appreciates the recognition by both the Trump and Biden Administrations of the need to create a more favorable regulatory environment in which artificial intelligence (AI) and AI-enabled emerging technologies can thrive and promote American economic growth and competitiveness. To that end, CEI recognizes the increasingly important role played by the Office of Science and Technology Policy (OSTP), the National Science and Technology Council (NSTC)’s Select Committee on Artificial Intelligence, the NSTC Machine Learning and AI Subcommittee, and the National AI Initiative Office. As these regulatory bodies seek to update the National AI Research and Development (R&D) Strategic Plan, they have an opportunity to strengthen America’s position as a global center of AI innovation. To accomplish that goal, the OSTP and the NSTC need to make several updates to the current AI strategy.

Specifically, the National AI R&D Strategic Plan would benefit from updates in five areas.

  • First, while the strategic plan recognizes the essential role of the private sector in promoting AI innovation, it needs to provide more concrete steps to engage the private sector in AI research and development projects.
  • Second, to ensure that taxpayer dollars are utilized effectively, the AI strategic plan should propose a framework to track and evaluate the effectiveness of R&D expenditure and grants to various recipients in different AI subdisciplines.
  • Third, the strategic plan would benefit from a more nuanced understanding of the AI R&D and regulatory approaches in other countries. For example, reviewing AI policies of other nations could help inform why the U.S. government should allocate a higher share of research spending to multidisciplinary AI projects and prioritize accuracy over algorithmic transparency as a goal for AI systems.
  • Fourth, while the AI strategy recommends developing shared AI datasets for academic and private sector use, more details are needed on such proposals.
  • Fifth, the National AI R&D Strategic Plan should propose a federal AI sandbox program to incentivize the private sector to play a more important role in AI innovation. By allowing private companies and research institutions to test innovative AI systems for a limited time, such a program can help promote technological innovation, enhance regulatory understanding of AI, and help craft market-friendly regulatory frameworks and technical standards for AI systems.

I.  The National AI R&D Strategic Plan Needs to Better Engage the Private Sector

The private sector and academic institutions play a crucial role in the development of AI technologies.2 Given that reality, a successful AI strategy needs to closely engage technology companies, startups, and research institutions. The 2019 National AI R&D Strategic Plan recognizes the private sector’s essential role in promoting artificial intelligence and provides several recommendations to enhance collaboration with the private sector. For instance, it proposes creating joint public-private collaboration, increasing the availability of public datasets, and expanding AI training and fellowship opportunities to meet workforce R&D needs.3 Despite such proposals, the strategy would benefit from a greater emphasis on engaging the private sector and academic institutions in promoting AI innovation, for example, by creating a federal artificial intelligence regulatory sandbox program, as discussed later in this comment.

II.   Developing Mechanisms to Track and Evaluate Artificial Intelligence R&D Spending

The National AI R&D Strategic Plan should propose a framework to better track the allocation and impact of AI-related research and development projects across federal agencies, research institutions, companies, and other recipients of federal AI R&D grants. Despite the growing federal expenditure on AI-related research and development activities, there appears to be a scarcity of efforts in tracking how this money is spent and how it impacts AI innovation.4

Greater transparency and more precise information about federal AI expenditure and its impact on innovation within different AI subdisciplines can help policymakers allocate R&D resources more effectively. For example, have resources allocated to specific AI subdisciplines—such as computer vision—led to demonstrably better research outcomes than in other areas? Are certain federal agencies and academic institutions more effective at utilizing research grants than others? Collecting and analyzing data to answer these questions can significantly improve policymakers’ ability to make evidence-based R&D spending decisions.

Some long-term AI research projects will require several years before R&D efforts show results—especially in “general AI” and areas of machine learning research that do not appear to have immediate commercial applications.5 However, tracking spending can nonetheless help compare the effectiveness of similar short- and long-term projects by different agencies, research institutions, and companies. That could not only help U.S. policymakers allocate more resources to more promising AI subdisciplines, but it might also help improve competition between different recipients of federal research grants.

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