The NSF AI Education Act of 2024, introduced Thursday by Sens. Jerry Moran, R-Kan., and Maria Cantwell, D-Wash., supports investments in science, technology, engineering and mathematics education, part of an effort to “help make certain the U.S. is an AI leader in the next century,” Moran said in a press release. 

The legislation would not only authorize NSF to grant fellowships and scholarships within AI and quantum education — along with awarding fellowships for professional development — but would also allow the agency to conduct an outreach campaign throughout the nation that increases awareness of its educational opportunities. The campaign would prioritize outreach to “rural and underserved areas,” per the bill summary.

“Demand for AI expertise is already high and will continue to grow,” Cantwell said in the release. “This bill will open doors to AI for students at all levels and upskill our workforce to drive American tech innovation entrepreneurship and progress in solving the toughest global challenges.”

The bill would also direct NSF to create publicly available playbooks about introducing AI into classrooms for pre-K through 12th-grade students, with “consideration for rural and economically depressed areas.”

NSF would also be granted authorization to hold a grand challenge for AI education and training that would include strategies for upskilling 1 million workers in the United States. in AI-related areas by 2028. Bipartisan Senate legislation released earlier this month also charges NSF with administering a grand challenge, with $1 million prizes awarded for innovations in AI.   

The bill from Moran and Cantwell also calls for related frameworks that “promote increasing the number of women who receive AI education and training” and ensure that “rural areas of the United States are able to benefit from artificial intelligence education and training.”

“Artificial intelligence has tremendous potential, but it will require a skilled and capable workforce to unlock its capabilities,” Moran said. “If we want to fully understand AI and remain globally competitive, we must invest in the future workforce today.”

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“The more we cut, the more the ideas that are being proposed to NSF in quantum, in AI will not be funded. And guess what; who’s funding them and the people? It is our competitor,” NSF Director Sethuraman Panchanathan said, in reference to global competitors. 

“This is a national security issue,” he added, “and this is not something that we should take lightly at all. I’m extremely worried.”

Panchanathan’s comments came in response to a question from Rep. Zoe Lofgren, D-Calif, ranking member of the Committee on Science, Space and Technology, who asked about the impact that further cuts might have on research priorities on top of the roughly 8% cut the science agency already took in 2024 appropriations.

In response to that same question, Dan Reed, chair emeritus of the National Science Board, called the cuts “devastating.” 

“We’re leaving the future on the table,” Reed said. “And I would add that those cuts potentially are convolved with inflation and so the real spending cuts are actually much larger.”

The hearing before the House Oversight Subcommittee on Research and Technology comes after NSF and other science agencies experienced cuts in the fiscal year 2024 appropriations passed by Congress. 

Notably, those funding levels fell short of what lawmakers previously authorized to carry out the work of the CHIPS and Science Act, which was signed into law in 2022 to boost U.S. production of semiconductors and to support scientific research and development in emerging technology areas.

President Joe Biden’s proposed budget seeks an increase for NSF, bringing its funding from $9.06 billion in the fiscal year 2024 appropriations to $10.18 billion. But even that would still put NSF’s funding below CHIPS Act targets. 

In response to a question from Rep. Scott Franklin, R-Fla., about the research NSF is able to fund, Panchanathan said the agency generally gets more than 40,000 proposals each year and is able to fund a quarter of those on average, but roughly 30-35% of proposals it receives have achieved NSF’s “gold standard” of merit review and could be funded.

Panchanathan said he’s worried about researchers being rejected for insufficient funds when their proposals were ranked high and not continuing to try. “The lost opportunity is not even part of this. If we factor that in, it’s even more than what we’re talking about,” he said.

Rep. Mike Collins, R-Ga., the chairman of the subcommittee, acknowledged the agency’s funding levels in opening remarks, noting that “the NSF’s budgetary constraints, coupled with evolving geopolitical dynamics and shifting research priorities, underscore the importance of our discussion today.”

Similarly, Rep. Haley Stevens, D-Mich., the subcommittee’s ranking member, pointed to the panel’s work on the science portion of the CHIPS and Science Act, which authorized the NSF’s Directorate for Technology, Innovation and Partnerships and called for a doubling of NSF’s budget by 2027. 

“We can’t just say that we’re competing against China. We must put our money where our mouth is,” Stevens said.

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The roadmap outlines policy areas the working group believes “merit bipartisan consideration” and summarizes findings from that group’s insight forums held last year with AI leaders from industry, academia and advocacy groups. In addition to boosting AI spending, the report also covers deepfakes, upskilling workers, and fully funding a National AI Research Resource in its priorities.

“We hope this roadmap will stimulate momentum for new and ongoing consideration of bipartisan AI legislation, ensure the United States remains at the forefront of innovation in this technology, and help all Americans benefit from the many opportunities created by AI,” the working group members said in the roadmap.

The Bipartisan Senate AI Working Group is composed of Sens. Mike Rounds, R-S.D., Martin Heinrich, D-N.M., Todd Young, R-Ind., and Senate Majority Leader Chuck Schumer, D-N.Y. The roadmap comes as legislators in both chambers have explored myriad ways to address the risks and potential of the booming technology but haven’t yet passed broad AI legislation. 

Previewing the announcement last week, Schumer said their approach isn’t to develop one comprehensive plan but rather targeted legislation that addresses specific issues. In a press conference Wednesday, Schumer said the working group’s deliberations were never meant to supplant the work of congressional committees.

“We are very, now, hopeful that the bipartisan momentum that we fostered and the recommendations we made will extend into the committees and their process,” Schumer said. “If anything is going to be accomplished, it has to be bipartisan and it’s going to be done by the committees.”

Schumer also said he plans to meet with House Speaker Mike Johnson, R-La., “in the very near future to see how we can make this bipartisan effort bicameral.”

Among the recommendations in the roadmap, the working group encouraged the executive branch and the Senate Appropriations Committee to reach “as soon as possible” the $32 billion in annual spending on non-defense AI innovation that was proposed by the National Security Commission on Artificial Intelligence in its final report. 

That panel, which was made up of people from industry and academia, was tasked with making recommendations to the president and Congress on AI and issued its conclusions in 2021. At the time, their recommended investment would have doubled government research and development spending.

Lawmakers also underscored the need to fund accounts that haven’t reached their full funding potential under the CHIPS and Science Act, “particularly those related to AI.” Among the accounts the lawmakers listed was the National Science Foundation’s Directorate for Technology, Innovation, and Partnerships, which is aimed at boosting U.S. competitiveness in critical and emerging technologies through research.

Additionally, authorizing a full-scale National AI Research Resource was included as a policy priority. The NAIRR, which operates under NSF, is currently in a pilot phase and is providing access to industry and federal tools and data needed for AI research, such as access to supercomputers and generative AI models. Lawmakers and administration officials, however, have stressed the need for legislation to codify and fully fund the resource.

The roadmap was immediately met with praise and criticism Wednesday.

Linda Moore, president and CEO of TechNet, applauded the roadmap’s support for funding, including for the AI Safety Institute and legislation to authorize the NAIRR. TechNet, a network of technology CEOs and senior executives, worked to advocate for the passage of the NAIRR legislation with the bill’s House sponsor, Rep. Anna Eshoo, D-Calif., Moore said in a prepared statement. 

By providing funding for those initiatives and others, “Congress will empower a new generation of AI leaders, expand innovation and opportunity beyond Silicon Valley, and keep America at the forefront of scientific development for generations to come,” Moore said.

Meanwhile, Nicole Gill, co-founder and executive director of Accountable Tech, called the roadmap “another proof point of Big Tech’s profound and pervasive power to shape the policymaking process.” Accountable Tech is an organization focused on reining in Big Tech.

Gill called the insight forums a “dream scenario for the tech industry” and alleged that companies “played an outsized role in developing this roadmap and delaying legislation.” She also said the roadmap “is most concrete in offering a roadmap for industry priorities while merely hand-waving toward many of the most pressing challenges associated with the widespread adoption of AI.”

This story was updated May 15, 2024, with comments from Schumer’s press conference Wednesday.

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The chatbot is aimed at making the process of looking for NSF grants easier, Dorothy Aronson, the agency’s chief AI officer told FedScoop. It will provide information about grants based on inputs from users about who they are and their research and can answer questions about the process, as it was trained using NSF’s proposal guide, Aronson said.

Aside from testing the chatbot itself, the process has also been a test of sorts for the agency, according to Aronson. 

“The most important thing about this exercise that we’re running is that it’s not only to create the chatbot; I think that’s a nice side effect,” Aronson said. “From my perspective, it’s to experience what it’s like to do a rapid implementation … of an AI capability.”

Aronson said they’re hoping to engage the NSF community in a conversation about responsible AI, how they can do that well at the agency, and get people thinking about the future.

The pilot comes as agencies across the government are experimenting with AI. Already the government has disclosed at least 700 use cases, and chatbots appear to be a popular use of the technology, with agencies like the Department of State and Centers and Disease Control and Prevention recently noting they’re using such tools. 

Although the chatbot is NSF’s first pilot of a commercial platform and first for a public-facing tool, it’s not the first AI use for the agency. NSF lists several use cases on its public inventory, and Aronson said the agency has developed smaller AI solutions before, such as a tool that suggests reviewers for people who work with NSF on research. 

The first three months of the pilot are wrapping up, marking the end of the development phase, according to an NSF spokesperson. Now, the agency is “beginning to widely demonstrate the pilot, gather feedback, and further train and hone the model.” NSF is working with Spatial Front, Inc., a small business contractor, on the chatbot. 

The chatbot will be particularly useful to people outside larger universities, which typically have offices dedicated to things like NSF grants, according to Aronson, who is also the chief data officer and has served as the CIO of the agency.

“This is most important to smaller universities or underrepresented communities who do not have access to large offices within their university that can help facilitate that work,” she said. 

Creating the tool has also been different from the norm for IT solutions, which start with what the end result will look like, Aronson said. With AI, the component is educated to give the desired answers and the interface comes after. “It’s a completely different way of working,” she said.

Aronson said the agency has put the first skin — or appearance — on the chatbot and shopped it out to customers to get feedback. Now, NSF is thinking about two directions: how to improve the chatbot further and what the next AI pilot will be, she said.

Going forward, Aronson said the agency plans to do a few pilots to find additional capabilities of the technology. “In the next one, we know we want to do something more complicated, ultimately, and we’ve broken that more complicated longer-term objective into smaller bits,” Aronson said. 

She also noted that while funding is tight this year, NSF is being “scrappy” about ways to move forward, and using the pilots to help figure out what to ask for in fiscal year 2026 so it has a “legitimate funding bucket for AI.” 

Additionally, Aronson said she’s working with the Federal CIO and CIOs at other agencies to explore the idea of “a journey map of data and AI and IT initiatives that would allow all of the federal agencies better insight into what other people are doing.” 

That journey map would allow agencies to get a picture of what others in the federal government are working on and learn about other solutions they could leverage, she said. An agency, for example, could use the map to see if another agency is developing a testbed for AI, identify extra compute power available elsewhere, or review an existing generative AI policy. 

If agencies could see “where the expertise was across the federal government, we could leverage each other’s expertise instead of each of us evolving to have that level of knowledge on our own,” Aronson said.

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The projects range from research into language model safety and synthetic data generation for privacy, to developing a model for aquatic sciences and using AI for identifying agricultural pests, according to a release from the NSF. Of those projects, 27 will be supported on NSF-funded advanced computing systems and eight projects will have access to those supported by DOE, including the Summit supercomputer at Oak Ridge National Laboratory.

“You will see among these 35 projects’ unbelievable span in terms of geography, in terms of ideas, core ideas, as well as application interests,” NSF Director Sethuraman Panchanathan said at a White House event. 

The NAIRR, which launched earlier this year in pilot form as part of President Joe Biden’s executive order on AI, is aimed at providing researchers with the resources needed to carry out their work on AI by providing access to advanced computing, data, software, and AI models.

The pilot is composed of contributions from multiple federal agencies and private sector partners, including Microsoft, Amazon Web Services, NVIDIA, Intel, and IBM. Those contributions include access to supercomputers; datasets from NASA and the National Oceanic and Atmospheric Administration; and access to models from OpenAI, Anthropic, and Meta.

In addition to the project awards, NSF also announced the NAIRR pilot has opened the next opportunity to apply for access to research resources, including cloud computing platforms and access to foundation models, according to the release. That includes resources from nongovernmental partners and NSF-supported platforms.

Panchanathan described the appetite for the resource as “pretty strong,” noting that 50 projects have been reviewed as positive. But he said there aren’t yet resources to scale those 50 projects. “There is so much need, and so we need more resources to be brought to the table,” Panchanathan said.

While the pilot continues, there are also bipartisan efforts in Congress to codify and fully fund a full-scale NAIRR. Panchanathan and Office of Science and Technology Policy Director Arati Prabhakar underscored the need for that legislation Monday.

“Fully establishing NAIRR is going to take significant funding, and we’re happy to see that Congress has initiated action,” Prabhaker said, adding that the White House is hopeful “that full funding will be achieved.”

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The AI Grand Challenges Act, introduced this week by Sens. Cory Booker, D-N.J., Mike Rounds, R-S.D., and Martin Heinrich, D-N.M., calls on the NSF director to create and administer a competition that incentivizes technologists to “harness AI to address specific and measurable challenges to benefit the United States and serve the public good.” 

“Grand challenges and prize competitions can encourage creative solutions to complex problems using science, technology, and innovation,” Booker said in a statement. “The time has come for a prize program to further encourage innovation in artificial intelligence.”

Participants in the AI Grand Challenges Program would compete to solve problems identified by NSF, spanning categories including cybersecurity, national security, health, energy, transportation, agriculture, manufacturing and more. The General Services Administration would be charged with managing a website that lists the various competitions.

The challenges should represent “ambitious but achievable goals that utilize science, technology, and innovation to solve or advance solutions to problems to benefit the United States,” the bill states. Cash prizes would be no less than $1 million, per the legislation, though the NSF director has the discretion to offer non-cash prizes as well.  

Heinrich, co-chair of the Senate AI caucus with Rounds, said in a statement that the competitions will ensure that AI’s potential is “accessible to all Americans — not just a limited few in Silicon Valley.” The technology could be a game-changer in everything from “treating rare diseases to lowering costs by improving the efficiency of our electrical grid,” he added. 

Health-related competitions get a special call-out in the legislation, with $10 million set aside for the winner of the grand challenge for artificial intelligence-enabled cancer breakthroughs, which seeks “to advance medical breakthroughs to address 1 or more of the most lethal forms of cancer and related comorbidities.” The goal of this challenge, the bill states, is to produce innovations with AI that “increase the total quality-adjusted life years of those affected or likely to be affected by cancer.”

“The ability to make headway in the fields of science, technology and especially health care will be revolutionary and could even lead to the cures of many diseases,” Rounds said in a statement. “Grand challenges have proven successful in the ways to advance towards new scientific discoveries. AI advancements will improve the quality of life for all Americans. The sky is the limit.”

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The President’s Council of Advisors on Science and Technology voted unanimously in favor of the report Tuesday following a nearly hourlong public discussion of its contents and recommendations. The delivery of PCAST’s report will fulfill a requirement in Biden’s executive order on AI, which called for an exploration of the technology’s potential role in “research aimed at tackling major societal and global challenges.”

“Empowerment of human scientists” was the first goal presented by PCAST members, with a particular focus on how AI assistants should play a complementary role to human scientists, rather than replacing them altogether. The ability of AI tools to process “huge streams of data” should free up scientists “to focus on high-level directions,” the report argued, with a network of AI assistants deployed to take on “large, interdisciplinary, and/or decentralized projects.”

AI collaborations on basic and applied research should be supported across federal agencies, national laboratories, industry and academia, the report recommends. Laura H. Greene, a Florida State University physics professor and chief scientist at the National High Magnetic Field Laboratory, cited the National Science Foundation’s Materials Innovation Platforms as an example of AI-centered “data-sharing infrastructures” and “community building” that PCAST members envision. 

“We can see future projects that will include collaborators to develop next-generation quantum computing qubits, wholesale modeling, whole Earth foundation models” and an overall “handle on high-quality broad ranges of scientific databases across many disciplines,” Greene said.

The group also recommended that “innovative approaches” be explored on how AI assistance can be integrated into scientific workflows. Funding agencies should keep AI in mind when designing and organizing scientific projects, the report said.

The second set of recommendations from PCAST centered on the responsible and transparent use of AI, with those principles employed in all stages of the scientific research process. Funding agencies “should require responsible AI use plans from researchers that would assess potential AI-related risks,” the report states, matching the principles called out in the White House’s AI Bill of Rights and the National Institute of Standards and Technology’s AI Risk Management Framework.

Eric Horvitz, chief scientific officer at Microsoft, said PCAST’s emphasis on responsible AI use means putting forward “our best efforts to making sure these tools are used in the best ways possible and keeping an eye on possible downsides, whether the models are open source or not open source models. … We’re very optimistic about the wondrous, good things we can expect, but we have to sort of make sure we keep an eye on the rough edges.”

The potential for identifying those “rough edges” rests at least partially in the group’s third recommendation of having shared and open resources. PCAST makes its case in the report for an expansion of existing efforts to “broadly and equitably share basic AI resources.” There should be more secure access granted to federal datasets to aid critical research needs, the report noted, with the requisite protections and guardrails in place.

PCAST members included a specific callout for an expansion of NSF’s National Secure Data Service Demonstration project and the Census Bureau’s Federal Statistical Research Data Centers. The National Artificial Intelligence Research Resource should also be “fully funded,” given its potential as a “stepping-stone for even more ambitious ‘moonshot’ programs,” the report said.

AI-related work from the scientists who make up PCAST won’t stop after the report is edited and posted online next week. Bill Press, a computer science and integrative biology professor at the University of Texas at Austin, said it’s especially important now in this early developmental stage for scientists to test AI systems and learn to use them responsibly. 

“We’re dealing with tools that, at least right now, are ethically neutral,” Press said. “They’re not necessarily biased in the wrong direction. And so you can ask them to check these things. And unlike human people who write code, these tools don’t have pride of ownership. They’re just as happy to try to reveal biases that might have incurred as they are to create them. And that’s where the scientists are going to have to learn to use them properly.”

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But even the programmatic funding increases President Joe Biden is seeking for those agencies and others in fiscal year 2025 fall short of what Congress authorized in the CHIPS and Science Act, highlighting the difficulty to support agencies key to science and technology goals within the confines and partisan tensions of the budget process. 

Biden’s budget, released Monday, came shortly after Congress passed a “minibus” of six bills to fund agencies for the current fiscal year. Under those appropriations, NSF received $9.06 billion, a roughly  8.3% decrease from the previous year, and NIST received $1.46 billion, a nearly 12% decrease. 

“There will be real impacts across the research enterprise with this reduction to the U.S. National Science Foundation (NSF),” an agency spokesman said of the minibus funding level in a written statement. “It is difficult to place this in the context of rapid, large-scale science investments by our competitors such as China with the express purpose of outcompeting the United States.”

A NIST spokesperson, meanwhile, noted in a statement that certain CHIPS programs, such as those for manufacturing incentives and R&D, “received full appropriations in the CHIPS and Science Act” but said the agency “will continue to work with Congress to secure funding for initiatives that were authorized but not fully appropriated.”

The CHIPS and Science Act was signed into law in 2022 to boost U.S. production of semiconductors — an important component for technologies from phones to national security systems — and to support scientific research and development in emerging technology areas like artificial intelligence and quantum computing. 

To help achieve those goals, the statute authorized funding targets for key agencies, including NSF, NIST, and the Department of Energy’s Office of Science. But in the years since the bill’s passage, budget requests and funding bills haven’t met those marks, and Biden’s new budget and the recent appropriations passed by Congress continue that trend.

Matt Hourihan, associate director of research and development and advanced industry at the Federation of American Scientists, said his bottom line with both the minibus and budget is “that we’re not going nearly far enough in investing [in] U.S. science and engineering, to bolster innovation, bolster competitiveness, bolster domestic talent.”

Minibus tension

The cuts to NIST and NSF were met with disappointment from lawmakers on both sides of the aisle. Rep. Frank Lucas, R-Okla., chair of the House Committee on Science, Space and Technology, said in a statement to FedScoop that he was “disappointed in these funding levels” as a supporter of science and technology.

“Unfortunately, in our current fiscal environment we have to make difficult decisions and that’s reflected in this bipartisan, bicameral agreement. Our challenge is figuring out how to continue advancing American science and technology under these funding constraints,” Lucas said.

But House Democrats, while also unhappy with the funding levels, sharply criticized Republicans for the cuts.

“By forcing us to choose between these cuts or recklessly shutting down the federal government, extreme MAGA Republicans and Speaker [Mike] Johnson have handed our competitive edge to China on a silver platter,” Rep. Zoe Lofgren, D-Calif., ranking member of the Committee on Science, Space and Technology, told FedScoop in a statement. Lofgren called the funding cuts “a blow to our economic competitiveness and national security” and said the biggest impact will be to the workforce.

Rep. Haley Stevens, D-Mich, the ranking member on the House Science Subcommittee on Research and Technology, similarly called the minibus decreases a “self-inflicted wound on American innovation and global leadership” in a comment provided to FedScoop. She also added that the “losses are solely in the hands of Republicans who pushed for these cuts.”

Areas of impact

The minibus included a decrease in the programmatic funding for NIST’s scientific and technical research and services account, from $890 million in fiscal year 2023 to $857 million in the minibus. That’s the first time the account — which funds things like AI, cybersecurity, quantum, and advanced technology research — has been cut, a House Science Committee Democratic staffer told FedScoop. 

A Senate Republican aide noted that NIST received a large funding increase for that account in fiscal year 2023 and said the minibus level is still higher than the funding for that account in fiscal year 2022.

That account also received $223 million in congressionally directed spending, or “earmarks,” which if included, is an increase from the account total with earmarks for the previous year. 

While the minibus did provide NIST with up to $10 million to set up the AI Safety Institute outlined in Biden’s executive order on the technology, the House Science Democratic staffer said other areas of the agency’s research could end up seeing cuts instead. The funding to establish the institute wasn’t the additional $10 million on top of existing appropriations for which a bipartisan group of lawmakers had advocated.

For NSF, the cuts will likely mean fewer opportunities for students and young scientists, as the agency’s work includes things like supporting graduate fellowships, education and training, Hourihan said. “All those programs can be affected by cuts of this magnitude,” he said.

The cuts could also impact NSF’s new Technology Innovations and Partnerships Directorate, which was established under CHIPS and is aimed at boosting U.S. competitiveness in critical and emerging technologies through research.

That directorate was funded through a supplemental last year and wasn’t part of the omnibus, a House Science Democratic staffer noted. Now it’s in “starvation mode” and may have to compete with other directorates for funding, the staffer said.

Budget shortfall

Biden’s budget requests increases for both NSF and NIST’s baseline funding. NSF would get $10.18 billion and NIST would receive $1.5 billion. 

Even though there are increases for quite a few agencies in the president’s budget, Hourihan said they’re “not nearly as much” as the Biden administration has proposed in the past and “a far cry from the CHIPS and Science targets.” 

The White House request “is a function of the tight spending caps that are in place under the Fiscal Responsibility Act that Congress reached last year,” Hourihan said. That legislation was a compromise deal that raised the debt limit and placed caps on defense and nondefense discretionary spending for fiscal years 2024 and 2025.

Hourihan estimates the budget, as is, would be an $8.5 billion shortfall from what was authorized for NSF, NIST and the DOE’s Office of Science in the CHIPS Act legislation.

Mark Becker, president of the Association of Public and Land-grant Universities, also noted the shortfall in a statement on Biden’s budget Monday, calling the request “a retreat from the bold vision outlined in the CHIPS and Science Act.”

“The funding bills Congress passed last week take a significant step backward on these priorities and the administration’s proposal for the next Fiscal Year falls short of addressing the scale of the challenge,” Becker said.

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During a Wednesday event on U.S. investment in R&D, the White House Office of Science and Technology Policy, National Science Foundation and National Science Board discussed findings in The State of U.S. Science and Engineering 2024 report, including the fact that the U.S. spent $806 billion, or 3.5% of its gross domestic product, on R&D in 2021.  

While officials were eager to share R&D successes from the federal government, they also looked to the report to shed light on workforce development needs for STEM-related fields, as well as the need to enhance educational opportunities for domestic students. 

“R&D is how we open the doors so that the future can be better than the past; it’s how we overcome the limitations of today and step into a better tomorrow,” OSTP Director Arati Prabhakar said during the event. “This report and the president’s budget both remind us of the tremendous strengths that we have here in America with our R&D capabilities, and they also start us on this important path to the work ahead.”

President Joe Biden’s fiscal year 2025 budget leans into innovation through R&D efforts: A fact sheet OSTP shared with FedScoop highlights a request for a 36% funding increase (to a reported $900 million) for NSF’s Directorate for Technology Innovation and Partnerships, along with $606 million for the Department of Energy’s Office of Science to “integrate supercomputing, AI and quantum-based technology for developing the next-generation high-performance computing systems.”

“Most of these innovation-intensive industries, of course, grew out of prior federal R&D investments,” Prabhakar said. “If you think about that, that is true in fields that are diverse as artificial intelligence and new medicines and clean energy, so I think it’s a very consistent theme.”

Additionally, OSTP shared in the release that artificial intelligence R&D funds will be spread across federal agencies to further the development of responsible AI, citing a budget request of $729 million for NSF, a 10% increase, including $30 million for a second year of the National AI Research Resource pilot. 

An OSTP spokesperson shared in an email that the FY 2025 budget also includes a reported $32 million request to support the AI talent surge, and pointed to upcoming Office of Management and Budget issuance of AI guidelines for government to both address risks and encourage innovation. 

OMB “will soon issue the first governmentwide policy to mitigate the risks and harness the benefits in the federal government’s own use of AI,” the spokesperson said. “To fully deliver on this mission, we need the right people. President Biden launched an AI talent surge to bring more AI professionals into the Federal government to help us achieve our ambitious AI agenda. … We’re very excited about the talent we’ve brought on to date, and the talent we will bring on to work on high-priority AI projects.”

The spokesperson noted the Presidential Innovation Fellows, the U.S. Digital Corps and the U.S. Digital Service as some of the tech talent programs that have been advancing the goals of the administration where the AI talent search is concerned. 

Still, the country can’t rely solely on those programs, given the fact that occupations requiring STEM knowledge account for 24% of the U.S. workforce, and 19% of all STEM workers were born abroad, per the report. NSB Chair Dan Reed said the flow of domestic talent into the STEM workforce has to increase. The total STEM workforce is around 37 million individuals, a mix of those with at least a bachelor’s and those with technical skills who do not have at least an undergraduate degree. 

Reed acknowledged the value of attracting foreign workers, calling the country “a global magnet for talent. That’s been one of our superpowers, that the best and the brightest on the planet want to study and work here. We have to preserve that, but it’s not a given. They come because they see opportunities; we have to continue to create those opportunities.”

For the domestic workforce, Reed said there is cause for concern, and it starts with education.

The NSB chair referenced the report’s findings of a “sharp decline” in elementary and secondary education mathematics performance, and the fact that women and minorities are underrepresented when it comes to bachelor’s and graduate degrees in science and engineering.

“We have to improve access to higher education as students are to pursue advanced STEM degrees,” Reed said. At the same time, the country “must continue to welcome international students from around the globe and to implement policies that entice [and] enable them to stay and work here after they receive their degrees.”

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“It takes a lifetime to build a reputation; it takes a moment to lose it,” Terry Carpenter, who was announced as NSF’s CIO in January, said of generative AI and its risks at the Elastic Public Sector Summit, produced by FedScoop.

The concern, Carpenter elaborated, is that despite the power some of these AI tools hold, if not used responsibly and thoughtfully, they can lead to unintended and harmful outcomes.

“There’s some reality to that fear,” he said. So far the agency’s approach in considering generative AI models has been: “Where can we use this effectively to maintain our high standards and can we assure that the outcome that we get from it is what we intend?”

Carpenter continued: “So when you think about … our reputation of giving money to the right research for the betterment of society, it’s really important to us that we uphold the standards of the merit review process.”

While NSF hasn’t outright forbidden the use of large-language, generative AI models across its enterprise, Carpenter said the agency has banned the use of such tools that are “public-facing” — like commercial versions of OpenAI’s ChatGPT or Google’s Gemini — to review research proposals submitted to the agency for funding consideration.

“So when we looked at the realities of what ChatGPT and other large language models could provide, you know, when they’re riding out there on that external data, you have to really think about: Well what data am I giving it? Where is that data? And how sensitive is that data?” Carpenter explained. “So we looked at those kinds of things and we said, ‘You know what, we’re not ready yet.’ So we’re going to not allow the public-facing tool sets to be applied to review proposals.”

That led to the creation of a policy at NSF “that says you cannot use [public-facing generative AI] to review a proposal,” he said.

However, that’s not a blanket ban. Carpenter highlighted that the agency is conducting an internal generative AI pilot: “a chatbot to try to help our partners and customers out there that are trying to seek grant monies to know whether or not they should try to write a proposal, and if they do write a proposal, how can we help them in that process,” he said.

The pilot is in the early stages and hasn’t yet been opened to the public.

The decision to move forward with the chatbot came about after NSF made an open call for ideas, through which it received 79 submissions, according to the CIO. After matching those ideas to key areas in which NSF leadership thinks generative AI is applicable — insight generation for the grant-awarding process, internal process enhancement, and improvement of customer and employee experience — and running them through what Carpenter called “a risk-based decision model,” the agency landed on just the one.

On top of that, while NSF employees are forbidden from using generative AI for reviewing proposals, the proposers themselves are allowed to use the technology in developing their submissions, Carpenter acknowledged. The agency just requires those who do so to disclose how they used the technology in their proposal “to gain learning and transparency in that,” he said.

“I think there’s a lot of learning to go,” Carpenter said. “We have to figure this out. It’s not going away. And I think a lot of the commercial industry and our partners are helping us to think through how do we apply our own internal data, and where can we assure the protection of the proprietary data that we’re given in the proposal process. We have a duty to protect that for the people that propose, and that’s what we’re thinking about.”

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