Reps. Will Hurd, R-Texas, and Robin Kelly, D-Ill., continue their push to develop bipartisan policy to help the U.S. keep its artificial intelligence research edge, publishing a new report focusing on the need for more research and development funding.
“Greater investments in artificial intelligence research and development are essential to maintaining American leadership in AI,” opens the report, produced in conjunction with the Bipartisan Policy Center and the Center for a New American Security.
Hurd and Kelly recommend — as the White House and the National Security Commission on AI have before — that national R&D spending on AI should be immediately doubled.
On top of that, the report goes further in specifying the need for certain types of investments the government needs to make and how to maximize the return on those investments. Previous reports from the Hurd and Kelly focused on the government’s AI workforce and AI in national security.
“Federal investment and smart R&D policy have been critical to the technological success of the United States and will be especially important with the rise of AI,” Bipartisan Policy Center President Jason Grumet said in a statement.
One place where research is starting to fray is academic institutions not having access to the computing power needed to train AI systems and algorithms on large data sets. The report suggests further collaboration between the government and the private sectors beyond just monetary investments, giving academia access to the massive computing power needed to continue to conduct research that benefits the advancement of AI-enabled technology. The report also recommends that new tax credits offer incentives for private companies to engage in basic research and development spending of their own.
“To ensure the United States is maximizing its R&D potential … the partnership of government, academia, and the private sector must be strengthened to ensure each has adequate access to the resources they need,” the report states.
More data, more compute
The report encourages the government to “diversify” its compute and dataset resources. By this, it means having the government invest in new forms of computing, like next-generation chips and having the government collect and open more types of datasets for AI training by public, private and academic groups.
“Data resulting from federally funded grants should, to the maximum extent possible, be made publicly available in accordance with appropriate safeguards to protect personally identifiable information,” one of the report’s recommendations states.
Another point on the diversification of AI development is the need to expand broadband to rural areas to be able to expand access to data and technology development. This would allow more people from different backgrounds to participate in research and for data to be collected from rural and other areas with a low level of internet access.
“Making cloud computing more widely available opens up the potential for cutting-edge R&D to take place outside America’s current AI hubs, making many small and mid-sized cities more appealing locations for startups and their employees,” the report states.
Keep it international
Beyond expanding access to AI research across the U.S., the report recommends AI research should be thought of as a critical international problem and that the U.S. cannot go it alone. Working with universities in partner nations should increase and government agencies like the National Science Foundation should create “multilateral teams of AI researchers.”
“The United States is fortunate to have most of the world’s leading AI powers as allies and partners,” the report states.
Those allies and partners will be critical to building large data sets and sharing breakthroughs in the research and technological advancements needed to further develop AI, according to the report.