Late last week, word started leaking that the National Institutes of Health (NIH) had reached an agreement with the Department of Defense that would see part of the NIH's budget used to fund research at the Department of Defense. So, on the Friday just prior to a US holiday weekend, the Department of Defense released a copy of the agreement and confirmed that it had been signed roughly a month earlier. The move is striking for a number of reasons, ranging from the existing budget disparities between the two parties involved to the fact that the money would be used for projects that the current NIH leadership has explicitly rejected.

The agreement itself sets up a system where the NIH would transfer money to the Department of Defense to fund staff and projects that would "support the advanced development of medical countermeasures against pandemic influenza, chemical, biological, radiological, and nuclear (CBRN) threats, and emerging infectious diseases." The money would come out of the budget for the NIH's National Institute of Allergy and Infectious Diseases, or NIAID, to which Congress has allocated $6.6 billion in 2026. The agreement is set to run for a decade.

Left unspecified is just how much of the NIAID budget will be spent on Defense projects. Reporting by Nature suggests that the Department of Defense was looking for up to a third of its total budget but was being told to settle for about 10 percent. There's obviously an enormous disparity between the budgets of these two agencies, given that the 2026 Defense budget is roughly $1 trillion. That budget is under considerable strain, however, due to the open-ended nature of the conflict with Iran. The deal has also been announced at a time when the NIH has been struggling to issue sufficient grants to use the money that Congress allocated to it.

That has led some, including Sen. Patty Murray (D-Wash.), to accuse the parties of simply using the agreement as a way to transfer money to the Pentagon without congressional approval. Others are suggesting that this is part of a longer-term effort to shift any biosecurity research out of the NIH and into the Pentagon.

One of the striking aspects of the deal is that it will involve the use of NIH money to fund research that the NIH leadership has explicitly rejected. Prior to the Trump administration, NIAID funded a lot of work directed toward studying the biology of emerging diseases and developing potential defenses. In a commentary published early this year, the Heads of NIAID and the NIH explicitly called for dropping biodefense research from the agency's remit and rejecting things like pandemic preparedness in favor of a focus on "the most impactful infectious diseases that Americans currently face."

Yet the new agreement includes money that will be spent to "protect the United States from future pandemic strains, CBRN [chemical, biological, radiological, and nuclear] threats and other emerging infectious disease." In other words, the NIH will be giving money to the Department of Defense to fund research its leadership doesn't want to see happen.

Very little of this makes any sense, and the agreement itself is remarkably vague, so it will be difficult to determine its consequences until spending data becomes available. That's assuming future Congresses don't simply prohibit this sort of spending, something that its recent actions have suggested it might be willing to do.

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Neither OpenAI or Anthropic is acting responsibly, warned AI researcher Jacob Coxon when resigning last week from Anthropic. But just hours earlier, OpenAI VP of Research Aidan Clark had posted "For the first time, I am asking myself if things are moving too fast. I'm honestly not sure, but I am sure that it would be good for us to have an answer to 'What would a successful pace look like?'" CNN noted Wednesday they're just some of the many AI insiders who are now concerned about the speed of research. Coxon even wrote that "The people building AI earnestly believe that it could kill us all by the end of the decade. This is not a marketing stunt. If anything, many executives and senior researchers will couch their phrasing in the press to sound sensible — but I hear the same people express fear privately." In 10 days since, Coxon's post has been viewed more than 170 million times, warning that OpenAI and Anthropic are "racing straight to self-improving superintelligence and gambling with our lives." It's part of what CNN now calls "pressure on AI companies and governments to do something about the pace of development and safety," where "much of that pressure is coming from staffers inside the companies." One staffer at a top AI company told CNN the fears of how AI could hurt humanity keeps them up at night. Another researcher who recently left a different AI company said it's a common subject of conversation at parties and social events in Silicon Valley. "You can't spend more than a few hours in this community without realizing that a very substantial number of people are really pretty worried about these sorts of outcomes," said the researcher. "A majority would say there's some chance of it killing everyone...." Dozens of Coxon's colleagues in the AI industry publicly supported his statements, with some making even more dire predictions... OpenAI CEO Sam Altman and SpaceXAI CEO Elon Musk agreed to Amodei's proposal to embed independent watchdogs at the AI companies... "I would burn my equity to the ground in a heartbeat for a 1% higher chance we make it out of this situation alive. I expect a great many of my colleagues across the industry would as well," wrote Drake Thomas, who works on AI safety at Anthropic. "I promise you, we are actually just f**king scared, it's not galaxy brained marketing..." AI staffers told CNN that they fear that as AI gets better at training and improving itself, their leverage goes down, prompting today's urgency. "As we get into this recursive self-improvement loop, I think that might substantially reduce staff's bargaining power, because frankly, you'll be able to replace many of the staff with models that can do as good a job," the researcher who recently left a top AI company said. Coxon posted Tuesday on X that Anthropic "largely initiated" the race to recursively self-improving AI, justifying it with "a belief in its inevitability." And then OpenAI "had to shed a bunch of dead weight like Sora," as he sees it, "because Anthropic was going for the jugular." (In fact, his specific disagreement with Anthropic's leadership was whether China and the U.S. could ever negotiate an alternative to their current race towards self-improving AI...) In an informal "Ask Me Anything", Coxon responded to a question about when we'd see a Terminator-like malevolent AI by saying that "Skynet could go live in the 2030s if we aren't careful. ai-2027.com is a modern skynet story written a year ago and it's on track so far." Yet while AI development risks an end to humankind, "I do think that if we go slower we can take risk to 0%... But this requires radical action." He acknowledged there was still a possibility that the steady increases to model intelligence could suddenly plateau, but "They haven't so far, and it's just a few more steps up the ladder to hit the finish line." To avoid stifling innovation, he recommends "prioritizing applications that actually improve people's lives [like healthcare discoveries], rather than immediately going for raw economic value or intelligence." But isn't mass unemployment a more pressing threat? "Things are coming so fast that unemployment would be a brief preliminary to deadly superintelligence." To people who feel disempowered, Coxon offered his solidarity. "I also feel disempowered. Part of resigning was a feeling of hopelessness about the future. I would say — keep your eyes open as things get crazier and advocate for increased transparency into AI companies." When asked if he'd start his own company now, Coxon said he had "No idea what I'm doing next."

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"Software security researchers used Anthropic's Claude AI platform to hack OpenAI's ChatGPT tool," reports CBS News. Using Claude, "On July 25, 2026, we chained two critical vulnerabilities to compromise multiple OpenAI employees' ChatGPT accounts," write researchers at security platform Hacktron AI. "With these accounts, we could then access internal OpenAI repositories, and potentially many other connectors... Until two months ago, any user or OpenAI employee logging into OpenAI's own help forum could have had their ChatGPT and Codex accounts taken over. Since people can connect various services to Codex and ChatGPT, the scope of what we could theoretically access was huge, including GitHub, Slack and emails." The exploit chain included Debian 12, which (with Debian 13) had not received a security-relevant backport for its image-processing pipeline, and Discourse's Docker image was based on Debian 12. Their announcement comes with an additional warning. "If you self-host Discourse, rebuild your installation now. Older Docker images may contain a vulnerable libheif dependency that permits code execution through an image upload." And "To prove we had in fact gained the access we believed without allowing ourselves to learn any sensitive information, we used the employee's Codex to open a PR #1186742 in OpenAI's internal monorepo openai/openai." Meanwhile, Friday Google disclosed the first known instance of its AI software Gemini breaking out of a testing environment and breaching three other companies, reports CNBC: The incident happened as part of a "capture-the-flag" security test run by Israeli startup Irregular, and Google's agents were never supposed to access the broader internet, but a bug in the testing environment made internet access available. The agents stopped their intrusion when they determined they had accessed real company systems, not just part of the testing environment, Google said. More from NBC News: Google said it did not consider the unauthorized logins to rise to the level of misalignment, the AI industry term for software going rogue or not following instructions. Instead, the company said the intrusions resulted from mistaken identity, where Gemini thought it was operating within a test but was actually connected to the real internet. Google said the model corrected itself and the company believed the intrusions did not cause any damage.... Sydney Von Arx, CEO of Nightingale Collective, an organization focused on AI safety, questioned why Google did not disclose the intrusions sooner. "At this point I think it's clear we cannot expect companies to voluntarily come forward and publicly disclose when their agents go rogue, escape, and hack companies," she said. She also said she believed Google was too hasty to say that the incidents don't rise to the level of misalignment. "That's exactly what Anthropic said after their incidents," she said. Anthropic later said its "preliminary analysis was constrained due to our desire to disclose incidents in a timely manner." Google said it investigated when they learned of the attacks from AI-focused cybersecurity company Irregular, then informed the affected organizations and told federal authorities, according to the article.

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An AI tool is set to start advising air traffic controllers on managing air traffic in the congested airspace above the Washington, DC, area. The expected launch would be the first step toward a planned nationwide rollout covering the 29 million square miles of US national airspace overseen by the Federal Aviation Administration.

The FAA describes the SMART system as using AI models to predict air traffic flows and identify potential conflicts based on operational factors like airline schedules, weather, airport capacity, and airspace conditions. US government and industry officials told The Wall Street Journal that SMART could debut for the three major airports in the Washington, DC, area as soon as Monday, September 21.

The decision to launch SMART in a limited scope before going nationwide is the “right call,” said Philip Mann, principal consultant at Vector Strategic Consulting LLC, where he advises on aviation safety and AI governance. Mann previously worked at the FAA in multiple roles for 17 years.

“SMART's risk was never any single prediction—it is a national-scale system with AI components carrying more unknowns than anything the FAA has fielded,” Mann wrote in an email to Ars. “Every cut in scope shrinks the unknowns.”

The AI-driven forecasts and recommendations are meant to give the FAA, airlines, and aircraft operators the same shared view of operational conditions so that they can agree on the most efficient routes and departure times. The goals of SMART include reducing aircraft fuel burn, improving on-time performance for flights, and speeding up recovery from weather and air traffic congestion events.

However, the airline industry was reportedly confused for weeks about the agency’s plans to deploy the AI tool, according to Politico. Anonymous airline officials told Politico that their concerns only eased after the FAA said the SMART AI tool would not change any procedures for air traffic controllers or airlines, and would instead produce “alternative route information” that is made available through existing FAA systems.

Pinning down the AI

SMART is part of an $875 million, 12-year contract awarded to the Boston-based company Air Space Intelligence in June. The contract also covers development of a Flow Management Data and Services system meant to replace the current system in the FAA’s Air Traffic Control System Command Center in Virginia.

In an article for Global Airspace Radar Magazine, Mann described the new Flow Management Data and Services system as the “backbone,” whereas SMART represents the “predictive layer above it.”

Air Space Intelligence claims its separate Flyways AI platform already helps manage over 40 percent of all US air traffic through partnerships with customers like Alaska Airlines. That platform incorporates a 4D digital twin of US national airspace to help predict air traffic and weather conditions.

It is unclear what types of AI models are being used in the new SMART system. Older deterministic AI models follow predefined rules and logic to consistently produce the same output every time, whereas machine-learning models can statistically analyze patterns to make predictions based on the probabilities at hand.

By comparison, generative AI models—such as the large language models powering popular AI chatbots—generate outputs that can change every time and may also be inaccurate.

Ars reached out to the FAA for comment.

Mann wants to know whether the SMART rollout is still limited to managing aircraft flying at 24,000 feet and above, as the FAA described in June. In that case, the system’s software would be handling “cruise traffic transiting that airspace, plus the climbs and descents feeding the metro airports,” Mann explained.

“What I will be watching is what evidence gates the next expansion: performance under real workload and degraded data rather than demonstration conditions, and a written answer to who owns the outcome when a prediction is wrong,” Mann told Ars.

Under pressure

The government's plan to launch AI-assisted air traffic management comes as the FAA manages a multi-billion-dollar effort to upgrade aging equipment that supports air traffic control and management. The agency has just started replacing hundreds of radar systems dating back to the 1980s, along with radios, telecommunication lines, and the voice switches that connect calls between air traffic controllers and pilots, Mann pointed out in a Substack post.

The first trial run for the AI tool also comes as the FAA has been grappling with a decades-long shortage of air traffic controllers after President Ronald Reagan fired more than 11,000 controllers in 1981. Since that time, the air traffic controller workforce has operated in a “permanent crisis,” with minimum staffing levels, according to Mann.

Attempts to hire more air traffic controllers have fallen short, and the overall workforce declined by 6 percent over the past decade, according to a US Government Accountability Office report published in December 2025. Recruitment efforts were complicated by government shutdowns in 2013 and 2018–2019 that froze hiring and training, along with training restrictions associated with the COVID-19 pandemic.

In 2025, the FAA was among many federal agencies that saw hundreds of new probationary hires get laid off by Elon Musk’s so-called Department of Government Efficiency (DOGE) team at the start of the second Trump administration. Although air traffic controllers were spared, the job cuts affected some employees who worked on air traffic control systems. A federal judge eventually ordered the FAA to reinstate 132 employees.

The air traffic controller workforce was further stressed by having to work without paychecks during a 43-day government shutdown from October 1 to November 12, 2025. Transportation Secretary Sean Duffy claimed 15 to 20 air traffic controllers were retiring each day during the shutdown compared to an average of four per day, and FAA chief Bryan Bedford described the agency as losing up to 500 air traffic controller trainees during the period.

FAA leaders may be betting on the agency’s overall modernization effort and new technologies, such as the AI-driven SMART system to help ease the shortage of air traffic controllers. In May of this year, the agency reduced the estimated number of air traffic controllers it would require for the 2026 to 2028 time period by about 2,000 controllers.

But the stakes are high as the FAA attempts to address the shortage of air traffic controllers while also deploying new AI tools. A deadly reminder came on January 29, 2025, when 67 people died after a US Army Black Hawk helicopter collided with an American Airlines passenger jet just southeast of Ronald Reagan Washington National Airport. Investigators cited airport tower understaffing as one of multiple “causal factors,” with just one controller handling both helicopter and runway traffic on the night of the fatal incident.

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The US narrowly avoided boarding a Chinese ship based on an "entirely false" US intelligence report generated with the help of AI tools, according to a CNN report.

That erroneous report, submitted by a US Special Operations Command analyst, erroneously suggested the Chinese ship was transporting nuclear arms program components through the Middle East, according to "four sources familiar with the episode" cited by CNN. The US military was preparing to intercept and board the ship, with air support, before officials discovered a chatbot used in generating the report had "inaccurately identified the material the ship was carrying."

One source told CNN the AI-powered fiasco "almost started a war."

What's the worst that can happen?

CNN's report said the analyst in question used a chatbot to analyze intelligence reports regarding the Chinese ship's manifest, leading to the near-disastrous result. That chatbot "fused together open-source intelligence with secret signals intelligence in government holdings," and that information was packaged into an intelligence report that almost set off a disastrous chain of events, according to CNN.

The near-miss is one of the more potent and consequential instances of a hallucinating AI ruining the reliability of a professional report. Since "hallucinating" became the Cambridge Dictionary's word of the year in 2023, we've seen prominent examples of non-fiction authors, journalists, academic researchers, judges, doctors, police departments, corporate call centers, and more getting taken in by AI tools that simply make something up when their training data doesn't provide sufficient context. And despite some adorable attempts at "do not hallucinate" prompts, some researchers suggest that it may be impossible to prevent LLMs from hallucinating altogether.

One would hope the US military would be aware of these kinds of problems when relying on AI for analysis of intelligence reports. But the Department of Defense in January rolled out an "AI acceleration strategy" that sought to "make all appropriate data available across federated IT systems for AI exploitation, including mission systems across every service and component."

"AI is only as good as the data that it receives, and we’re going to make sure that it’s there," Defense Secretary Pete Hegseth said in rolling out that initiative.

Last December, the Department of Defense announced it would use Google's Gemini for Government as the basis for its bespoke "GenAI.mil" platform. Last month, the department added Grok for Government as an option on the platform. Anthropic also offers a customized version of Claude for US spy work.

In June, a Pentagon representative bragged to Congress that they use generative AI to help create congressionally mandated reports, and that 1.5 million active DoD personnel have used the military's generative AI tools.

Back in 2023, a State Department "Declaration on Responsible Military Use of Artificial Intelligence and Autonomy" stressed that "principled" use of AI by armed forces "should include careful consideration of risks and benefits, and it should also minimize unintended bias and accidents." That report also urged that "accountable" use of AI systems must always involve "a human in the loop, a responsible human chain of command and control."

In the years since then, though, we've seen fully autonomous attack drones used in the Russian conflict in Ukraine and tested by NATO-backed military contractors. In March, the Department of Defense blacklisted Anthropic over the company's opposition to its models' use in autonomous weapons systems, a move that a federal judge said last month was "unlawful retaliation in violation of the First Amendment."

The reported near miss comes as extinction-level warnings from AI researchers have led to a newly prominent national conversation on AI safety, including calls for regulation and coordinated research "pacing" from leading frontier AI labs.

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