According to a Federal Register notice Tuesday, the $1.4 million committee will focus “exclusively on human performance,” providing guidance and insight on improving function, combating the physical, mental and emotional tolls of military service known collectively as “operator syndrome,” and preventing physical injuries and operational stress. 

“The Council will serve as a high-impact, low-cost mechanism for the [DoD] to secure the expertise of the nation’s foremost leaders at the nexus of warrior health and performance,” the announcement stated. 

The Pentagon established a Warfighter Performance Optimization division earlier this year within Under Secretary of Defense for Personnel and Readiness Anthony Tata’s office. It is intended to oversee and coordinate the individual services’ efforts to improve troops’ readiness and performance.

In May, Defense Secretary Pete Hegseth directed Tata to report on existing optimization initiatives across the services to create a department-wide performance optimization plan. 

Hegseth said he wanted to accelerate fielding technologies that will improve performance — such as wearable devices and other analytics tools — and focus on elevating “cognitive performance as a key to readiness.” 

“By building on and modernizing the principles of Total Force Fitness (TFF), WPO will deliver a unified operational approach to accelerate readiness, dominance, and peak performance across the Force. We will treat the Warfighter as a readiness capability, held to the same disciplined evaluation, maintenance, and optimization we demand of every asset that preserves combat power,” Hegseth wrote. 

The services have created their own approaches to health, fitness and human performance within the last several years. Army introduced its Holistic Health and Fitness initiative in 2020 to improve the health of the force and reduce the number of soldiers considered non-deployable because of chronic medical conditions. 

The Navy introduced its Human Performance Optimization program as a pilot in San Diego in February, providing training and education on nutrition, sleep, injury prevention and stress management.  

The Marine Corps has had a total fitness strategy since 2023 that combines wellness, fitness, mental health and data to improve the health of members, while the Air Force is building a new human performance optimization facility at Davis-Monthan Air Force Base in Arizona, which is designed to support Air Force Special Warfare airmen. 

The new advisory committee will have up to 20 members with expertise in an array of scientific and medical fields, including urology, endocrinology, nutrition, neurology, combat stress, orthopedics, preventive medicine, wearable technology or spiritual, psychiatric or psychological health, sleep medicine and human factors engineering.  

As with all federal advisory committees, volunteers are unpaid and only receive travel pay and per diem reimbursement when conducting council-related business. 

The announcement described the council as “an exceptionally cost-effective resource.” 

The newly formed group, the announcement stated, will provide information that helps the services create “lethal, operationally ready warriors prepared physically, psychologically, for successful large-scale, high kinetic, combat operations against peer adversaries who are imbued with the essential Warrior Ethos to win decisively,” the announcement stated.  

Shortly after Hegseth took office last year, he dismissed the members of roughly 40 Defense Department advisory boards and launched reviews to determine whether they supported his goal to “revive the warrior ethos” in the U.S. armed forces. 

The Defense Advisory Committee on Women in the Services and the Defense Advisory Committee for the Prevention of Sexual Misconduct were among those terminated.

Hegseth has also created several new advisory boards since being sworn in, most recently, the Homeland Defense Board, announced Sept. 11, which he plans to chair. The board will provide guidance on military support for homeland security missions. 

The Total Army Combat and Training Munitions Information System, or TACTMIS, is meant to replace the previously used Total Ammunition Management Information System, or TAMIS, once it retires on Oct. 30. TACTMIS aims to update how the Army plans, manages and reports munitions for training, testing, operational and combat activities, according to a recent release.

“TACTMIS is a foundational step in modernizing how the Army manages the munitions that enable readiness and warfighting,” Army Chief of Munitions and G-3/5/7 Deputy Chief of Staff John C. Hinnant said in the release. “It gives the Total Army a more authoritative, integrated and accountable way to generate requirements, manage authorizations and maintain trusted visibility of munitions data across the force.”

TACTMIS, developed under the Software Acquisition Pathway, was built using the Appian Platform to be a cloud-enabled, low-code “Software-as-a-Service” capability, the announcement says. The system supports a variety of inputs such as requirements calculations, authorization management, request processing and enterprise reporting.

Using a common organizational framework, the system is meant to reduce manual workload, improve data integrity and increase the visibility of munitions demand and fulfillment across the service and its joint partners.

The upgraded system can coordinate workflows across enterprise systems while maintaining the commanding role of the Army systems and data sources it interacts with, per the statement, supporting readiness planning while providing timely data to inform decision-making for senior leaders and defense industrial base requests.

“TACTMIS moves the Army from fragmented and manual munitions-management processes toward a modern digital capability built for the scale and speed of today’s force,” CW3 Deidre Burgos, TACTMIS program manager, said in the release. “Our focus is ensuring commanders and staffs have reliable tools to manage munitions requirements, authorizations, forecasts and expenditures with greater accuracy, transparency and confidence.”

The system is also aligned to support the Army’s broader modernization efforts such as Ammo360, which is a software initiative meant to boost ammunition accountability and unify the operating picture within the service’s network.

TACTMIS is designed to support over 10,000 users across the globe and operate without dedicated unit-level administrators. The system’s platform allows for TACTMIS to evolve in increments as the Army’s requirements, policies and mission needs change so redesigns are unnecessary for future enhancements.

Planned enhancements include a classified capability intended to support real-time combat munition requirements and expenditure reporting for readiness and logistics operations, the announcement reads.

“Delivering this initial release is an important milestone, but it is also the beginning of an enduring modernization effort,” Burgos said. “TACTMIS provides the digital foundation the Army needs to evolve alongside future operational requirements while maintaining uninterrupted support to the force’s ability to arm, train, and sustain.”

The company said Oct. 14 that the expansion will help the plant reach record production levels and deliver components to final-assembly sites, including Camden, Arkansas and Troy, Alabama.

The project expands the plant’s manufacturing footprint to more than 735,000 square feet. The expansion adds 100,000 square feet of new space and converts 85,000 square feet of office space into factory floor space for automated, high-precision machining.

Nearly 800 production employees work at the plant, which produced 250,000 parts in 2025. Lockheed said it has added more than 30 high-precision machines in recent months and expects to install nearly 100 additional machines by the end of 2026.

Lockheed also said Hadrian, a California-based manufacturing startup, will install 24 automated machines at the Grand Prairie facility to produce missile parts. Lockheed employees will operate the equipment, which is expected to be up and running by early 2027. The project follows a memorandum of understanding the two companies signed in December 2025.

“The warfighter can’t wait on peacetime timelines,” Hadrian CEO Chris Power said in the release. “Rebuilding the Arsenal of Freedom at the scale America needs will take partnerships that combine expertise and speed, and this is what that looks like.”

The buildout supports a series of framework agreements the Defense Department has signed with Lockheed since January, designed to boost missile production and lead to long-term contracts. The first aims to increase PAC-3 MSE production from about 600 to roughly 2,000 interceptors per year over seven years.

The Army followed with a $4.7 billion contract in April, then converted it in July into a seven-year production contract worth about $58.6 billion in total.

A separate THAAD framework, signed in January, led to a June contract from the Missile Defense Agency worth more than $35 billion to quadruple interceptor production. Lockheed and the Pentagon announced similar agreements for the Precision Strike Missile on March 25 and for the AIM-260 on Sept. 17.

“Lockheed Martin has brought together commercial speed and combat-proven performance because America needs both,” said Jim Taiclet, Lockheed’s chairman, president and CEO. “By combining advanced technology with the expertise of our American workforce, we’re transforming manufacturing to deliver critical munitions at speed and scale.”

“This expansion is more than just a new facility; it is a stronger supply chain and a more resilient industrial base,” said Michael Duffey, the Pentagon’s undersecretary for acquisition and sustainment.

The Grand Prairie investment is part of Lockheed’s plan to spend $8 billion to $9 billion through 2030 to increase munitions production and modernize or expand more than 20 U.S. facilities. The company said it plans to create 6,000 jobs nationwide, including 2,000 in Texas.

Defense Secretary Pete Hegseth addressed AUSA attendees at the Project Agincourt panel on Wednesday, sharing that the Pentagon is requesting roughly $50 billion in reconciliation funding to support the push to scale autonomous and robotic systems.

This request is part of an effort to make the technology available in far greater numbers.

The figure is separate from the Pentagon’s fiscal 2027 budget request, which includes $53.6 billion for the Drone Dominance initiative. That request covers $16.9 billion for unmanned-system procurement, $14.4 billion for counter-unmanned systems, $13.5 billion for contested logistics, $4.5 billion for collaborative autonomy and $4.3 billion for institutional systems and personnel. The budget request does not establish that the reconciliation funding Hegseth cited is the same money or that it is dedicated entirely to drone purchases

Hegseth characterized the funding as a one-time investment rather than a recurring annual allocation, intended to accelerate the development and production of autonomous and robotic systems.

“Ultimately we will be dealing with hundreds of thousands of one-way attack systems this year and into the millions in years to come at a pace that this department’s never ever seen before.”

The Defense Secretary said the Pentagon must make it easier for new companies to compete in a defense market long dominated by established contractors and costly platforms. Traditional defense firms remain important, he said, but the department also needs lower-cost systems that can be manufactured at scale.

The Army’s Drone Dominance program offers a concrete measure of that ambition. In a December 2025 announcement, the Army said a $1 billion initiative would fund approximately 340,000 small unmanned aircraft systems for combat units over two years. The service said it expected to deliver tens of thousands of drones in 2026 and hundreds of thousands by 2027.

Acting Army Secretary Adam Telle said the service is broadening access to its programs for companies outside the traditional defense industrial base. The Army, he said, must make room for new entrants while continuing to work with established suppliers.

Telle also described plans to coordinate the Army’s autonomous-systems efforts while distributing capabilities to operational units. The service is developing an approach that incorporates drones, autonomous ground systems, autonomous fires and autonomous lift into future combat operations.

“We have an MOS in the Army, 390A, where warrant officers could keep the speciality and the skills over the duration to teach our soldiers how to do robotics,” Telle added.

Expanding access to Army test ranges is another part of that effort, Telle said. Greater access gives developers more opportunities to test systems and receive feedback from military users. He also described efforts to share lessons across the force rather than have individual units and organizations solve the same problems independently.

Hegseth said the department must remove bureaucratic barriers that slow the adoption of new technology, telling the panel, “I want you to tell me which rules can be signed away.” He urged officials to identify rules and directives that could be changed without involving new legislation to accelerate progress.

Sen. Chris Murphy, D-Conn., visited the Middle East this week on a Congressional Delegation trip, speaking with Gulf region leaders and visiting American facilities to assess damage done by the Iran war. Murphy was denied access to Al Udeid Air Base, Qatar, which had suffered damage from drone strikes during the conflict.

“They are using every tool they can, including withholding information about damages, slow walking the pace of reports about casualties and denying us access to see the damage as part of a campaign of cover-up, so as to mask the true cost of the war,” Murphy told reporters on Thursday.

The “unprecedented” base denial prepared Murphy, a member of the Senate Foreign Relations Committee and Defense Appropriations Committee, in the coming days to draft language that would explicitly require the Department of Defense to grant members of Congress access to military bases overseas under all circumstances if needed.

“I don’t have any illusions that that’s going to pass between now and the end of the year, but I think that’ll be a really important part of the discussion around an appropriations bill next year and the defense authorization bill,” he said during the press call.

Prior to his trip, Murphy requested access to the base through a letter and direct appeal to U.S. Central Command leadership. But he was denied access even as the Department of State supported his trip to the region, with the Defense Department saying it was due to previously imposed travel restrictions.

“Senator Murphy’s office was informed before his trip to the Middle East that he would not receive Department of War support to access Al Udeid Air Base, consistent with the Secretary of War’s directive on travel restrictions in the region ordered on March 3, 2026,” a senior Defense Department official told Military Times on Thursday.

“That decision was communicated in advance by the Office of the Secretary of War for Legislative Affairs,” the official continued. “The Department applies the Secretary’s guidance evenly.”

In early March, the State and Defense departments issued travel guidance, calling on Americans to depart areas in the region and updating its travel advisory to recommend against visiting certain countries, including Qatar.

“It is absolutely ordinary for members of Congress to travel to areas of conflict and get to talk directly to the military leaders and the soldiers that are involved in the conflict and see for ourselves the damage that has been done to our bases and equipment,” Murphy said, highlighting how during the Iraq and Afghanistan wars he was able to visit operating bases.

He argued that since Congress decides funding and authorization for war, it is necessary to see the consequences, but he was unable to visit Al Udeid or have a briefing on the war with American military officials while in the region.

On the same day the travel advisory was issued in March, the U.S. embassy in Riyadh, Saudi Arabia, was hit ​by two Iranians drones, resulting in building damage and a fire. Murphy said that the drones impacted multiple floors of the embassy and part of the space is now “uninhabitable” with permanent damage.

The U.S. previously announced in 2023 plans to build a new embassy compound in Riyadh, which Murphy attributes the lack of repairs to.

Even though no injuries or casualties were reported from the strike, Murphy said that if the attack happened during the day it would have killed many Americans.

“[Secretary of Defense Pete] Hegseth is determined to hide the cost and the consequences of this war from the American public, and it is absolutely outrageous that I and Republican senators are being denied the ability to see the damage for ourselves,” he said.

Now, Pentagon officials say that some of that AI is not part of the current revamp of the polygraph interview process, after Defense News asked for a response to concerns about the earlier statements and the slides.

On Wednesday, the Pentagon’s Defense Counterintelligence and Security Agency, or DCSA, which vets security clearance holders and applicants, said in an emailed statement that “active research and development” for the “Modernizing Polygraph” effort “does not incorporate generative super intelligence, also known as artificial intelligence,” that creates new content — such as emails, graphics or voiceovers.

Nor does the effort include “large language models,” meaning chatbots like ChatGPT and other programs trained on giant data sets to engage in human conversation, DCSA added.

And the research does not involve “facial action coding [of emotions], micro-expression analysis or vocal analyses,” the statement said. “While those technologies are not part of the effort,” DoD will “continue to monitor emerging scientific capabilities to evaluate their potential utility down the road.”

DCSA did not address other types of AI models that, according to the slides, researchers had been developing to scan spoken and written language for “deceptive speech” patterns.

Wednesday’s statement came after Defense News sought a response to criticisms from national security lawyers, scientists and AI auditors about AI’s ability to analyze deception — meaning not just to lie, but to do so knowingly and willfully.

They warned that AI-aided scanning of speech patterns, vocal stress or facial expressions to read minds lacks scientific backing, will compound errors and may violate civil liberties in a domain where few such rights exist.

Defense News chronicled their concerns and the Pentagon’s prior research and development of AI-aided lie-detection and emotion-estimation tools.

The recent DCSA statement, including the project name “Modernizing Polygraph,” contrasts with several earlier DoD statements, 2027 budget documents and DCSA slides that Defense News obtained through an open records request.

In July, a Pentagon official, who spoke on condition of anonymity to discuss the technology, explained the advantages of AI-driven sentiment and deception analysis.

“AI processes data in real time and enables standardized, objective data analysis,” the official told Defense News, via email. “AI-based analysis is a force multiplier for our human investigators, not a replacement.”

The official added, “The models are primarily trained on data from laboratory-controlled studies using volunteer participants.”

The DCSA slides, which include presentations from 2021 through 2025, show that the Air Force, DCSA and academic labs had been working on “sentiment analysis” AI models and “deceptive speech” AI-aided analysis since 2019, as part of a “Credibility Assessment Modernization” project.

In July, the DoD official described the AI models as part of a larger multi-year “transformation,” which the official referred to interchangeably as “Polygraph+” and Credibility Assessment Modernization.

Current budget materials price the Polygraph+/Polygraph Next project at $31 million, including costs for AI “scoring algorithms” and “decision aids,” thermal imaging tools to spot blood flow changes that can reflect stress and other non-contact sensors.

On Friday, DCSA declined to provide additional information, including the scope of the “Modernizing Polygraph” project and the decision not to include AI-based voice screening and facial expression analysis.

Trained on Twitter and Reddit

Over the summer, Farakh Zaman, a developmental leader at the Air Force Office of Scientific Research, elaborated on the appeal of AI-aided deception analysis.

“By processing subtle physiological, vocal and linguistic cues, these developmental algorithms may help establish a more objective baseline for investigators and pinpoint specific areas requiring further human-led clarification,” he said by email in July.

Wednesday’s DCSA statement said that the Air Force is not involved in the “active” research and development phase.

One undated declassified DCSA slide describes the Air Force amassing “deception-related” text to create a “deep learning model,” an algorithm that analyzes hordes of data to find patterns. The Air Force trained an early model on text from websites including Twitter, Reddit and other vocabulary data sets such as WordNet, according to the slide.

“This baseline training helps the algorithms understand natural, modern linguistic patterns, slang and everyday vocabulary,” Zaman explained in July. He acknowledged the need for “further rigorous testing, validation and a clear transition path” before fielding a prototype.

A separate DCSA slide, dated May 2025, contains a flowchart that depicts an avatar — a computer-generated image of an interviewer — in front of a security clearance applicant. Next to the applicant, a camera and microphone feed audio, video and speech-to-text data from the interview into various large language models. The recording devices and algorithms interact to gauge the applicant’s emotional state, while a human investigator observes and keys in questions for the avatar to ask.

DCSA’s Wednesday statement said the university that drafted the chart is not involved in the current research and development stage.

According to another undated DCSA slide, DoD has set a goal for natural language processing technology to interpret an interviewee’s feelings with 75% accuracy.

In July, the Pentagon official said by email that a human investigator remains essential for “the contextual reasoning and emotional intelligence required in these sensitive interviews.”

‘I’ve caught AI lying to me’

Ahead of Wednesday’s statement, Mark Zaid, a national security attorney who reviewed the slides, warned that the danger of derailing a military officer’s career is too great for AI to misinform an investigator.

The polygraph device “is just registering the physiology of the person,” such as spikes in breathing rate, perspiration or blood pressure, he said. “Then a human examiner analyzes those reactions to render an opinion.”

Here, however, “AI would be taking the polygraph readings and rendering an opinion” to the human examiner, said Zaid, who has represented individuals on all sides of the polygraph table, from workers disputing revoked clearances to former government officials and polygraphers.

“Now, we’re starting to get into the movie Minority Report,” he said, referencing a 2002 Steven Spielberg film that depicts a government reliant on psychic children for tips to predict crimes and detain people accused of future crimes.

Zaid, whose own clearance was revoked temporarily after he represented a whistleblower pivotal in President Trump’s first impeachment, said, “That concerns me more than the polygraph,” if science does not back AI’s reliability.

So far, scientific studies do not.

Rather, decades of research have discredited theories, popularized by shows such as Lie to Me, that anyone — human or artificial — can recognize deception based on speech patterns, vocal stress or facial movements.

Another concern scientists and auditors have is bias: the Justice Department has warned that using emotion-recognition algorithms to measure worker competency can discriminate against high performers with intellectual or developmental disabilities, who algorithms do not always understand.

Also, “automation bias,” the tendency to take AI’s advice without question even when conflicting information exists, may further erode the polygraph system’s reliability, technologists warned.

“[T]here is simply no consensus that polygraph evidence is reliable,” the Supreme Court declared in a 1998 decision banning polygraph results and polygraphers’ opinions from military courts.

Zaid said he appreciates the attempt to retool polygraph testing but wants proof that the planned approach is in fact an improvement.

“Anytime we might be able to scientifically advance the ability to determine truth, with accuracy, would generally be a good thing,” he said. But “the first thing that jumps out at me with AI is how often it is wrong…I’ve caught AI lying to me.”

Greg Rinckey, a former Army Judge Advocate General Corps officer who now provides security clearance representation, said that today’s “technology is so outdated, where they’re using tubes around people’s chests and blood pressure and sweat, so, any way that you can get a more reliable test for security clearances, especially counterintelligence investigations [into leaks], is a step up.”

That said, he questioned, “What is the research saying on how accurate it is?”

At present, research suggests the odds of AI-aided speech, voice or face analysis pegging a lie are about 50:50.

AI is ‘assuming dishonesty’

“There are no – reliable – diagnostic cues for deception detection, and I have yet to see any evidence, whether it is with humans or with artificial intelligence, that goes against that trend,” said David Markowitz, a Michigan State University professor who studies AI’s ability to understand human communication.

For instance, “the leakage idea — that these microfacial expressions will leak out from our awareness, signaling veracity or deceit — there’s very little evidence to support that, unfortunately,” he said.

Markowitz expressed doubts about AI-based deception analyses that claim an accuracy rate of 75% because “that is not how accurately humans do it, and often these systems are a big reflection of how humans do it.”

For example, he pointed to a recent experiment in which he prompted a Google Gemini AI model to examine audio and video of mock interrogations of accused cheaters in a trivia game, all of whom claimed innocence and some of whom were lying. Prior studies had asked humans to observe the same interrogations. DoD has entered into agreements to run a secure version of Gemini on unclassified and classified networks.

Markowitz said that his study, “The [in]efficacy of AI personas in deception detection experiments,” found Gemini was just as inaccurate as humans, both faring no better than chance, when prompted to distinguish fraudsters from truth-tellers.

What’s more, compared to humans, AI was more likely to wrongly accuse a trivia player of lying.

Markowitz gave one possible reason for AI’s systemic distrust of trivia players: The AI “is assuming that someone must have done something wrong because why else would they be questioned,” he said. “Anytime that someone is in an interview setting where they might be accused of something, a large language model is assuming dishonesty.”

Supreme Court: The jury is the lie detector

The consequences of a machine, whether a heart monitor or a voice screener, potentially bungling a credibility assessment can last a year or longer, said Zaid, the national security lawyer.

When officers who have successfully passed exams without issue suddenly fail their latest polygraph test, DoD typically puts them “in a corner with a dunce cap on for a year before officials will re-administer another exam,” he said. “You can’t get promoted. You can’t get certain assignments. And you can’t go overseas, which, to case officers, is death careerwise.”

Further, civil courts routinely dismiss complaints when employees claim that inaccurate results cost them their clearances. Nearly 40 years ago, the Supreme Court ruled that the courts have no power over such national security matters.

Concerns about power imbalances and due process prompted the European Union to label AI-aided polygraph tools as “high risk” and place strict limits on law enforcement’s use of them.

Stateside, the Supreme Court, in forbidding polygraph evidence in military courts, noted that allowing it would meddle with the human’s role, or, as it were, the jury’s role, in determining credibility.

“A fundamental premise of our criminal trial system is that the jury is the lie detector,” Justice Clarence Thomas wrote in the Court’s 1998 United States v. Scheffer decision.

Pointing to the court’s decision, Zaid said that he wants assurances of due process when staff undergo administrative proceedings to contest a revoked clearance resulting from misaligned algorithms. Comparing the situation to successful cases disputing speeding tickets caused by a miscalibrated street camera, Zaid questioned, “Would the person be provided the evidence? An understanding of the AI’s training?”

New biases

Pentagon officials have long stressed the desire for AI-based lie detection to help curb gender and cultural biases that human investigators may carry into an interview room.

At the same time, employers’ use of similar technology for pre-employment screening has faced allegations of other biases and system errors.

“Facial expression analysis is heaviest in terms of biases against individuals with disabilities,” said Jo Ann Oravec, a University of Wisconsin professor whose research focuses on AI, public policy and disability issues.

For instance, AI-powered video screening of job applicants tends to misinterpret the involuntary twitches or vocal outbursts of skilled people with certain disabilities — and thus pass over qualified applicants, said Oravec, author of the 2024 article “From Polygraphs to Truth Machines: Artificial Intelligence in Lie Detection.”

In response to concerns about such biases in July, the Pentagon official said via email that the credibility assessment modernization plan adheres to DoD’s AI Ethical Principles of “responsible, equitable and traceable” use of algorithms.

The Air Force’s Zaman, in his July email, said that his team’s work aligns with DoD’s Responsible Artificial Intelligence Guidelines.

Researchers “are actively engineering and testing these models” to account for “diverse, representative training data,” he stated. The testing covers “broad variations in speech, language and expression.”

Ryan Carrier, founder of ForHumanity, a global nonprofit that helps organizations audit AI systems, said that the Pentagon’s principles and guidelines are a skeleton of those that the European Union follows and that ForHumanity uses for inspections.

For example, the EU’s AI Act demands users of high-risk systems receive training to overcome a different kind of bias called “automation bias” — or the tendency to execute AI’s advice without questioning its accuracy. This bad habit can lead to incorrect data overriding correct decisions, Carrier said.

Also, multimodal systems, meaning AI systems that simultaneously parse audio (the subject’s voice), video (their facial movements) and text (interview transcriptions), tend to misalign data and results, yielding an irrelevant analysis, Carrier said.

The system “could be making determinations that a person is lying or trying to deceive me that are outside of the tool’s specifications,” he explained.

In response to concerns about multimodal systems in July, the Pentagon official had said, “Any automated output is treated strictly as auxiliary data for a highly trained, certified polygraph examiner.”

Similarly, Zaman, at the time, said that investigators who use AI-aided deception-detection systems are “trained to contextualize the tool’s findings, preventing automated outputs from dictating an outcome.”

To safeguard against mismatched data or results, the Air Force keeps a documented history of each piece of data’s origin and modifications and brings in independent white-hat hackers to try producing false correlations, he added.

“We recognize that multimodal AI systems present unique technical challenges, and mitigating these risks by hardening our systems is central to our engineering and testing protocols,” Zaman said.

Reason for suspicion?

In August, when the Pentagon administered a raft of polygraph exams to probe leaks alleging the Iran conflict is depleting U.S. arsenals, some observers suspected the endgame was not to find the leakers, but to crack down on disloyalty.

Critics of the planned system said that AI-based deception analysis may be best suited to achieve the same purpose.

“If it’s purely an intimidation technique, it may not be utterly useless from the point of view of large bureaucracies,” said Jay Stanley, a senior policy analyst with the American Civil Liberties Union’s Speech, Privacy and Technology Project.

The expectations for AI-powered trustworthiness testing resemble the hope that U.S. national security officials held out for the polygraph about 100 years ago, other lawyers said.

Polygraph devices “were seen as this magic-miracle-machine when they first came out,” and, over time, the government learned that when seemingly making deductions, the tools were “actually just flagging correlating factors, like heart rate and physiological factors that can indicate lying, but aren’t actually reflective of it,” said Jake Laperruque, deputy director of the Center for Democracy and Technology’s Security and Surveillance Project.

He added, “Thinking that AI sentiment analysis tools are actually making an assessment or engaged in reasoning — that’s not what those machines are actually able to do.”

The five-year contract, which includes two additional option years, the Navy said, is meant to provide a steady and reliable supply of the SM-6, a missile that can carry out both offensive strikes and missile defense missions.

The SM-6 award is the latest in a series of large munitions contracts the Pentagon has pursued this year to pressure contractors into ramping up output. It follows a $20.7 billion provisional multiyear deal for Raytheon’s AMRAAM air-to-air missiles in late September and a $58.6 billion Patriot interceptor deal awarded to Lockheed Martin in July.

The production agreements are designed to entice contractors to move faster while surging production. They are part of a broader push by the Trump administration to prioritize weapons production over shareholder returns.

Industry executives have warned that Congress has not yet appropriated funding for the deals, meaning contractors may be unable to invest at scale in components and facilities until lawmakers act.

RTX has said it has invested heavily to keep up with rising demand. It has expanded its skilled workforce, strengthened partnerships across the defense industrial base and automated production, with the aim of significantly increasing output for near- and long-term needs.

Raytheon says the SM-6 is the only combat-proven weapon that can perform anti-air warfare, anti-surface warfare and ballistic missile defense. It has been fired from a range of Navy ships as well as from land-based launchers.

The 2-1 decision by the U.S. Court of Appeals in Washington came in a lawsuit by Anthropic challenging its March designation by the Pentagon as a national security supply chain risk, which the startup says has cost it billions of dollars in lost business and damaged its reputation ahead of a highly anticipated initial public offering.

The court’s majority said it was reasonable for the Pentagon to designate Anthropic after it refused to allow its products to be used for autonomous weapons or mass surveillance. It rejected Anthropic’s claim that the Pentagon had retaliated against it for its views on AI safety and ethics.

Siding with Hegseth’s argument that Anthropic’s safety restrictions could compromise military operations, the majority said, “The Secretary raises the deeply sobering prospect of overly constrained AI models shutting down unexpectedly and thus causing important military operations to fail,” in an opinion by Judge Gregory Katsas.

San Francisco-based Anthropic said in a statement Friday that it respectfully disagrees with the decision but remains confident in its position and is considering its options, including review of the three-judge panel’s decision by the full appeals court.

The White House and the Department of Defense did not immediately respond to emails seeking comment.

A federal judge in San Francisco last month struck down a parallel designation under a different law, finding the administration had unlawfully retaliated against Anthropic for its views on AI safety. U.S. District Judge Rita Lin in San Francisco also blocked Trump’s government-wide ban on Anthropic and Hegseth’s order barring military contractors from doing any business with the startup.

Hegseth designated Anthropic as a risk under two different laws after Anthropic refused to remove guardrails against its technology being used for autonomous weapons or mass domestic surveillance.

The unprecedented move came after months of negotiations ended in failure and public recriminations by Hegseth and Trump, who accused Anthropic of endangering American lives with ideological posturing.

Anthropic denied that characterization and said AI is not yet reliable enough to be safely used in autonomous weapons. The company also said it opposes domestic surveillance as a violation of fundamental rights.

The president cited national security concerns for the move, echoing the rationale offered for the roughly $400 million ballroom complex being built on the site of the White House’s former East Wing, which was demolished to make way for the project. He did not identify any specific threats.

The projects are part of Trump’s ambitious effort to reshape Washington, including a push to add his name to the John F. Kennedy Center for the Performing Arts. The plans have drawn criticism from preservationists and others who argue they could alter or diminish historic landmarks.

In a social media post, Trump said that at the “strong request” of the military he had agreed to turn the 250-foot (76-meter) arch “into a top grade Military Complex/Triumphal Arch, to house, store, and have the rapid ability to use large numbers of drones, plus Snipers, on both the roof and plaza areas, and additionally have and hold large quantities of sniper ammunition in storage.”

The White House and the Pentagon did not immediately respond to a request for comment.

The Federal Aviation Administration said last week that the arch would not pose a hazard to aircraft but would be required to have an “eternal flame” on top, clearing an aviation hurdle for the arch, which Trump proposed to mark the nation’s 250th anniversary.

Aviation experts have raised safety concerns given its proximity to Reagan Washington National Airport, while veterans have sued to block the arch, arguing it would destroy the historic sightline between the Lincoln Memorial and Arlington National Cemetery.

The concern, critics say, is not limited to weapons that can select and engage targets on their own.

At the hearing, titled “Artificial Intelligence in the Military Domain: Implications for Human Rights,” witnesses told members of the Tom Lantos Human Rights Commission that AI can influence human decisions leading to a strike while leaving the individual formally responsible for the final call.

“The approval button alone does not demonstrate the control,” Anna Mysyshyn, a Ukrainian AI-governance researcher, told lawmakers.

The issue comes as the Pentagon pushes to use AI to accelerate military decision-making. The Pentagon’s 2023 AI adoption strategy identified “fast, precise and resilient kill chains” as a desired outcome, while its 2026 AI strategy calls for becoming an “AI-first” warfighting force by redesigning military workflows and operational concepts around current AI capabilities.

Mysyshyn questioned whether a person supervising multiple AI-enabled systems can recognize an incorrect recommendation and intervene fast enough before harm occurs. She cited Ukraine as an example of AI compressing decisions from hours to minutes.

In many scenarios, a human making the final decision does not necessarily have enough information, time or the ability to challenge the system’s recommendation, she said.

The Defense Department’s 2023 directive on autonomy in weapon systems requires autonomous and semi-autonomous weapons to allow commanders and operators to exercise appropriate levels of human judgment over the use of force.

Wednesday’s testimony focused on a broader question: whether that judgment remains meaningful if AI is influencing targeting faster than a human can authenticate.

Amanda Klasing, national director of government relations and advocacy at Amnesty International USA, warned that AI can compress the military “kill chain” in ways that make it difficult to determine whether meaningful human discernment actually occurred before a strike.

Joseph Chapa, a former military officer and scholar of military ethics, argued that the debate should not focus solely on how autonomous a system is. He urged policymakers to consider whether an AI system relies on statistical inference, what happens when it fails in a particular operational environment and whether its decisions can be audited afterward.

Statistical AI systems can fail differently from traditional software, Chapa said, including producing substantially different outputs from relatively small changes in inputs. More complex systems can also make it difficult to reconstruct how a particular recommendation was produced after the fact.

He called for greater AI education across the military, including specialized training for personnel working with targeting and intelligence systems.

Witnesses on Wednesday also pointed to a larger accountability problem: determining what happens when an AI-assisted decision results in civilian harm.

The Defense Department established its Civilian Harm Mitigation and Response Action Plan in 2022, including a Civilian Protection Center of Excellence intended to serve as a hub for analysis and training. Federal law requires the Pentagon to operate the center.

But a Defense Department inspector general review released in May assessed the department’s implementation of the civilian-harm framework and found problems including the loss or reassignment of personnel, the end of funding for a civilian-harm data-management platform and the failure of a senior steering committee to continue meeting.

That matters in the case of AI because, as Klasing noted, the military currently has limited ability to determine whether AI may contribute to improper targeting of civilians.

On the first day of the U.S.-Iran war, a Tomahawk cruise missile struck Shajareh Tayyebeh elementary school in Minab, southern Iran. At least 168 people were killed — more than 100 of them under the age of 12, according to UN and Iranian officials.

The school building sat fewer than 100 yards from a long-time Islamic Revolutionary Guard Corps naval installation and was previously located within the IRGC compound perimeter until a wall appeared between 2013 and 2016, according to an analysis of satellite imagery by Amnesty International.

By the time the U.S. and Israel launched their first strikes on Feb. 28, the school had been established several years prior. It was active on social media and had its own website, a Reuters investigation found.

More than 120 House Democrats sent a letter to the Pentagon on March 12, demanding clarity on whether artificial intelligence, “including the use of the Maven Smart System, [was] used to identify the Shajareh Tayyebeh school as a target.”

U.S. military investigators in the wake of the incident stated that the strike was likely carried out by U.S. forces. The Pentagon, however, has still not released its investigative findings.

Klasing proposed adding information about AI involvement to the Pentagon’s annual civilian-casualty reports required under Section 1057 of the National Defense Authorization Act. The existing reporting requirement calls for information about civilian casualty mitigation efforts and investigations, but does not specifically require the department to identify whether AI contributed to an incident.

Steve Feldstein, a senior fellow at the Carnegie Endowment for International Peace, said the Pentagon should collect data from military operations and conduct after-action reviews to determine whether AI-assisted systems accurately identified intended targets and whether errors contributed to civilian casualties.

“A bigger question is to what extent is the Pentagon collecting data and verifying the target accuracy of all these 1000s of strikes?” Feldstein said.

Feldstein also cautioned against treating AI itself as the source of every potential problem. AI can be used to help verify intelligence, detect changes in imagery and prioritize defensive responses to threats such as drones and ballistic missiles.

But if a human-influenced system is built around assumptions that certain demographic traits make someone a lawful target, Mysyshyn said, AI would not correct that underlying premise.

Feldstein similarly pointed to the rules humans establish before an AI system is used. If commanders determine that a particular level of civilian harm is acceptable in pursuit of a military objective, he said, the machine is operating within a human-defined framework.

The challenge is particularly acute when systems operate faster than people can meaningfully assess recommendations.

The commission opened Wednesday’s hearing with an example from Iraq. In 2004, Army squad leader Nick Ellison encountered two young men firing a machine gun from a car during a census patrol in Kirkuk.

Ellison made eye contact with one of the men, saw panic and ordered his soldiers to hold fire. The men turned out to be brothers of a newly married groom, and the gunfire was celebratory.

Mysyshyn said testing should examine bias, reliability, civilian protection, realistic time pressure, whether operators can interrupt systems and whether decisions can be traced throughout an AI system’s lifecycle.

Chapa said some AI systems may be difficult to audit after the fact, while Deborah Brown of Human Rights Watch said information about military AI use has often emerged through investigative reporting and whistleblowers rather than government disclosures.

The growing challenge, according to witnesses, is no longer making a machine pull a trigger, but whether the human who approves the trigger pull has enough time, information and authority to make a meaningful choice before disaster.

Military Times reporter Katie Livingstone contributed to this report.