Recent assessments from the U.S.-China Economic and Security Review Commission’s 2025 annual report underscore the challenge ahead. According to the report, “China is aggressively positioning itself as a global leader in space technology and exploration, seeking to reshape international governance, influence standards, and displace the United States as the world’s premier space power.”

The report notes China’s operational satellite fleet exceeded 1,060 by mid-2025, with hundreds dedicated to intelligence, surveillance and reconnaissance.

Chief of Space Operations Gen. B. Chance Saltzman has signaled U.S. resolve on this front. During the opening keynote at the Air & Space Forces Association’s Warfare Symposium in March 2025, he made U.S. intentions clear to allies and adversaries alike, declaring, “The Space Force will do whatever it takes to achieve space superiority.”

The April 2025 release of “Space Warfighting: A Framework for Planners” codifies the service’s shift from primarily supportive roles to treating space as a contested warfighting domain, openly emphasizing offensive and defensive counter-space operations alongside traditional enabling capabilities.

In the document’s foreword, Saltzman writes that space superiority “unlocks superiority in other domains, fuels Coalition lethality, and fortifies troop survivability. It is therefore the basis from which the Joint Force projects power, deters aggression, and secures the homeland.”

‘Race to resilience’

Current core U.S. military space capabilities remain foundational but increasingly vulnerable.

Missile warning and tracking systems, such as the Space-Based Infrared System and emerging Next-Generation Overhead Persistent Infrared satellites, provide global detection of ballistic and hypersonic launches, often within seconds of ignition. This capability is supplemented by proliferated low-Earth orbit sensors, including the Space Development Agency’s Tranche 3 tracking layer, a $3.5 billion investment awarded in late 2025 for 72 new satellites planned for launch beginning in 2029.

Protected satellite communication and positioning, navigation and timing networks, including the jam-resistant Advanced Extremely High Frequency constellation and military GPS featuring enhanced anti-jam M-code, ensure resilient command and control in degraded environments.

Space domain awareness tools, such as the maneuverable Geosynchronous Space Situational Awareness Program satellites, operate in near-geosynchronous orbit to conduct close inspections of objects. Upgraded ground-based sensors, including the Ground-Based Optical Sensor System, track orbital objects and potential threats.

While robust, these systems are vulnerable to attacks such as signal jamming, sensor dazzling by directed-energy weapons and cyberattacks — reversible threats that U.S. officials report occur daily or near-daily. U.S. officials note that even temporary disruptions could significantly impair critical joint operations in wartime.

These challenges are driving the service’s “Race to Resilience” initiative, which aims to achieve battle-ready architectures by 2026. Several key milestones in the coming year will advance the Space Force’s readiness in these contested environments.

Boost-phase space-based interceptor prototypes, a proposed weapon system designed to destroy enemy ballistic missiles during the boost phase of their flight, were awarded under competitive contracts for the Golden Dome missile defense initiative in November 2025. Kinetic midcourse awards (hit-to-kill interceptors during the missile’s coasting phase) are expected in February 2026.

Speaking shortly after his appointment at the Space Foundation’s Innovate Space: Global Economic Summit in July 2025, program lead Gen. Michael Guetlein shared his optimism for the program, stating, “I firmly believe that the technology we need to deliver Golden Dome exists today,” highlighting the importance of integrated command and control.

The service will also finalize requirements for the Space Warfighter Operational Readiness Domain, a distributed digital training environment that builds on existing Space Flag exercises, enabling guardians across multiple locations to participate in virtual simulations of contested operations.

Four on-orbit servicing demonstrations are planned for 2026 to test satellite refueling, repair, inspection and maneuvering. These capabilities are essential for maintaining dynamic space operations, extending the lifespan of assets and enhancing resilience in these contested environments. These missions, funded by various DOD entities and commercial partners, mark a key step toward proving the viability of in-space logistics.

Additionally, the Commercial Augmentation Space Reserve will transition from pilot phase to full-scale operations in 2026, targeting 20 contracts by year-end to provide wartime access to commercial satcom networks. This resiliency measure is backed by record fiscal 2026 funding approaching $40 billion, reflecting priorities for hybrid military-commercial architectures.

With threats intensifying, including China’s rapid satellite expansion and Russia’s disruptive capabilities, 2026 positions the Space Force to deliver resilient architectures that ensure U.S. space superiority, enabling joint forces to maintain the edge in any conflict or contested environment.

As these advanced systems begin to permeate various industry sectors, including U.S. government agencies, they necessitate a reevaluation of conventional security and auditing frameworks. The term “production ready” will need to be redefined, considering the unique requirements for scalability, interoperability, robustness, resource management, and coordination inherent in these systems. Additionally, addressing ethical and legal considerations, standardizing protocols, ensuring usability and maintainability, and establishing robust performance metrics are essential for successful deployments.

MAS offers the U.S. government enhanced capability in multiple areas, including:

Policy Analysis and Simulation: MAS can simulate complex socio-economic systems to analyze policy impacts. For instance, it can simulate the behavior of citizens, businesses, and governmental organizations to understand the effects of different policies or regulations.

Security and Defense: In defense and security applications, MAS can be utilized for tasks like surveillance, reconnaissance, and threat detection. Agents can work together to gather intelligence, analyze data, and respond to emerging threats in real-time.

Policy Enforcement: MAS can assist in enforcing regulations and policies by monitoring compliance and detecting violations. For example, in tax enforcement, agents can analyze financial data to identify potential cases of tax evasion.

Knowledge Transfer: As employees leave or retire from agencies/companies, their body of knowledge is often lost. With MAS, we can implement a “knowledge gathering agent” who along with a “knowledge deficit agent” can work together to identify knowledge deficits (think of code coverage deficits in software development) and interact with the subject matter experts to capture knowledge through interactive chat sessions.

Smart Infrastructure Management: MAS can be employed to manage and optimize various aspects of infrastructure, such as transportation systems, energy grids, and water distribution networks. Agents representing different components of the infrastructure can collaborate to improve efficiency, reduce costs, and enhance resilience.

Potential pitfalls

In the evolving landscape of system architectures, where traditional setups featuring web applications, REST or GraphQL APIs, gateways, and data meshes starkly contrast with the decentralized, message-driven communication models of MAS, a critical challenge emerges – ensuring robust security within these decentralized networks. This challenge necessitates security measures that not only integrate smoothly with existing security frameworks but also adapt to the unique dynamics of MAS.

Addressing the security conundrum in MAS, especially as they begin to play a significant role in the infrastructure of the U.S. government, demands innovative solutions. Our research and development initiatives are deeply engaged in tackling this and other related challenges, aiming for a seamless adoption of MAS.

A promising move in the right direction is the deployment of specialized agents within the MAS architecture, tasked with the critical role of safeguarding data integrity and access. Such specialized agents epitomize the adaptation of traditional security measures to fit the decentralized, message-driven nature of MAS, ensuring that security does not become an afterthought but a seamlessly integrated component of the system’s architecture.

This specialized security agent example exemplifies the potential of multi-agent systems to not only mimic but also enhance the capabilities of human counterparts in critical areas such as cybersecurity. By maintaining a focus on continuous learning and adaptation (like the professional development of human employees), such agents can offer invaluable assistance in generating secure code and configurations.

Another specific concern is poisoning attacks, which involve introducing malicious data to disrupt agents’ learning and decision-making processes. Effective mitigation strategies include data validation, robust learning algorithms, redundancy, continuous monitoring, secure communication channels, strong authentication, adaptive defense mechanisms, and collaboration with cybersecurity experts. While these challenges are significant, the concerted efforts of researchers and developers in the field ensure that solutions will be found, paving the way for the widespread adoption of MAS and generative AI in the future.

As we continue to explore the frontiers of generative AI and MAS, the journey towards integrating MAS into our technological infrastructure is both challenging and exciting. We believe MAS is the only viable approach to bringing generative AI into the U.S. government in a managed manner due to its ability to leverage existing tools, enable robotic process automation, and ensure comprehensive auditing and tracking

MAS offers a flexible and adaptable approach to modeling and solving complex problems in the federal government, enabling efficient collaboration, decision-making, and resource management across different agencies and domains.

John Mark Suhy is CTO of Greystones Group. He more than 20 years of enterprise architecture and software development experience with agencies including FBI, Sandia Labs, Department of State, U.S. Treasury and the Intel community.

Well known examples include the Human Genome Project, space exploration, Silicon Valley, and biomedical research. Further, in the ever-evolving landscape of science and innovation, the U.S. stands as a beacon for global talent, attracting brilliant minds to its research institutions and universities. This influx of international scientists and engineers has undeniably enriched the nation’s scientific endeavors, leading to countless breakthrough discoveries, transformative innovations, and advancements.

However, amidst the celebration of diversity and collaboration lies a growing concern – the need to balance the openness of the U.S. research enterprise and maintain the nation’s competitive edge on the global stage with the imperative to safeguard national security interests.

Revelations and discussions from this year, as articulated in a GAO Report on Research Security released in January 2024; in remarks made by the Director of National Intelligence, Avril Haines, in her March 2024 testimony before the Senate Select Committee on Intelligence; and in widely reported revelations by the FBI, have highlighted the potential risks associated with foreign researchers working on sensitive projects.

Now, especially as we approach the election, the conversation has turned to how best to protect intellectual property and prevent the unwanted compromise and nefarious exploitation of critical technology by foreign adversaries and other bad actors, including terrorist groups and those that mean to do harm to our national well being. While this is not an easy tension to navigate, it is one we can indeed manage consistent with our national values as we continue to forge ahead with advanced scientific research and technology development to the benefit of all people, everywhere.

At the heart of the matter lies the challenge of finding a solution that does not stifle the flow of talent while ensuring that the nation’s interests are protected. This delicate balance requires a departure from conventional approaches to risk assessment, which often rely on simplistic country-based criteria or blanket restrictions that paint various foreign researchers with the same brush of suspicion.

Instead, what is needed is a nuanced and agile approach – one that leverages technology to identify and mitigate potential risks swiftly and effectively and supplements the work that teams focused on innovation and national security are already doing. Enter the concept of a triage tool – a sophisticated mechanism that incorporates AI capabilities designed to assess the risk posed by international scientists and engineers while expediting the entry of low-risk individuals into the U.S. research ecosystem.

The ideal triage tool, tied to policy that favors the fast tracking of the many scientists who will provide valuable contributions without jeopardizing national security, would possess several key attributes: it must operate without bias, respecting the diversity of backgrounds and nationalities among applicants; it should be automated, ensuring swift processing and scalability without compromising accuracy; and it must prioritize privacy, abstaining from intrusive data collection methods such as biometrics or personally identifiable information.

Furthermore, the tool should complement existing vetting processes, seamlessly integrating into the fabric of U.S. research institutions and agencies. It should be cost-effective, offering significant savings in both time and resources while delivering reliable results with minimal false positives or negatives.

By implementing such a tool, the U.S. can achieve a delicate balance between fostering international collaboration and protecting its national security interests and by establishing robust mechanisms for protecting sensitive information, the U.S. can bolster trust and encourage fruitful collaboration between domestic and international partners. This would not only enhance the experience of foreign researchers seeking opportunities in the U.S. but also provide reassurance to domestic institutions and agencies tasked with safeguarding sensitive information.

The U.S. stands at a crossroads, where the nurturing of global talent is not merely an option but a strategic imperative. Embracing international scientists and engineers is not only a testament to our commitment to excellence but also a catalyst for driving forward the frontiers of human knowledge and ingenuity. In the end, it is not about erecting barriers or shutting the door to international talent – it is about striking a harmonious chord between openness and vigilance, rather than a forced tradeoff between the two.

By embracing innovation in risk assessment and vetting processes, and thereby welcoming the contributions of international talent, the U.S. can continue to lead the world in scientific discovery, address the existing skill gaps, foster global collaboration and culture exchanges, while safeguarding its technological edge for generations to come and fortifying the country’s position as a leader in innovation.

Donald (Don) J. Blersch is Clearspeed’s SVP of Government Innovation. With multi-agency experience, including NASA, the National Oceanic and Atmospheric Administration (NOAA), Central Intelligence Agency (CIA), the Office of the Director of National Intelligence (ODNI), the National Reconnaissance Office (NRO), the Missile Defense Agency (MDA), and the U.S. Department of State’s Bureau of Diplomatic Security, Blersch led the implementation of technology innovation while advising the executive leadership bench on a wide range of security disciplines, enabling the department to meet vital national security responsibilities with a well-vetted and trusted workforce, hyperfocused on the protection of sensitive, classified information.

Researchers asked a group of students, none of whom had specialized training in the life sciences, to use AI tools, such as OpenAI’s ChatGPT-4, to develop a plan for how to start a pandemic. In just an hour, participants learned how to procure and synthesize deadly pathogens like smallpox in ways that evade existing biosecurity systems.

AI cannot yet manufacture a national security crisis. As Jason Matheny at Rand reiterates, while biological know-how is becoming more widely accessible through AI, it’s not currently at a level that would substitute for a lack of biological research training. But as biotechnology becomes both more advanced — think of Google DeepMind’s AlphaFold, which uses AI to predict how molecular structures will interact — policymakers are understandably worried that it’ll be increasingly easy to create a bioweapon. So they’re starting to take action to regulate the emerging AI industry.

Their efforts are well-intentioned. But it’s critical that policymakers avoid focusing too narrowly on catastrophic risk and inadvertently hamstring the creation of positive AI tools that we need to tackle future crises. We should aim to strike a balance.

AI tools have enormous positive potential. For instance, AI technologies like AlphaFold and RFdiffusion have already made large strides in designing novel proteins that could be used for medical purposes. The same sort of technologies can also be used for evil, of course.

In a study published last year in the journal Nature Machine Intelligence, researchers demonstrated how the AI MegaSyn could generate 40,000 potential bioweapon chemicals in just six hours. Researchers asked the AI to identify molecules that are similar to VX, a highly lethal nerve agent. In some cases, MegaSyn devised compounds that were even more toxic.

It’s possible that bad actors could one day use such tools to engineer new pathogens far more contagious and deadly than any occurring in nature. Once a potential bioweapon is identified — maybe with the help of AI — a malicious actor could order a custom strand of DNA from a commercial provider, who would manufacture synthetic DNA in a lab and return it via mail. As experts at the Center for Security and Emerging Technology at Georgetown University has posited, perhaps that strand of genetic material “codes for a toxin or a gene that makes a pathogen more dangerous.

It’s even possible that a terrorist could evade detection by ordering small pieces of a dangerous genetic sequence, and then assemble a bioweapon from the component parts. Scientists frequently order synthesized DNA for projects like cancer and infectious disease research. But not all synthetic DNA providers screen orders or verify their customers.

Closing such loopholes will help, but we can’t regulate away all of the risk. It’d be wiser to beef up our defenses by investing in AI-enabled early-detection systems.

Today, the Centers for Disease Control and Prevention’s Traveler-based Genomic Surveillance program partners with airports nationwide to gather and analyze wastewater and nasal swab samples to catch pathogens as they enter our borders. Other systems are in place for tracking particular pathogens within cities and communities. But existing detection systems are likely not equipped for novel agents designed with AI’s help.

The U.S. intelligence community is already investing in AI-powered capabilities to defend against next-generation threats. IARPA’s FELIX program, in partnership with private biotech firms, yielded first-in-class AI that can distinguish genetically engineered threats from naturally-occurring ones, and identify what has been changed and how.,A similar technology could be used for DNA synthesis screening — with AI, we could employ algorithms that predict how novel combinations of genetic sequences might function.

We have barely begun to tap the potential of AI to detect and protect against biological threats. In the case of a novel infectious disease, these systems have the power to determine how and when a pathogen has mutated. That can enable the speedy development of vaccines and treatments specifically tailored to new variants. AI can also help predict how a pathogen is likely to spread.For these technologies to play their vital role, leaders in Washington and around the world must take steps to build up our AI defenses. The best way to counter “bad AI” isn’t “no AI” — it’s “good AI.”

Using AI to its full potential to protect against deadly pandemics and biological warfare demands an aggressive policy effort. It’s time for policymakers to adapt. With adequate foresight and resources, we can get ahead of this new class of threats.

Andrew Makridis is the former Chief Operating Officer of the CIA, the number-three position at the agency. Prior to his retirement from the CIA in 2022, he spent nearly four decades working in national security.

Jennifer Swanson, deputy assistant secretary of the Army for data, engineering and software, said the effort will shed light on how the service’s acquisition and logistics enterprise could take advantage of generative AI tools to make processes like contract writing and data analysis more efficient.

“The pilot’s not just about increasing our productivity, which will be great, but also — what are the other things that we can do and what are the other industry tools that are out there that we might be able to leverage or add on,” Swanson said June 18 at Defense One’s Tech Summit in Arlington, Va.

The Army is the latest Defense Department agency to announce efforts to experiment with generative AI. The Air Force and Space Force last week unveiled their own experimental tool — the Non-classified Internet Protocol Generative Pre-Training Transformer, or NIPRGPT. And in 2023, the Navy rolled out a conversational AI program called Amelia that sailors could use to troubleshoot problems or provide tech support.

Swanson said she’s optimistic about the potential for generative AI, especially for laborious specialties like contract writing and policy where automation could release some strain on the Army’s workforce.

“In the area of contracts and in the area of policy, I think there’s a huge return on investment for us,” she said. “Might [AI] one day be able to write a contract? We hope so. But we’ve got to pilot and test it and make sure everybody’s comfortable with it first.”

The large language model the service will use for the effort is different from systems like ChatGPT, Swanson said, because it is trained on Army data. It will also provide citations that indicate where the data it provides originated, a feature that will help the service fact-check that information.

The pilot is part of a broader effort within the Army to identify both the pitfalls and the opportunities that come with widely adopting AI tools. In March, the service announced a 100-day plan focused on reducing the risk associated with integrating AI algorithms.

As part of that exercise, Swanson said, the Army reviewed its spending on AI research and found that testing and security are the two biggest gaps toward fielding these tools more broadly. The service also identified 32 risks and 66 mitigations it can implement to reduce their impact. Further, it created a generative AI policy that it will apply to the pilot in order to set parameters for the effort. That policy includes a requirement that there be a “human in the loop.”

The generative AI pilot will lead into the next phase of the effort — a 16-month focus on how to use the technology operationally. Findings from that work will inform the Army’s budget for fiscal 2026.

“So the 100 day plan is setting the conditions — where are we at — and then the 500 day plan is really about operationalizing it,” she said.

Florent Groberg, vice president of strategy and optimization at private investment firm AE Industrial partners, said that as the Army moves through these review processes and experiments with AI, it should be transparent with industry about what it wants and then move quickly to leverage the tools companies are developing.

“To me, it’s really understanding the framework of what you want to accomplish,” he said during the same panel with Swanson. “Put some boundaries out there and then go do it.”

These weaknesses often arise due to the complexity of maintaining and updating legacy systems which often lack basic security controls, as well as the challenges of ensuring comprehensive security measures across expansive and interconnected IT enterprises. As artificial intelligence continues to advance, its use in the federal space is becoming more prevalent, leading agencies to increase their use of the technology as part of their cyber defenses.

However, recent research reveals that although 80 percent of cybersecurity decision-makers believe accelerating AI adoption is vital for their organization’s resilience against emerging threats, only 31 percent report that their organization currently utilizes AI for cybersecurity. Notably, 54 percent of leaders who have implemented AI say that it has helped to accelerate incident response times, highlighting AI’s potential as a powerful defensive tool.

AI serves as both a formidable defense mechanism for protecting sensitive data and a potent tool for cyber attackers. AI’s ability to continuously learn and improve from each interaction makes it an invaluable asset in defending against evolving threats. However, malicious actors also exploit AI to develop sophisticated cyberattacks, targeting vulnerabilities and bypassing traditional defenses with alarming precision.

Maximizing AI’s defensive capabilities With ZTS

To combat evolving threats and address vulnerabilities, AI and Zero Trust Segmentation offer a path forward. AI rapidly automates tasks, detects threats, and provides predictive analytics – analyzing vast amounts data in real-time to identify and mitigate anomalies quickly. ZTS complements AI by ensuring continuous verification of every access request within an enterprise, segmenting the applications with strict access controls and monitoring, thus limiting lateral movement by attackers and containing breaches.

AI’s defensive capabilities can be maximized when integrated with ZTS. Since ZTS involves continuously verifying and monitoring all user and device activities within a enterprise, no entity is trusted by default, even if it is already inside the enterprise. The integration of AI and ZTS means that even if an attacker manages to infiltrate the enterprise, their ability to move laterally and escalate privileges is severely limited.

While ZTS alone provides robust defenses by restricting access and enforcing strict verification protocols, the addition of AI enhances these capabilities by automating threat detection and response, identifying potential breaches in real time, and adapting to new attack vectors dynamically. Auto-labeling, for example, enhances AI’s effectiveness by streamlining data classification, reducing manual intervention, and allowing faster, more accurate anomaly detection. This leads to improved operational efficiency and heightened security as AI systems better recognize patterns, predict issues, and implement safeguards in real-time.

Together, AI and ZTS form a proactive, comprehensive defense strategy for critical infrastructure organizations, enhancing resilience against sophisticated cyber adversaries and helping organizations to stay one step ahead of attackers.

Pushing for responsible AI in critical infrastructure

Deploying AI across critical infrastructure organizations demands a strong commitment to ethics, focusing on transparency, fairness, and accountability. Transparency ensures AI systems are understandable and trustworthy. Fairness aims to prevent biases so that no one group is disadvantaged. Accountability requires organizations to take responsibility for AI outcomes, with protocols to address errors and mechanisms for stakeholders to raise concerns.

To deploy AI responsibly across critical infrastructures, organizations should adhere to several best practices. The Department of Homeland Security has ramped up its focus on AI with its new Artificial Intelligence Safety and Security Board, which offers recommendations for safely preventing and preparing for AI-related disruptions to critical services; addressing AI risk and threats; trainings, deployments, and usage of AI; responsibly leveraging AI while protecting individuals’ privacy, civil rights, and civil liberties. Proactive approaches like these are essential to stay ahead of adversaries exploiting AI for malicious purposes.

To effectively harness AI’s defensive capabilities and protect critical infrastructure, responsibly integrating AI with ZTS is essential. This integration creates a dynamic defense mechanism that is difficult for attackers to bypass. AI’s continuous monitoring and real-time threat analysis enhance the ability to swiftly identify and respond to threats, forming a robust cybersecurity posture.

Combining AI’s real-time data processing and predictive analytics with ZTS’ stringent access controls significantly boosts resilience against evolving cyber threats. This approach addresses current vulnerabilities and anticipates future challenges, ensuring the security of critical infrastructure in a complex threat landscape.

Gary Barlet is federal chief technology officer at Illumio.

A senior Justice Department official raised the concerns in a court filing on Friday that sought to justify keeping the recording under wraps. The Biden administration is seeking to convince a judge to prevent the release of the recording of the president’s interview, which focused on his handling of classified documents.

The admission highlights the impact the AI-manipulated disinformation could have on voting and the limits of the federal government’s ability to combat it.

A conservative group that’s suing to force the release of the recording called the argument a “red herring.”

Mike Howell of the Heritage Foundation accused the Justice Department of trying to protect Biden from potential embarrassment. A transcript of the interview showed the president struggling to recall certain dates and confusing details but showing a deep recall of information at other times.

“They don’t want to release this audio at all,” said Howell, executive director of the group’s oversight project. “They are doing the kitchen sink approach and they are absolutely freaked out they don’t have any good legal argument to stand on.”

The Justice Department declined to comment Monday beyond its filing.

Biden asserted executive privilege last month to prevent the release of the recording of his two-day interview in October with special counsel Robert Hur. The Justice Department has argued witnesses might be less likely to cooperate if they know their interviews might become public. It has also said that Republican efforts to force the audio’s release could make it harder to protect sensitive law enforcement files.

Republican lawmakers are expected to press Attorney General Merrick Garland at a hearing on Tuesday about the department’s efforts to withhold the recording. According to prepared remarks, Garland will tell lawmakers on the House Judiciary Committee that he will “not be intimidated” by Republican efforts to hold him in contempt for blocking their access to the recording.

Sen. Mark Warner, the Democratic chair of the Senate Intelligence Committee, told The Associated Press that he was concerned that the audio might be manipulated by bad actors using AI. Nevertheless, the senator said, it should be made public.

“You’ve got to release the audio,” Warner said, though it would need some “watermarking components, so that if it was altered” journalists and others “could cry foul.”

In a lengthy report, Hur concluded no criminal charges were warranted in his handling of classified documents. His report described the 81-year-old Democrat’s memory as “hazy,” “poor” and having “significant limitations.” It noted that Biden could not recall such milestones as when his son Beau died or when he served as vice president.

Biden’s aides have long been defensive about the president’s age, a trait that has drawn relentless attacks from Donald Trump, the presumptive GOP nominee, and other Republicans. Trump is 77.

The Justice Department’s concerns about deepfakes came in a court papers filed in response to legal action brought under the Freedom of Information Act by a coalition of media outlets and other groups, including the Heritage Foundation and the Citizens for Responsibility and Ethics in Washington.

An attorney for the media coalition, which includes The Associated Press, said Monday that the public has the right to hear the recording and weigh whether the special counsel “accurately described” Biden’s interview.

“The government stands the Freedom of Information Act on its head by telling the Court that the public can’t be trusted with that information,” the attorney, Chuck Tobin, wrote in an email.

Bradley Weinsheimer, an associate deputy attorney general for the Justice Department, acknowledged “malicious actors” could easily utilize unrelated audio recordings of Hur and Biden to create a fake version of the interview.

However, he argued, releasing the actual audio would make it harder for the public to distinguish deepfakes from the real one.

“If the audio recording is released, the public would know the audio recording is available and malicious actors could create an audio deepfake in which a fake voice of President Biden can be programed to say anything that the creator of the deepfake wishes,” Weinsheimer wrote.

Experts in identifying AI-manipulated content said the Justice Department had legitimate concerns in seeking to limit AI’s dangers, but its arguments could have far-reaching consequences.

“If we were to go with this strategy, then it is going to be hard to release any type of content out there, even if it is original,” said Alon Yamin, co-founder of Copyleaks, an AI-content detection service that primarily focuses on text and code.

Nikhel Sus, deputy chief counsel at Citizens for Responsibility and Ethics in Washington, said he has never seen the government raise concerns about AI in litigation over access to government records. He said he suspected such arguments could become more common.

“Knowing how the Department of Justice works, this brief has to get reviewed by several levels of attorneys,” Sus said. “The fact that they put this in a brief signifies that the Department stands behind it as a legal argument, so we can anticipate that we will see the same argument in future cases.”

As baby boomers near retirement, Gen Xers solidify leadership roles, millennials take on supervisory positions, and some of Gen Z enters the workforce for the first time, this diverse mix of generations presents a unique set of challenges when it comes to technology adoption within federal agencies.

Coupling Innovation with Security

Given the nature of their position, U.S. government agencies, face an inherent struggle to balance adopting new technology while following strict regulations and security measures. Just earlier this year, the Biden Administration announced new requirements for how federal agencies use AI technology.

Under these mandates, agencies must publish a complete list of the AI systems they use and their reasons for using them, along with a risk assessment of those systems.

The need to scrutinize data privacy and cybersecurity for emerging tools like cloud computing and AI can create a bureaucratic bottleneck, hindering agencies’ ability to quickly adopt these innovations.

How do agencies balance a workforce of digital natives and digital newcomers?

Further complicating this balancing act, generational differences can lead to inefficiencies. While younger workers like millennials and Gen Zers are excited to use advanced technology in the workplace, having already implemented it into other facets of their everyday lives, other generations such as baby boomers may have limited experience with newer technologies. This disparity can lead to disorganization and hinder collaboration if not adequately addressed.

The federal government needs to prioritize training and professional development programs to equip its workforce with the necessary technological skills. One way to do this is to implement continuous training programs.

For digital newcomers or people raised before the digital age, this means offering basic to advanced tech training where they can get up to speed with the latest tools. For digital natives, agencies can provide training focused on leadership and soft skills to complement their technical expertise.

Equipping a diverse workforce with the right skills fosters collaboration, especially when using cloud-based tools for geographically dispersed teams.

Collaboration in a Dispersed Workforce

The need for such continuous training programs becomes even more pressing when considering that more than half of Americans (52%) believe that new technologies are more likely to drive people apart than bring them together. With the rise of telework and remote work arrangements, technology plays a critical role in fostering collaboration within a geographically dispersed workforce. Cloud-based platforms, video conferencing tools, and collaborative software can bridge the physical distance and ensure teams can work together seamlessly regardless of location.

While tools may bridge the physical gap, fostering a culture of knowledge sharing can take teams a step further to connect multiple generations. This can be achieved through mentorship programs where workers unaccustomed to using new technology are paired with those well-versed in tech use, to facilitate mutual learning.

Work veterans can share their organizational knowledge and experience while digital natives can provide insight into new technologies. Knowledge exchange platforms are also vital tools as platforms like forums and internal networks can help employees share tips, tutorials and best practices for tech use.

In conclusion, navigating the intersection of technology and a multigenerational workforce is no easy feat for federal agencies. Their approach must include investing in secure, regulation-compliant technologies, implementing comprehensive training and development programs, fostering a culture of continuous learning, and leveraging technology to enhance collaboration and communication, regardless of location.

However, by addressing the challenges and opportunities presented by this dynamic, agencies can leverage technology to create a more efficient, skilled, and collaborative workforce prepared for the digital age.

Robert Edelman is the senior vice president for strategy and innovation at Sedgwick Government Solutions.

Semiconductors are the backbone of nearly all electronics and their complexity requires the use of third-party IP, a pre-designed component that has been licensed from an external vendor and integrated into a chip’s design. Third-party IP is increasingly common as it allows for faster time to market and reduced costs.

However, the reliance on external IP also introduces potential security risks, as the integrity and trustworthiness of the IP provider cannot always be guaranteed. And those risks are not limited to a single sector. They have far-reaching implications across the government, as compromised semiconductor chips could lead to vulnerabilities in weapons systems, communications networks, and other vital infrastructures, hindering essential functions that could undermine national security.

Congress has taken steps toward addressing the challenges posed by third-party IP. The National Defense Authorization Act for Fiscal Year 2024, signed into law in December, includes language that recognizes the need for increased transparency and collaboration between IP vendors and the government. This legislation comes after the ratification of the CHIPS and Science Act of 2022, which aims to onshore semiconductor chip production and secure the supply chain while marking an important milestone in the effort to tackle this long-standing problem.

There are still many gaps that must be addressed to provide the government the highest levels of assurance regarding third-party IP. To further mitigate delays, cost overruns, and potential security risks associated with using third-party IP in semiconductor chips for critical applications, IP vendors could document and provide their security requirements and safeguards at the onset.

This would provide transparency for the user of the IP — the system-on-a-chip, or SoC, developer, or in this case, the U.S. government — and allow it to better vet the IP, regardless of how many months or years down the line a review is needed. This evidence should be measurable to provide quantifiable security assurance. By providing that higher level of visibility, the government, or any other user, can more easily assess whether the IP meets necessary program security requirements.

Unfortunately, vendors often provide their IP without any accompanying security evidence as part of their documentation, leaving users in the dark about potential risks and the level of assurance to assign to the IP. Vulnerabilities can be assessed and mitigated through a security “sign off” process that relies on meeting security requirements established early on in the development process.

The vendor rarely knows what the end application is, so SoC developers must be able to evaluate the IP in the context of their specific requirements. Having the necessary security evidence to review as part of the IP documentation package provides the microelectronics design community with IP that has been “signed off” for meeting security assurance requirements. It demonstrates that specific security weaknesses and vulnerabilities have been mitigated, security features implemented, and potential risks averted. Programs exploring the viability of third party IP could then determine whether said IP suits their needs — or if additional information or modifications are necessary to further ensure the security of the final product.

IP vendors want to offer their customers all of the necessary assurances they require, just as long as it doesn’t involve giving access to the inner workings of their IP. They have a legitimate desire to safeguard their IP to maintain a competitive advantage and a predictable revenue stream. For the sake of providing a higher level of assurance and transparency, the IP provider can’t be required to give up their most sensitive information.

So, to address those concerns, vendors and developers — the U.S. government — should adopt a proactive, cooperative approach that prioritizes solutions that maintain the confidentiality and integrity of the IP. It needs to be grounded in a shared commitment to national security and the integrity of critical systems.

Likewise, a further step toward enhancing trust and mitigating risks would be to have independent security verification of the third-party IP. This objective evaluation would generate verifiable security evidence from the IP provider that could be used by the SoC developer to ensure secure integration, configuration, and use.

This independent verification would also help meet various compliance requirements, which often mandate a security assessment. By having an impartial entity validate the security claims and documentation provided by the vendor, the government could gain greater confidence in the trustworthiness of the IP.

Ultimately, the only way to truly address the mounting concerns — today, chiefly those from the U.S. government — that critical systems may be susceptible to failure due to compromised third-party IP components is for the vendors and developers to work together to comprehensively validate their security proactively. This will ensure these chips and the devices, products, and programs that rely upon them will operate as intended without the risk of being hacked by an unknown entity.

Jason Oberg is CTO and co-founder of Cycuity, a cybersecurity company that offers security assurance for semiconductor chip development.

But intent and triumph are not one and the same. How can the government, not known for cutting-edge tech adoption or top-tier salaries, attract the best AI talent in the face of a significant skills shortage and a recruiting field dominated by the big spend and brand appeal of tech titans like Google, Facebook, and OpenAI?

The government must lean into one advantage that no other employer can offer: the mission. There has always been interest among young professionals to engage in work that has a tangible impact on society, and government tech roles can be particularly attractive. Developing AI applications to keep the nation safe, improve the delivery of government services, and better the lives of hundreds of millions is a compelling draw.

For example, AI solutions are being used today to reduce the flow of fentanyl across our borders, analyze weather hazards to protect the public from excessive heat, improve veteran experiences with the Department of Veterans Affairs, and so much more. With AI, the government aims to elevate its services across a broad range of use cases in healthcare, transportation, commerce – you name it.

Just about every agency will be impacted, including the Departments of Agriculture, Housing and Urban Development, Justice, and Labor. For any AI tech worker passionate about improving government and the lives that depend on it, there will be countless opportunities to create innovative solutions that address real-world challenges.

But hiring these humanity-driven tech professionals is one thing. Retaining them is another.

It’s hard to hang on to tech talent, and that is particularly true for data scientists. As enthusiastic as they may be coming in to support the government’s mission, these workers must be continuously empowered and enabled to have the impact that they hoped to have. This requires bureaucratic empowerment by senior leaders, but it also means giving talent access to the data, tools and infrastructure they need to build innovative AL/ML solutions – with proper security, governance, and responsible AI capabilities in place – so they can have a direct hand in improving people’s lives.

The government can also offset its disadvantage in compensation levels by offering other forms of financial compensation, including student loan forgiveness – an authority the government already has – and additional education or training that can support future career growth within and beyond the public sector.

One of the most important ways for government agencies to reel in AI expertise is to be intentional about the AI talent they need, as compared to the tech sector. While Big Tech will pursue world-class data scientists and AI engineers to build bespoke AI models and products, the government needs different skills for different purposes. Product managers can serve as connectors between the agency’s mission and AI talent and tools, which can include contractors and suppliers that provide the skills and commercial-off-the-shelf products that support that mission.

Government agencies also need skilled leaders who can push bureaucratic processes forward in areas like procurement, budget, and governance – all of which require specialized knowledge, experience, and talent.

Success as a CAIO, for instance, requires more than technical expertise; it demands a special blend of political savvy and bureaucratic acumen. Without the ability to navigate the complex landscape of government operations and aligning AI strategies with broader agency goals, there’s little even the most brilliant mind in AI can accomplish.

Supporting an agency’s mission in the long term also hinges on fostering a long-term talent pipeline. This is one area where the government has proven formidable. Programs like the U.S. Digital Service, U.S. Digital Corps, Presidential Innovation Fellows, and 18F not only create pathways for tech professionals passionate about government into government roles, they’ve created a fast lane for cutting-edge Silicon Valley innovation to transform federal bureaucracy.

Indeed, many participants in these programs in the 2010s have returned to the government in more senior technology roles in the 2020s – a testament to the draw of public service.

Can the U.S. government compete for today’s top AI talent? Historically, attracting the world’s top tech talent is what our country does best. With AI poised to reshape economic landscapes and geopolitical power balances, our government understands the stakes.

And for me, this makes the U.S. an easy bet.

Former Department of Homeland Security official Joel Meyer is currently President of Public Sector at Domino Data Lab, provider of the leading Enterprise AI platform trusted by over 20% of the Fortune 100.