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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Homeland Security will partner with the Israel National Cyber Directorate (INCD) to create the Israel-U.S. Binational Industrial Research and Development (BIRD) Cyber program that will focus on improving the cyber resilience of critical infrastructure.

BIRD Cyber will provide grants of $1.5 million per project to companies and research institutions in both nations.

“The new BIRD program advances the U.S.-Israeli partnership through cyber innovation and collaboration to build more secure and resilient infrastructure,” said Kathryn Coulter Mitchell, senior official within DHS’ Science and Technology Directorate. 

“We welcome the opportunity to cooperate with INCD and build on our work with the BIRD Foundation to develop innovative technologies that reduce risk to our cyber and physical infrastructure and that lead to enhanced safety for both our nations,” Mitchell said in a press release.

The $1.5 million BIRD Cyber Call for Proposals are looking to fund projects that include participants from both countries. Recipients of the funding will include companies, universities and research institutions.

The scheme is focused on piloting new technology that may help to improve security architecture, real-time risk assessment and data analytics.

The deadline for submitting proposals to this new Call for Proposals is November 15, 2022 with the winning projects being selected in March 2023.

The U.S.-Israel partnership is aimed at promoting the development of technologies of mutual benefit for both countries, building upon the BIRD Homeland Security program established in 2016 by DHS and the Israel Ministry of Public Security.

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Through the pilot program, data on the award amount, key dates and recipient is scraped from National Science Foundation-issued grant letters and meshed with payment information inside a blockchain token for real-time, transactional transparency.

The Bureau of the Fiscal Service has spent the last two-and-a-half years working on the proof of concept, which continues a 2017 effort, in light of grant recipients reporting they submit about 400 reports to agencies annually and 350 quarterly.

“This is taking a tremendous amount of their time and resources to just tell us how they spent their money,” said Craig Fischer, program manager at BFS, speaking at the ACT-IAC Imagine Nation conference in Hershey, Penn., on Monday. “Well, we know at least part of the problem that is involved in reporting is that we can’t always see where the money is going.”

BFS pays grant recipients using their banking number, so it knows who was paid. But what happens to the money after is harder to track — increasing the reporting burden on NSF- and Department of Health and Human Services-funded researchers.

By tokenizing federal payments, BFS can not only audit everywhere that token has been but use it to pre-populate reports like the SF-425 Federal Financial Report. One of the more time-consuming reports, SF-425 takes eight employees five hours to collect 15-plus data elements. The token, on the other hand, populates it in seconds.

“The next step is making those tokens turn back into a payment,” Fischer said. “So we’re now looking at creating those [application programming interface]s in the agency financial management systems.”

BFS built its proof of concept off NSF’s Award Cash Management $ervice (ACM$), a grant payment drawdown system, and it hopes to expand to HHS given the volume of grants awarded by that agency, Fischer said.

His agency is already working with the grants quality services management office (QSMO) inside HHS, which is standing up a marketplace of cloud-based systems and services from federal shared service providers like BFS for customer agencies. The Federal Demonstration Partnership is another customer, as is the Department of Commerce in the past, and the National Institute of Standards and Technology is an “important” partner setting standards around blockchain, Fischer said.

BFS’s proof of concept still has challenges to address, like the fact systems it’s trying to connect to don’t all live in cloud solutions that are Federal Risk and Authorization Management Program certified.

While the proof of concept relies on a permission-based version of the Ethereum blockchain — grant recipients requiring BFS’s permission to join the network and download its digital wallet — the agency is still working through all the token’s privacy ramifications, Fischer said.

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The grants are a part of ongoing efforts by the Air Force to boost the understanding of particle physics and its impact on computing. They focus on basic research, with many of the funded projects looking at how sub-atomic particles could create high-powered compute capabilities and secure communications systems.

The department’s “Million Dollar International Quantum U Tech Accelerator” kickoff event was held in September, but the money for the latest grants was only recently approved, according to a release from the Air Force.

The 17 grants gave recipients approximately $75,000, a small sum for the multibillion-dollar department, but the Air Force has “fast-tracked” quantum grants as it begins to place a higher priority on quantum technology research. Most of the recipients work at U.S. academic institutions. Funding also came from research at the Office of Naval Research and New York state technology offices.

“[The Air Force Office of Scientific Research] has a long history of collaborating with academia and industry on breakthrough science critical to the future of the Air Force and Space Force capabilities,” said Shery Welsh, director of the Air Force’s Office of Scientific Research. “We are thrilled to have supported the Million Dollar International Quantum U Tech Accelerator competition as it served as a perfect entry point for us to find talented, entrepreneurial, and energetic researchers dedicated to finding creative solutions that go beyond the classical Quantum Information Science (QIS) systems.”

Other parts of the military have recently started to work on quantum issues. The Defense Information Systems Agency is starting to research quantum-proof encryption methods that would be able to keep communications secure in a world where some computers could have the power to break traditional keys, DISA officials said in December.

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“From a business and management stand point, automation would be a game-changer,” Chief Financial Officer Mary Comans said Wednesday during the IBM Think Gov digital event, produced by FedScoop.

FEMA awards many types of grants, including emergency preparedness funds to state, local, tribal and territorial governments. Automating detail-oriented and medial tasks away from manual labor would help the government respond to crises such as the coronavirus pandemic and major storms. The summer only gets busier for the agency after hurricane season begins June 1.

RPA bots could help free up time for FEMA workers to concentrate on more critical decisions, Comans said.

The pandemic presents unique challenges to FEMA, both internally and externally. With emergency declarations covering the country and FEMA coordinating with 40 other federal agencies, moving to maximum telework only added to the agency’s challenges, she said. With employees out of the office, automating some of their work would alleviate strained resources.

Comans said her primary responsibility was the “health and safety of the workforce.” While RPA bots won’t solve everything, she said being able to automate more tasks would be extremely helpful in the agency’s modernization journey.

“The field of emergency management needs to evolve,” she said.

Among the ideas for bots are validating upfront eligibility for grant recipients or streamlining the process for assigning funding. Automation also would catch any accidental overpayments or payments to the wrong organization, Comans said.

“We need to ensure that at the end of the day every dollar goes to the survivor that needs it,” she said.

Other agencies, like the General Services Administration, have also turned to bots as a coronavirus-response tool. One of GSA’s RPAs compiled infection data from countries where federal buildings are located. The data helped inform the government’s situational awareness and the potential risk of infection for federal workers.

Groups like the Defense Innovation Unit have also prioritized automation technology more broadly, seeking machine learning solutions to advance the complexity of the tasks bots can do.

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For NSF CIO Dorothy Aronson, the experiment — which involves giving documents the equivalent of “digital fingerprints” — represents more than just finding a new way to solve an old problem. It also offers a glimpse of how the expertise of data scientists, together with modernized technologies, can potentially accelerate the government’s efforts in identifying and funding innovative ideas.

“I’m fantasizing here, but if you’re a citizen, you could send any proposal for innovation to a single [government] location and it would be automatically distributed, or suggestions would be made, to various federal organizations,” she said. “We’re just starting off with little experiments. But there’s a lot of benefits that could come from this.”

That vision may seem like a pipe dream for the thousands of scientists, engineers, academic institutions and entrepreneurs who apply each year to 26 federal grant-making agencies and more than 1,000 programs nationally. But for NSF, which accounts for roughly 20% of federal support to academic institutions for basic research, the technology foundation to build on that vision is now largely in place, according to Aronson.

Capitalizing on modernized IT   

The challenge facing NSF and other grant-making agencies — including the National Institutes of Health, which is working with NSF on the project — is how to share and compare proposals without exposing private information and potentially valuable ideas to the public.

NSF CIO Dorothy Aronson

“We often get multiple ideas that have a very high degree of similarity and we don’t want to fund that same idea multiple times,” explained Aronson. “So we have to work hard to figure out where there’s duplication.”

Streamlining the workload of program officers and automating as much of the proposal process as possible is “a perennial objective,” said Aronson. “This is not a new problem. It’s just one that we didn’t have the opportunity to solve before.”

What has changed, she said, is a combination of newer technology capabilities and “the availability of people who know the tools used by data scientists in order to create and apply the concepts [we needed] to compare the proposals.”

NSF already had the technology in place to convert PDF and other types of documents into machine-readable formats. And about five years ago, it had begun investing in an enterprise data warehouse, which provides greater flexibility than traditional transactional database systems.

“That was a very important transition for us because it put the data more closely into the hands of the customers,” said Aronson. “They didn’t have to know tools like SQL, for example, to derive the information they needed. And that allowed us to go to things like dashboards for executives.”

Since then, NSF also began gradually moving much of its IT operations, including the enterprise data warehouse, into a cloud environment. That’s helped give NSF the ability over the past two years to capitalize, for instance, on language processing capabilities and artificial intelligence, according to Aronson.

All of those technology upgrades, however, weren’t enough to solve a critical problem: How to simultaneously mask the content of proposals, for privacy protection, and still give program officers a form of visibility into how one grant proposal was similar or different from thousands of others.

What NSF ultimately needed, explained Chezian Sivagnanam, NSF’s chief enterprise architect, was a way to create a mathematical abstraction, or “fingerprint,” for each proposal that could be compared to other documents, each of which typically runs 15 pages in length and includes a variety of images. However, that fingerprinting process also has to work in a way that can’t be reversed engineered, in order to prevent someone from exposing the underlying content.

Data scientists to the rescue

Aronson said the big “breakthrough for us” occurred when NSF began “bringing people into our organization who understood how to apply data science principles and look at problems through the lens of a data scientist. It opened a wider world to us because of the knowledge base of what other data scientists had already created.”

That led to discussions with a number of data science experts and a variety of testing sprints, according to Sivagnanam. “Luckily, we found an algorithm being used within NIH, called Word2Vec, that basically converts document content into numbers. It then applies mathematical statistics on top of these numbers and looks for cosine similarities to relate one document with another,” he explained.

There was just one more catch, he said. “Once we converted the documents, we needed to put the results in a common infrastructure.” That’s where the capabilities of a blockchain and a distributed ledger entered the picture.

“The idea is to score each proposal [for similarities] then build this ledger, scale this up, so that going forward, every grant that comes in through all these organizations will get in this ledger,” Sivagnanam said. “The ledger has the analytical capability that when it finds a close scoring match, it then automatically triggers an alert to the respective program officers on both sides saying, ‘Hey, there is something similar between these proposals. You may want to talk about them further,’ as a pre-conditional exercise.”

NSF’s blockchain development work gained traction early last year from the General Services Administration’s 10x program — a kind of incubator investment fund that supports promising technology projects that can scale across the federal government or improve public services.

“The blockchain part is important,” Sivagnanam said, “because the proposals may come in two or three years after one another. So you need to make sure there are immutable records…with the blockchain monitoring what historically has happened.”

Aronson made it clear, the process, for now, is still in a “manual” mode. “We’ve got the logic together that allows us to create the fingerprints. And we’re able to identify potential overlap. But in order to make it a real-time capability, we need something that will automatically convert a proposal to a fingerprint, add it to the blockchain and then communicate to everybody else on the chain — so it would be a constant conversation,” she said.

“Because we really didn’t have everything in place two or three years ago, this idea really wouldn’t have been actionable,” she said.

She now believes the time is no longer far off when, if a proposal comes to NSF, but is better suited for the Department of Energy, it could be routed and flagged within minutes instead of months. “It would allow us as a federal government to be more efficient at our distribution of innovative proposal ideas.”

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The DOE’s Office of Science indicated its intent to issue a funding opportunity announcement in fiscal 2020 to establish two or more of what it calls Quantum Information Science Centers. These centers will be the “flagship” of the quantum push, Paul Dabbar, DOE undersecretary of science, said in a release.

“This initiative ensures that America will remain a world leader in this pivotal, rapidly advancing field, which is creating fundamentally new ways of obtaining and processing information,” Dabbar said.

DOE issued a notice of intent and request for information on how the department should structure future quantum centers and review applications. DOE hopes these centers will lay the foundation for next-generation processing.

The centers’ development was mandated by the National Quantum Initiative Act, which was signed into law in December. The law provides more than $1.2 billion to build a framework of private, public and academic research to develop quantum technology.

The development of quantum computing, which utilizes advanced technologies that would exponentially grow computing power, is expected to disrupt modern technology and change the cybersecurity game, FedScoop reported last year.

In April, DOE announced $40 million available in grant funding for multidisciplinary teams developing advanced algorithms and software for quantum computers.

Responses to the RFI are due 45 days from its posting on the Federal Register.

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Karsun Solutions LLC on Thursday received a five-year, $80-million contract to develop technology to expedite the Federal Emergency Management Agency’s grants process before and after disasters.

The Grants Management Modernization program will use agile development to merge FEMA’s 10 legacy IT systems into a single platform for the agency’s 40-plus grant programs.

Upon completion of the platform—called FEMA Grants Outcomes, or FEMA GO—citizens and first responders will be able to apply for and receive federal disaster and non-disaster grants faster, said Terry Miller, spokesman for Northern Virginia-based Karsun.

“We’re talking about individuals who could be on the ground in a hurricane like Katrina,” Miller said. “You have people definitely hurting on those types of occasions.”

The contract comes after Puerto Rican officials recently criticized FEMA for the slow arrival of disaster recovery funds for the 2017 hurricanes Irma and Maria, and California officials made similar complaints about the devastating 2017 and 2018 wildfire seasons. Federal agencies do have different rules for Puerto Rico because it’s a U.S. territory.

FEMA grant applications are traditionally paper driven, when a streamlined, secure process could prevent against fraud while distributing money quicker post-disaster, Miller said.

The solution will also improve the process for non-disaster funding like firefighter grants, Miller said. Fire departments often apply on a yearly basis, reporting much of the same information.

“Our prototype showed ways you could pull legacy information into it, so things could be pre-populated,” Miller said.

The Department of Homeland Security employed a new bid process with the contract, asking applicants to submit a 20-minute video detailing past performance, key personnel, the technical approach, and the prototype.

Five companies were selected to give an hour-long presentation walking through different scenarios, followed by an hour of questions and answers.

“It’s not something we’ve seen other industries do before,” Miller said. “We definitely appreciated the way they went about it.”

Karsun is an IT modernization firm specializing in software development, cloud services and analytics—all of which are covered in the single award, blanket purchase agreement with DHS.

“The average award time of a grant varies widely based on the type of grant,” said Daniel Llargues, FEMA spokesman, in an email. “A simpler and more efficient grants lifecycle process will naturally result in faster grant awards, which means recipients will receive assistance to prepare for, mitigate, or recover from disasters sooner.”

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Since 2014, DOE’s Office of Science has assessed and invested in early quantum simulations, machine-learning algorithms and software stacks. The supercomputers are expected to revolutionize work in the fields of quantum physics, chemistry and biology.

“[B]ut the need to address basic research knowledge gaps persists,” according to DOE’s funding opportunity announcement.

“Continued investments in quantum computing will focus the intellectual prowess of our scientists and engineers on the development of technologies that the private sector can convert into commercial applications to improve the lives and security of all Americans,” said Energy Secretary Rick Perry in the announcement.

Some projects may develop new programming languages and debuggers adaptable to various quantum computing systems, while still allowing them to interface with classical computers.

“While prototype QC systems currently exist and the qubits that they support are scaling up; the hardware technologies and the proposed architectures vary and the applications that these early systems are useful for are limited,” according to the announcement.

DOE envisions using future quantum computers for researching how to manipulate electrons to imitate processes like logic and photosynthesis or to create biologically inspired, molecular machines.

Universities, national laboratories, industry and nonprofit teams seeking more than $2 million annually may apply.

The competitive grants will be awarded by peer review to two or three five-year projects. Awards are capped at $2.5 million annually, and funding after the first year is dependent on congressional appropriations.

Letters of intent are due May 1, 2019, and final applications by May 31, 2019.

The announcement comes on the heels of several initiatives around the federal government to boost quantum computing research. At the close of 2018, President Trump signed the National Quantum Initiative Act into law, proposing to spend more than $1.2 billion over the next five years to establish a coordinated framework between federal research labs, academia and the private sector to advance quantum technologies. And in September, the administration issued a national strategy for advancing the development of the technology.

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Staffers for Rep. Virginia Foxx, R-NC, told FedScoop Wednesday that she reintroduced the legislation last week, with the hopes of repeating its 2018 success in the House and securing bipartisan support.

Once again cosponsored by Rep. Jimmy Gomez, D-Calif., the bill aims to make the reporting process for the government’s $600 billion in annual grant spending more efficient by requiring agencies use nonproprietary data taxonomies and identifiers for grantees. The plan is to standardize how the government reports its grants data much in the same way the DATA Act did for agency spending.

The current identifiers, maintained by contractor Dun & Bradstreet, are known as the data universal numbering system, or DUNS. Users of that system must have a DUNS Number and can request one for free from the company.

Foxx, as well as open data groups like the Data Coalition, have argued in the past that by moving to an open source, nonproprietary identifier system, the government can gain more visibility into how agencies manage their grant spending.

The original GREAT Act passed the House in September in a voice vote and even saw a companion bill develop in the Senate. That Senate bill reported out of its Homeland Security and Governmental Affairs Committee in November but never drew a floor vote in a crowded legislative calendar.

The GREAT Act follows other bills introduced last year that didn’t make it out of Congress before the legislative session ended. Last week, Reps. Will Hurd, R-Texas, and Robin Kelly, D-Ill., reintroduced their Federal CIO Authorization Act, which aims to codify the federal CIO position in law.

Jessica Yabsley, the Data Coalition’s senior director of communications, said in an email that the GREAT Act was one of several reintroduced bills the organization is supporting in 2019, including the Financial Transparency Act, which directs eight financial regulatory agencies to set specified data standards for information collected from the financial industry, and the Searchable Legislation Modernization Act, which calls for “nonproprietary, machine-readable data standards” to be applied to congressional documents to make them more accessible to the public.

The GREAT Act has been assigned to the House Committee on Oversight and Reform.

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