For Sarah Nur, Treasury’s chief information security officer and associate CIO for cyber, that arcade-style battle to protect federal networks from adversarial threats is “nonstop.”

AI has made it “a lot easier” for “unsophisticated threat actors … to create these attack scenarios,” Nur said, “so that they can go ahead and launch and play around in our current infrastructure.”

Speaking Tuesday at a Scoop News Group-produced GDIT event in Washington, Nur and other federal cyber officials spoke of the proliferation of AI-fueled cyberattacks and how much more critical coordination and information-sharing has become as use of the technology among amateur hackers has surged.     

Cynthia Kaiser, deputy assistant director of the FBI’s cyber division, said she’s seen “a crop of adversaries who are becoming at least mildly better” at their craft due to AI. The technology eases hackers’ ability to perform basic scripting tasks and identify coding errors, Kaiser said, while deepfakes are leveraged in social engineering campaigns and increasingly refined spearphishing messages.

“A beginner hacker can go to the intermediate level,” she said, “and even the most sophisticated adversaries can be more efficient.”

Gharun Lacy has also observed a leveling up among threat actors in his role as deputy assistant secretary for cyber and technology security in the State Department’s Bureau of Diplomatic Security. Those adversaries are “using AI as an amplifier,” bettering their best skills as a result. 

“Do you have a threat actor that is extremely proficient in human engineering? Then they’re going to get better at human engineering,” Lacy said. “That phishing email will now call you by a nickname that you had in high school.” 

The Treasury Department is especially susceptible to this onslaught of new-age threats given its role as the federal government’s sanctions arm, Nur said, not to mention the fact that the financial industry is one of the most targeted critical infrastructure sectors. Hackers today can simply look up a CVE, plug it into an AI system and ask it to provide “an undetected attack scenario that I can utilize,” Nur said, noting that packages of this kind on the dark web are “ready to go.”

“I heard someone say ‘fight AI with AI.’ I get what that means,” Nur said, “and I think that’s a very key concept. We really have to look at leveraging AI to quickly detect these anomalies and any kind of fraud or unusual suspicious activity.”

The silver lining for federal security officials is that AI still provides defenders with a decided advantage over attackers in cyberspace. The key to maintaining that advantage, they say, is doubling down on coordination with public and private-sector partners.

Kaiser said the use of large language models to “more rapidly draft text” for interagency memos and private-sector alerts represents “a huge win for everybody” in the battle against threat actors. 

At the State Department, the chief AI officer, chief data officer and members of the agency’s Center for Analytics have successfully leveraged AI in “reducing the noise in terms of threat intelligence,” Lacy said, sifting through “massive amounts of data” to make it “more actionable directly for us.” Streamlining data and threat intel leads to more valuable insights that State can provide to its partners, he added. 

“If I know this piece of information is not useful for me, but it may very well be useful to one of my private industry partners, I need to know how to get that information to them quickly,” Lacy said, noting that the White House has provided a quality blueprint for sharing intelligence and has encouraged agencies to be “very forthcoming now in terms of naming, blaming [and] shaming when incidents happen — and doing it quickly.”

Lacy pointed to a State Department collaboration with foreign ministries from the United Kingdom, Australia, Canada and New Zealand that brings together those countries’ cyber defenders in a quarterly meeting to “share a lot of information.” 

“I think we’re past the sharing; we’re on to collaborating,” Lacy said. “I think that’s … the phase we’re in right now. But the collaboration has to yield collective action.”

Treasury’s in a similarly collaborative mode at the moment, fresh off its launch last month of Project Fortress, a public-private partnership aimed at protecting the financial sector from cyber threats. Nur said the agency has been active in onboarding companies and organizations to the group, ensuring that participating financial institutions have access to top tools and are practicing good cyber hygiene before truly “aggressive AI attacks” become the norm.

Whether it’s meeting regularly with other CISOs, coordinating with international partners or establishing communication channels with industry, agency cyber officials across the board agree that mitigating AI-fueled threats will only be possible with more collaboration and better sharing of information.

“In the past, what really prevented us from sharing that information is that embarrassment, that reputational impact,” Nur said. “We can no longer think in those ways. We need to shift our mindset to say, ‘hey, look, we’re going to expect at least two to three a year, maybe even more, and that’s OK.’” 

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The State Department is no exception. According to Eric Stein, deputy assistant secretary for the Office of Global Information Services, the department’s eRecords archive system currently contains more than 4 billion artifacts, which includes emails and cable traffic. “The latter is how we communicate to and from our embassies overseas,” Stein said.

Over time, however, department officials need to declare what can be released to the public and what stays classified — a time-consuming and labor-intensive process.

The State Department has turned to cutting-edge technologies like artificial intelligence (AI) and machine learning (ML) to find a more efficient solution. Through three pilot projects, the department has successfully streamlined the document review process for declassification and improved the customer experience when it comes to FOIA (Freedom of Information Act) requests.

An ML-driven declassification effort

At the root of the challenge is Executive Order 13526, which requires that classified records of permanent historical value be automatically declassified after 25 years unless a review determines an exemption. For the State Department, cables are among the most historically significant records produced by the agency. However, current processes and resource levels will not work for reviewing electronic records, including classified emails, created in the early 2000s and beyond, jeopardizing declassification reviews starting in 2025.

Recognizing the need for a more efficient process, the department embarked on a declassification review pilot using ML in October 2022. Stein came up with the pilot idea after participating in an AI Federal Leadership Program supported by major cloud providers, including Microsoft.

For the pilot, the department used cables from 1997 and created a review model based on human decisions from 2020 and 2021 concerning cables marked as confidential and secret in 1995 and 1996. The model uses discriminative AI to score and sort cables into three categories: those it was confident should be declassified, those it was confident shouldn’t be declassified, and those that needed manual review.

According to Stein, for the 1997 pilot group of more than 78,000 cables, the model performed the same as human reviewers 97% to 99% of the time and reduced staff hours by at least 60%.

“We project [this technology] will lead to millions of dollars in cost avoidance over the next several years because instead of asking for more money for human resources or different tools to help with this, we can use this technology,” Stein explained. “And then we can focus our human resources on the higher-level and analytical thinking and some of the tougher decisions, as opposed to what was a very manual process.”

Turning attention to FOIA

Building on the success of the declassification initiative, the State Department embarked on two other pilots to enhance the Freedom of Information Act (FOIA) processes from June 2023 to February 2024.

Like cable declassification efforts, handling a FOIA request is a highly manual process. According to Stein, sometimes those requests are a single sentence; others are multiple pages. But no matter the length, a staff member must acknowledge the request, advise whether the department will proceed with it, and then manually search for terms in those requests in different databases to locate the relevant information.

Using the lessons learned from the declassification pilot, Stein said State Department staff realized there was an opportunity to streamline certain parts of the FOIA process by simultaneously searching what was already in the department’s public reading room and in the record holdings.

“If that information is already publicly available, we can let the requester know right away,” Stein said. “And if not, if there are similar searches and reviews that have already been conducted by the agency, we can leverage those existing searches, which would result in a significant savings of staff hours and response time.”

Beyond internal operations, the State Department also sought to improve the customer experience for FOIA requesters by modernizing its public-facing website and search functionalities. Using AI-driven search algorithms and automated request processing, the department aims to “find and direct a customer to existing released documents” and “automate customer engagement early in the request process.”

Lessons learned

Since launching the first pilot in 2022, team members have learned several things. The first is to start small and provide the space and time to become familiar with the technology. “There are always demands and more work to be done, but to have the time to focus and learn is important,” Stein said.

Another lesson is the importance of collaboration. “It’s been helpful to talk across different communities to not only understand how this technology is beneficial but also what concerns are popping up—and discussing those sooner than later,” he said. “The sooner that anyone can start spending some time thinking about AI and machine learning critically, the better.”

Another lesson is to recognize the need to “continuously train a model because you can’t just do this once and then let it go. You have to constantly be reviewing how we’re training the model (in light of) world events and different things,” he said.

These pilots have also shown how this technology will allow State Department staff to better respond to other needs, including FOIA requests. For example, someone may ask for something in a certain way, but that’s not how it’s talked about internally.

“This technology allows us to say, ‘Well, they asked for this, but they may have also meant that,’” Stein said. “So, it allows us to make those connections, which may have been missing in the past.”

The State Department’s strategic adoption of AI and ML technologies in records management and transparency initiatives underscores the transformative potential of these tools. By starting small, fostering collaboration and prioritizing user-centric design, the department has paved the way for broader applications of AI and ML to support more efficient and transparent government operations.

The report was produced by Scoop News Group for FedScoop, as part of a series on innovation in government, underwritten by Microsoft Federal.  To learn more about AI for government from Microsoft, sign up here to receive news and updates on how advanced AI can empower your organization.

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“Of our workforce, there are a lot of people who haven’t been playing with ChatGPT,” State Chief Information Officer Kelly Fletcher said Thursday at AIScoop’s AITalks event in Washington, D.C. “We’re encouraging them to do so, but they need training.”

The internal chatbot, which FedScoop previously reported on, is an example of how the agency is weighing how generative AI might help with tasks like summarization and translation. It comes in response to staff demand. 

Beyond the chatbot, the State Department is using artificial intelligence for other purposes, including declassifying documents, said Matthew Graviss, the agency’s chief data and artificial intelligence officer. The department is also using open-source models to help create a digital research assistant for certain mandated reports, though he didn’t name those documents.  

The department is also using public tools with public information to help synthesize information for ambassadors, Graviss said. “You don’t need FedRAMP this and FISMA that to do that kind of stuff,” he added. “Public tools work.” 

Earlier this month, FedScoop reported that the Department of State had removed several references to artificial intelligence use cases in its executive order-required inventory. 

Other agencies, meanwhile, have taken a variety of approaches to generative AI, with some more cautious about exploring the technology. Others are setting up sandboxes to explore generative AI tools, working, for instance, with versions of OpenAI tools available on Azure for Government. 

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Amid growing concern that U.S. companies and technologies are getting outmuscled by China in standard-setting bodies, the Promoting United States Leadership in Standards Act of 2024 from Sens. Mark Warner, D-Va., and Marsha Blackburn, R-Tenn., calls on the National Institute of Standards and Technology and the State Department to bolster U.S. participation in the creation and implementation of standards for AI and other emerging tech. 

“In recent years, the Communist Party of China has asserted their dominance in the global technology space, and as their status has risen, our authority and influence has fallen,” Warner said in a statement. “This legislation clearly outlines steps we must take to reestablish our leadership and ensure that we are doing all we can to set the global standards for critical and emerging technologies.”

According to a press release, the legislation aims to preserve U.S.  influence when it comes to technical requirements as well as “values, such as openness, safety, and accessibility, embedded in emerging technologies.”

It’s the Chinese Communist Party’s “mission to undermine the U.S. and our interests around the globe by exploiting our deficiencies,” Blackburn said in a statement. “As they ramp up their efforts to dominate global standards for emerging technologies, the U.S. must be a global leader in innovation, and that includes setting standards that reflect our interests and values.”

The legislation mandates NIST to deliver two reports to Congress: one covering current U.S. participation in the development of standards for AI and other emerging technologies and another that assesses a pilot program that would award $10 million in grants over four years for the hosting of standards meetings in the U.S.

That second report, which would be due after the pilot program’s third year, would also detail expenses, identify the recipients of the grants, and highlight the geographic distribution of participants at the standards meetings. 

Finally, the bill calls on NIST’s director to launch a web portal that enables stakeholders to “navigate and actively engage in international standardization efforts,” in addition to featuring information on how to contribute to activities related to standards for AI and emerging technologies. 

“Nurturing open and global participation in standardization activities, especially when hosted in the United States, can address shared technical challenges while advancing American technology leadership,” Morgan Reed, President of ACT | The App Association, said in a statement. “This legislation represents a decisive step in the right direction.”

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With an annual spend of more than $100 billion on IT products, the federal government is falling short on the consistent tracking of its software licenses, leading to missed opportunities for cost reductions, the GAO found. And though there are federal initiatives in place to “better position agencies to maximize cost savings when purchasing software licenses,” the GAO noted that “selected agencies have not fully determined over- or under-purchasing of their five most widely used software licenses.”

The GAO’s study looked at software licenses purchased by the 24 Chief Financial Officers Act agencies, finding that 10 vendors made up the majority of the most widely used licenses. For fiscal year 2021, Microsoft held by far the largest share of vendors organized by the highest amounts paid (31.3%), followed by Adobe (10.43%) and Salesforce (8.7%).

While the GAO was able to identify and analyze vendors based on government spend, it was “unclear which products under those licenses are most widely used because of agencies’ inconsistent and incomplete data,” the report noted. “For example, multiple software products may be bundled into a single license with a vendor, and agencies may not have usage data for each product individually.”

“Without better data, agencies also don’t know whether they have the right number of licenses for their needs,” the report continued.

For their recommendations, the GAO focused on nine agencies based on the size of their IT budgets and then zeroed in on the five most widely used licenses within those agencies. The selected agencies were the Departments of Agriculture, Energy, Housing and Urban Development, Justice, State and Veterans Affairs, as well as the Office of Personnel Management, Social Security Administration and USAID.

The recommendations centered most on better and more consistent inventory tracking to ensure that agencies didn’t double-dip on software license purchases and were in a better position to take advantage of cost-saving opportunities. There should be more concerted efforts to compare prices, the GAO stated.

HUD did not say whether it agreed or disagreed with the GAO’s recommendations, while the other eight agencies said in responses that they did.

Congress in 2023 attempted to rein in duplicative software across the government with the Strengthening Agency Management and Oversight of Software Assets Act, which aimed to consolidate federal software purchasing and give agencies greater ability to push back on restrictive software licensing. However, after passing the House in July, the bill never moved in the Senate.

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The GAO said in a new report that while State has a cybersecurity risk management program in place, it is missing key elements of its cybersecurity risk management program, including mitigating departmentwide risks, conducting bureau-level risk assessments, completing authorization for all of its information systems, and implementing a departmentwide continuous monitoring program.

GAO said that the state of the department’s current cybersecurity program risks the ability to “detect, investigate and mitigate cybersecurity-related incidents.”

“Until the department implements required risk management activities, it lacks assurance that its security controls are operating as intended,” the report states. “Moreover, State is likely not fully aware of information security vulnerabilities and threats affecting mission operations.”

There are a number of issues at hand, GAO found, including a lack of fully implemented processes that support its incident response program and an IT infrastructure that isn’t “adequately secured” and needs to be modernized.

“This includes replacing the 23,689 hardware systems and 3,102 occurrences of network and server operating system software installations that have reached end-of-life. Certain installations of operating system software had reached end-of-life over 13 years ago,” the report states.

The report continues: “Without fully implemented incident response processes and an adequately secured IT infrastructure to support State’s incident response program by, among other things, updating outdated or unsupported products, State’s IT infrastructure is vulnerable to exploits.”

GAO offered 15 recommendations for the department and the secretary of state to address, including developing a plan to mitigate known vulnerabilities, ensuring all systems have a current authority to operate, and conducting risk assessments for the information systems that the watchdog reviewed, among other things.

The GAO also recommended that the department “direct the CIO to update an October 2020 matrix” so the program complies better with federal guidance and departmentwide policies. The department issued a statement previously on its cybersecurity program’s responsibility to identify and assess vulnerabilities and respond to threats. 

The department concurred with all recommendations.

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The suggestions were among those that seemed to generate interest at a Tuesday roundtable on Capitol Hill, including some legislative interest in fixing cloud procurement from Connolly, the ranking member of the House Committee on Oversight and Reform’s subcommittee focused on cybersecurity and IT. 

The roundtable discussion followed the release of the latest Federal IT Acquisition Reform Act (FITARA) scorecard, which measures agency progress in meeting that statute’s requirements and centered on how agencies are progressing with cybersecurity improvements in government. 

Those in attendance included IT and cyber officials from the departments of Commerce, Veterans Affairs and State, Social Security Administration, Government Accountability Office, and General Services Administration.

Among the challenges for the government procuring cloud services is an absence of the definition of “cloud” in the Federal Acquisition Regulation (FAR), Carol Harris, a director for GAO’s IT and cybersecurity team, noted at the meeting. Harris said the GAO is currently looking into the main challenges for cloud procurement.

“In addition, there’s not a type of contract available that covers a consumption-based pricing model, which is what you do when you procure cloud,” Harris said. “And so because of these outdated requirements in the FAR, these agencies are having to do these workarounds, and that’s a major problem.”

Harris suggested there’s an opportunity for congressional action. 

“I have to admit, I did not know, and neither did GAO until recently, that the FAR – the major procurement vehicle of the federal government — has no definition of cloud,” Connolly told FedScoop after the meeting. 

He added: “We’re going to fix that.”

Harris also noted that there are challenges for agencies in how to effectively hire employees with cloud expertise, and agencies are awaiting requirements and deadlines from the Office of Management and Budget on the application rationalization component of the government’s cloud computing strategy “Cloud Smart.” 

Another suggestion on the performance metrics themselves came from Kelly Fletcher, chief information officer for the State Department, who pointed to the volume of cybersecurity scores agencies are given, including FITARA and Performance.gov metrics.

“In no way to impugn any of the scores, I think they’re all really valuable, but the problem is when I try to explain to my leadership ‘how are we doing on cybersecurity,’ frankly, I can pick and choose,” Fletcher said. 

She added: “I think some consistency across these public metrics would be very helpful.”

Connolly, in response, noted that FITARA is tied to the elements in the statute it stems from, but said he wasn’t sure if lawmakers were aware there were competing scores when they created the scorecard. “I think it’s good feedback for us to try to at least stay cognizant of those other measurements,” Connolly said.

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The State Department’s 191 embassies around the world often find themselves in the crossfire of a crisis within their host nations. Those emergencies come with many high-risk moving pieces that require constant connectivity to communicate with officials back in the U.S., and the embassies can’t always rely on the local networks of the regions they’re based in, Fletcher said during FedScoop’s FedTalks on Thursday. 

“So my first experience with an emergency was Sudan. I was in D.C., but we had an IT presence in Sudan. And every day I’d wake up and make sure they could still communicate: is your phone working, are the cell towers out, is the internet working in places where the government will turn off the internet?” said Fletcher. 

“But I think in the future what I’m really excited about is affordable, resilient, reliable SATCOM that I can use in emergencies,” she said.

SATCOM also has advantages for embassies in less developed parts of the world that lack connectivity and network infrastructure for State Department communications, Fletcher said.

“But also SATCOM that maybe for smaller embassies can be used as part of daily business. I think it’s going to fundamentally change how we engage with each other and how we think about getting data where it needs to go,” she added.

Satellite communications have seen an explosion of activity in the past year during the Ukraine war, notably with services like Elon Musk’s Starlink platform.

Fletcher highlighted an example of “how cool it is that we can use SATCOM even on some iPhones today” using the SOS button, but she also pointed out the challenge that most government phones are severely outdated and would need to be upgraded before having SATCOM capabilities built in. 

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Within government, there are existing projects that are more mature than AI chatbots and are immediately ready to deliver more efficient government operations. Through a partnership between three offices, the Department of State is seeking to automate the cumbersome process of document declassification and prepare for the large volume of electronic records that will need to be reviewed in the next several years. The Bureau of Administration’s Office of Global Information Services (A/GIS), the Office of Management Strategy and Solutions’ Center for Analytics (M/SS CfA), and the Bureau of Information Resource Management’s (IRM) Messaging Systems Office have piloted and are now moving toward production-scale deployment of AI to augment an intensive, manual review process that normally necessitates a page-by-page human review of 25-year-old classified electronic records. The pilot focused mainly on cable messages which are communications between Washington and the department’s overseas posts. 

The 25-year declassification review process entails a manual review of electronic, classified records at the confidential and secret levels in the year that their protection period elapses; in many cases, 25 years after original classification. Manual review has historically been the only way to determine if information can be declassified for eventual public release, or exempt from declassification to protect information critical to our nation’s security.

However, manual review is a time-intensive process. A team of about six reviewers works year-round to review classified cables and must use a triage method to prioritize reviewing the cables most likely to require exemption from automatic declassification. In most years, they are unable to review every one of the between 112,000 and 133,000 electronic cables under review from 1995-1997. The risk of not being able to review each document for any sensitive material is exacerbated by the increasing volume of documents. 

This manual review strategy is quickly becoming unsustainable. Around 100,000 classified cables were created each year between 1995 and 2003. The number of cables created in 2006 that will require review grew to over 650,000 and remains at that volume for the following years. While emails are currently an insignificant portion of 25-year declassification reviews, the number of classified emails doubles every two years after 2001, rising to over 12 million emails in 2018. To get ahead of this challenge, we have turned to artificial intelligence. 

Considering AI is still a cutting-edge innovation with uncertainty and risk, our approach started with a pilot to test the impact of the process on a small scale. We trained a model, using human declassification decisions made in 2020 and 2021 on cables classified confidential and secret in 1995 and 1996, to recreate those decisions on cables classified in 1997. Over 300,000 classified cables were used for training and testing during the pilot. The pilot took three months and five dedicated data scientists to develop and train a model that matches previous human declassification review decisions at a rate of over 97 percent and with the potential to reduce over 65 percent of the existing manual workload. The pilot approach allowed us to consider and plan for three AI risks: lack of human oversight of automated decision-making, the ethics of AI, and overinvestment of time and money on products that aren’t usable.

The new declassification tool will not replace jobs. The AI-assisted declassification review process requires human reviewers to remain part of the decision-making process. During the pilot and the subsequent weeks of work to put the model into production, reviewers were consistently consulted and their feedback integrated into the automated decision process. This combination of technological review with human review and insight is critical to the success of the model. The model cannot make a decision with confidence on every cable, necessitating that human reviewers make a decision as they normally would on a portion of all cables. Reviewers also conduct quality control. A small, yet significant, percentage of cables with automated confident decisions are given to reviewers for confirmation. If enough of the AI-generated decisions are contradicted during the quality control check, the model can be re-trained to consider the information that it missed and integrate reviewer feedback. This feedback is critical to sustaining the model in the long term and for considering evolving geopolitical contexts. During the pilot, we determined that additional input from the Department’s Office of the Historian (FSI/OH) could help strengthen future declassification review models by providing input about world events during the years of records being reviewed.

There are ethical concerns that innovating with AI will lead to governing by algorithm. Although the descriptive AI used in our pilot does not construct narrative conversations like large language models (LLMs) and ChatGPT, it is designed to make decisions by learning previous human inputs. The approximation of human thought raises concerns of ethical government when it replaces what is considered sensitive and specialized experience. In our implementation, AI is a tool that works in concert with humans for validation, oversight, and process refinement. Incorporating AI tools into our workflows requires continually addressing the ethical dimensions of automated decision-making. 

This project also saves money — potentially millions of dollars’ worth of personnel hours. Innovation for the sake of being innovative can result in overinvestment in dedicated staff and technology, which is unable to sustain itself or end up in long-term cost savings. Because we tested our short-term pilot within the confines of existing technology, when we forecast the workload reduction across the next ten years of reviews, we anticipate an almost $8 million savings on labor costs. Those savings can be applied to piloting AI solutions for other governmental programs managing increased volumes of data and records with finite resources, such as information access requests for electronic records and Freedom of Information Act requests.

Rarely in government do we prioritize the time to try, and potentially fail, in the interest of innovation and efficiency. The small-scale declassification pilot allowed for a proof of concept before committing to sweeping changes. In our next phase, the Department is bringing the pilot to scale so that the AI technology is integrated with existing Department technology as part of the routine declassification process.

Federal interest in AI use cases has exploded in only the last few months, with many big and bold ideas being debated. While positive, these debates should not detract from use cases like this, which can rapidly improve government efficiency and transparency through the release of information to the public. Furthermore, the lessons learned from this use case – having clear metrics of success upfront, investing in data quality and structure, starting with a small-scale pilot — can also be applied to future generative AI use cases as well. AI’s general-purpose capabilities mean that it will eventually be a part of almost all aspects of how the government operates, from budget and HR to strategy and policy making. We have an opportunity to help shape how the government modernizes its programs and services within and across federal agencies to improve services for the public in ways previously unimagined or possible.  

Matthew Graviss is chief data and AI officer at the Department of State, and director of the agency’s Center for Analytics. Eric Stein is the deputy assistant secretary for the office of Global Information Services at State’s Bureau of Administration. Samuel Stehle is a data scientist within the Center for Analytics.

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