Gecko Robotics announced Tuesday that the Navy is increasing the value of its initial contract to up to $300 million — just six months after the company reached an initial agreement with the sea service.

“Gecko’s AI and robotic technology can save the U.S. Navy up to $8 million in repair costs per ship and return vessels to sea quicker by identifying structural issues up to 50 times faster than traditional methods — reducing inspections from months to days,” Gecko Robotics said in a release.

The initial contract began as a 5-year, $54 million indefinite delivery, indefinite quantity deal for Gecko to work on 18 ships assigned to the Navy’s U.S. Pacific Fleet.

The company uses drones, wall-climbing robots and fixed sensors to gather data on components, decks, welds and hulls.

That information, paired with AI tools, is used to identify current and potential structural issues that may remain hidden to the naked eye.

A key part of the new contract investment is Gecko Robotics’ Komodo machine system, which analyzes the health of deck coatings by scanning — eliminating the need to physically dig into them.

This allows the Navy to plan repairs and map out damaged areas before the ship enters dry dock, something that previously only occurred after the maintenance cycle began.

The Navy has consistently stated its goal of reaching 80% fleet readiness by 2027, despite criticisms of the service’s deployment capabilities.

The Government Accountability Office reported in December 2024 that readiness rates among the Navy’s amphibious warfare ships fell to 46% between 2011 and 2020, hindering Marine Corps deployment and training plans.

In August 2025, that rate reportedly dipped to just 41%, resulting in a more than five-month gap in Marine Expeditionary Unit deployments that year and further straining resources amid the Trump administration’s push to counter the illicit drug trade in Latin America and the Caribbean.

Chief of Naval Operations Adm. Daryl Caudle, who adopted the 80% goal from his predecessor Adm. Lisa Franchetti, laid out the major tenets for achieving the ambitious milestone.

“Achieving this requires shorter maintenance cycles, increased spare-parts availability, improved training pipelines and targeted upgrades across the fleet,” Caudle wrote for Military Times in December.

APKWS kits convert unguided 2.75-inch rockets into laser-guided munitions. All four services field them, and the weapon has become a cheaper alternative to air-to-air missiles for shooting down drones.

Congress still has to approve and fund the buy, the department said. BAE said it will increase production while the two sides work out a multiyear contract. Neither side announced the deal’s cost.

The framework also outlines a path to increase output to 35,000 kits a year for U.S. allies. The department said that added capacity will come online as partner nations formally request kits through the Foreign Military Sales program.

“By securing multi-year demand, this agreement keeps production lines running at capacity, provides our forces with interceptor inventory, and flips the cost calculus in the taxpayer’s favor,” Michael Duffey, the Pentagon’s undersecretary for acquisition and sustainment, said in the announcement.

BAE, which builds the kits in Hudson, New Hampshire, and Austin, Texas, said in February that it had delivered its 100,000th kit.

The 25,000 figure in this framework agreement matches capacity BAE has cited before. A company official said in 2023 that APKWS was in full-rate production with room to grow to 25,000 units a year.

“APKWS delivers proven, reliable and affordable precision at scale to counter evolving threats and ensure our warfighters maintain a decisive advantage,” said Tom Arseneault, president and CEO of BAE Systems Inc.

The Navy’s current five-year APKWS contract with BAE, awarded in August 2025, is worth up to $1.74 billion. It covers up to 55,000 kits for the Navy, the Army and foreign customers, with work expected to be completed by December 2031.

Among allied buyers, Saudi Arabia won State Department approval in July for a possible $1.96 billion package that includes up to 20,000 APKWS kits, split evenly between air-to-air and air-to-ground versions. Italy is also weighing a buy of 5,031 kits for counter-drone defense.

The APKWS agreement is the latest in a series of framework deals the Pentagon has signed this year to boost munitions production.

In January, Lockheed Martin agreed to more than triple production of the Patriot Advanced Capability-3 Missile Segment Enhancement, or PAC-3 MSE, interceptor.

In March, BAE and Lockheed agreed to quadruple production of seekers for the Terminal High Altitude Area Defense, or THAAD, interceptor. A separate THAAD framework signed in January led to a June contract worth more than $35 billion for the interceptors themselves.

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.

Despite massive technological shifts, that paradigm still holds, which is why the U.S. Army and Navy have teamed up to keep systems operational — even in the extreme cold of the Arctic.

As the Department of Defense eyes greater operability in the far north, these low temperatures can wreak havoc on equipment and machinery (and toilets), with ice becoming enemy No. 1.

Which is why the Naval Facilities Engineering and Expeditionary Warfare Center, or NAVFAC EXWC, and the Cold Regions Research and Engineering Laboratory, or CRREL, began working with both branches to field a rapidly deployable Triple Container rigid-wall shelter system usable in temperatures as low as -50 degrees Fahrenheit.

The already fielded version can operate in temperatures as low as -15 degrees Fahrenheit. The team focused on different configurations of thermal wrappings, insulation and other components to ensure that parts of the kit’s components that are particularly vulnerable to cracking and freezing — hoses, valves, bladders and pumps — were able to withstand the greater threshold for cold, according to a recent Army release.

The result, per the release, far exceeded the objectives, with the TRICON-based system staying operational down to -65 degrees Fahrenheit.

Testing took place in CRREL’s New Hampshire-based Extreme Cold Chamber, a 288-square-foot cold room capable of reaching temperatures as low as -90 degrees Fahrenheit, per the release. While military units typically have to wait until the Alaskan winter reaches its peak to simulate similar conditions, the controlled environment allowed the research team to create conditions similar to those of the real world.

“Our armed forces live and operate in extremely cold and difficult conditions, so having these facilities operational is important for their physical and mental health while serving in the Arctic and other high-north environments,” said Dr. Dan Tague, a research chemist at CRREL, one of seven U.S. Army Engineer Research and Development Center laboratories.

In 2024, the DoD released its “Arctic Strategy,” citing “Major geopolitical changes are driving the need for this new strategic approach to the Arctic, including Russia’s full-scale invasion of Ukraine, the accession of Finland and Sweden to the NATO Alliance, increasing collaboration between the People’s Republic of China (PRC) and Russia, and the accelerating impacts of climate change.”

The region, according to the report, had become “a venue for strategic competition,” and a space where the United States intends to build a more persistent presence.

The latest successes with TRICORN-based systems provide, beyond the obvious comforts for personnel stationed in the Arctic — Toilets! Laundry! Showers! — an expanded operational footprint for the U.S. military as a whole, according to James Pilkington, a project manager in NAVFAC EXWC Expeditionary Technical Department.

“This extends the operational range of base camps in terms of geographic locations and durations,” said Pilkington. “In turn [it] extend[s] force posture.”

The idea: to radically reduce the sound signature of friendly troops by suppressing every weapon on a battlefield.

The contract also plunged the company into engagement with an emerging area of concern: the health dangers of toxic gases and particles blasted back into the shooter’s face when firing a suppressed weapon.

While the full extent of the risks is still being understood, SOCOM made it clear to Sig at the time of the contract that it wanted to cut down on toxicity, setting a standard that seemed unreachable.

“The requirement at the time was that they wanted a suppressed upper receiver group that produced less toxicity than an unsuppressed M4,” Josh Shoemaker, product manager for defense systems at Sig, told Military Times. “At the time the industry was all like, ‘That’s not physically possible.’ It was really a set of requirements that was defying everybody’s understanding of suppressors.”

In the years that followed, Sig would come under fire multiple times for tests that showed various suppressed weapons had too much toxic blowback. But through lengthy development and the introduction of advanced manufacturing, Shoemaker said, the company reached the ability to reduce 70% of toxic gas blowback in a suppressor.

But there’s a tradeoff, he added. Suppressors can excel at reducing noise, flash or blowback, but not all three at once. One solution the company is now proposing would offer specialized suppressors that maximize blowback reduction for training and signature masking for combat.

The idea, Shoemaker said, is that troops are most at risk from toxic gas exposure when shooting in enclosed spaces and over long periods in the same area, both of which are more likely to happen in training. On top of that, he said, training accounts for the vast majority of the rounds a soldier will ever fire.

“The Army already has this principle where they have training ammunition and go-to-war ammunition. When they go to war, they’re using a different projectile and different ammunition than they are when they’re training,” Shoemaker said. “They do this with their body armor, with their uniforms — their uniforms, when they’re training, are not all flame retardant. … Why wouldn’t we do that same thing with the suppressors?”

Early in its 10-year production contract to design the Army’s next rifle and light machine gun — a program known as Next Generation Squad Weapon — military testing officials cited concerns about how much toxic back-blast the suppressed weapons were producing. The result was a delay that pushed fielding from late 2023 into 2024.

And these problems continued to be reported as recently as last year. The Pentagon’s weapons testing branch noted in its Fiscal Year 2025 annual report that soldiers in an operational assessment “reported negative physiological effects caused by the noxious off-gassing from their weapons, as well as concerns about the extreme heat from the weapons’ suppressors after firing.”

Shoemaker said that some of this feedback was expected when comparing the previous standard rifle, an unsuppressed M4, to the new M7, which has a larger round and a more powerful discharge. But he added that the company was listening to soldiers and “actively working” to address concerns.

“Toxic fumes [are] still a very new thing, right?” Shoemaker said. “When you have a very narrow audience that you’ve been providing these products to for years, you don’t get the same feedback that you do when you’re providing to a much wider audience.”

Behind the scenes, according to Shoemaker, Sig has been close to the forefront of fume-reduction technology. The company uses a 3D printing process called Direct Metal Laser Sintering, or DMLS, to build “complex labyrinths” into their SLX and SLH suppressors designed for fume reduction.

Previously, suppressors were made with machined baffles that were welded together, one by one.

“There would have been no way to get a tool in here to cut any of these paths or direct any of that gas,” Shoemaker said of the new suppressors. “It was game-changing for the entire suppressor industry because it unlocked all of these abilities to … make these complex geometries.”

In service of developing reduced-toxicity suppressors for the Army and later the Navy, Sig acquired two specialized testing environments: the Crane box, invented at Naval Surface Warfare Center-Crane Division, Ind., to precisely measure released carbon dioxide as weapons fire in a confined space; and the Military Operations in Urban Terrain (MOUT) chamber, which now measures precise particulate amounts and concentrations of four gases: carbon monoxide, carbon dioxide, ammonia and hydrogen cyanide. Sig is the only non-military entity to possess the chambers.

While Shoemaker said the company is still seeking to make incremental improvements to the blowback reduction capabilities of existing suppressors — from, say, the current 70% reduction maximum to 75% — he also said the DMLS technology would make it easy to deliver a variety of suppressors specialized to maximize reduction of either sound, flash or fumes based on use case.

The Army has yet to ask for a mix of training suppressors and combat suppressors. But Shoemaker indicated it may emerge as a solution for a service that wants to have it all in terms of sound, flash and toxic gas reduction, and can’t practically have it all in one can.

If so, the company will be ready.

“With DMLS, [engineers] can make a new design, and we can have it and shoot it three days later,” he said.

Growing demand for air and missile defense systems amid conflicts in Ukraine and the Middle East has strained U.S. weapons stockpiles, prompting the U.S. Army to award Lockheed Martin a contract worth up to $58.6 billion in July to ramp up production of PAC-3 interceptors.

Lockheed Martin said PAC-3 Edge incorporates a new seeker, upgraded flight controls and a multi-pulse rocket motor supplied by Northrop Grumman, enhancing the interceptor’s ability to counter advanced threats, including hypersonic missiles, at longer ranges and higher altitudes.

“The cost of this would be about that of the existing PAC-3 MSE,” Tim Cahill, president of missiles and fire control at Lockheed Martin, told Reuters. “At full production, the annual rate would be about 2,000 units a year, comparable with PAC-3 MSE.”

In January, Lockheed Martin signed a seven-year framework agreement with the Pentagon to expand production of its PAC-3 missile interceptors, aiming to increase annual manufacturing capacity to 2,000 units from about 600.

Subsequently, the US Navy awarded Anduril a contract worth up to $2.9 billion to manufacture submarine components, with payments tied directly to production outcomes and the company assuming most of the execution risk, the defense startup said.

The investment and associated contract, together valued at up to $6.6 billion, come amid a broader push by the United States and its allies to expand arms production following Russia’s invasion of Ukraine and conflicts in the Middle East.

The new plant, dubbed Arsenal-2, will be situated in Baltimore County and is expected to be up and running by the end of the decade, creating 3,100 direct jobs and supporting over 11,000 indirect jobs.

Asked about the $2.9 billion government contract, Christian Brose, chief strategy officer at Anduril, said, “It’s really the government buying the results of what we’re able to produce from the facility that we’ve invested in.”

Anduril is already building out a facility in California to manufacture critical Virginia-class submarine components such as torpedo tubes, helping address urgent capacity shortfalls in the U.S. industrial base, Brose said.

The company plans to expand into producing larger submarine modules and hull sections once its Baltimore shipyard becomes operational.

Virginia-class submarines, which can travel at over 25 knots, are the Navy’s latest generation of nuclear-powered attack submarines, designed for anti-submarine warfare, land-attack strikes and surveillance missions.

General Dynamics’ Electric Boat and Huntington Ingalls Industries jointly build the submarines.

Anduril, founded in 2017 by Palmer Luckey, is a defense firm that is best known for its autonomous systems, drones and software built for the U.S. military and its allies.

The startup has, however, expanded beyond drones into maritime and undersea systems and command-and-control software designed to connect military sensors, weapons and other systems.

The new plant comes after Anduril’s $1 billion Arsenal-1 facility in Ohio that began producing autonomous combat drones this year.

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 service’s Direct Reporting Portfolio Manager for Robotic and Autonomous Systems and Defense Innovation Unit selected BeeX, BlackSea Technologies and Vatn Systems after they successfully completed the Mine Countermeasure Modernization Prize Challenge, according to a recent release.

“Through the partnership with DIU, in less than four months we were able to quickly move from open call to on-water testing, to contracting options and initial operational planning,” George Saroch, DRPM RAS program manager for mine warfare, said in the announcement.

DIU launched the competition on May 29, offering $200,000 to companies selected to participate and up to $3 million to the winning company.

Out of 80 applicants, only 11 companies were chosen to compete.

The competition asked companies to tackle near-surface mine neutralization, bottom mine detection and bottom mine neutralization.

Those that were awarded the prize proved that their technology was capable of locating, identifying and destroying underwater mine threats, the Navy said.

The Navy has faced mine warfare during the Iran war, with Iran placing sea mines along the Strait of Hormuz.

The suite of options the service has to address the threat, however, remains limited.

Four Avenger-class minesweepers were decommissioned in 2025 before the war, leaving only four left in the fleet, all of which are stationed in Sasebo, Japan.

The Navy also has three Independence-class littoral combat ships, previously stationed in Bahrain, that each come equipped with a mine countermeasures mission package that employs a combination of helicopters, sonar, acoustic and electromagnetic generators and autonomous vessels to minesweep and minehunt.

But several retired U.S. Navy captains who deployed on minesweepers told Military Times in March that those ships were not as effective as the minesweepers due to technological issues.

The Pentagon’s weapons testing office DOT&E found that pieces of the mine countermeasures technology on the LCS with the MCM package were “not operationally suitable” and could “not support sustained mine sweeping operations.”

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.