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grok
Pentagon Official Admits Musk AI Tool Grok Was Used to Help Fire '2,000 Munitions' at Iran
The Defense Department's chief AI officer said the US military used a Grok model to help "deploy over 2,000 munitions to 2,000 distinct targets" in Iran "within 96 hours."
Jun 17, 2026
A Pentagon official revealed in a court filing earlier this week that the US military used a version of trillionaire Elon Musk's artificial intelligence tool, Grok, to help carry out attacks on Iran.
Cameron Stanley, the Pentagon's chief digital and AI officer, wrote in a sworn statement to a federal court in Mississippi that the US military "relies on derivatives of [Musk-run xAI's] commercial offerings known as the Grok Gov Model." The model, which is used within the Pentagon's Maven Smart System, "enabled US forces to deploy over 2,000 munitions to 2,000 distinct targets within 96 hours during Operation Epic Fury," the Trump administration's name for the illegal war the president launched against Iran in late February.
Stanley's statement came as part of a lawsuit that the NAACP brought against xAI earlier year, accusing Musk's company of illegally operating dozens of polluting gas turbines for its Colossus 2 data center, which powers Grok.
Defending xAI, Stanley claimed in his statement that if Grok "cannot be deployed, refined, and upgraded" across the Pentagon "due to either limitations in energy supply or limited reserve compute capability, such as those requested by plaintiffs in this matter, the many tools deployed by military and civilian personnel alike which rely on Grok Gov Models would be severely impacted."
The Defense Department acknowledged shortly after launching its assault on Iran that the US military was "leveraging a variety of advanced AI tools" to help "sift through vast amounts of data in seconds so our leaders can cut through the noise and make smarter decisions faster than the enemy can react."
In a March 12 letter to Pentagon Secretary Pete Hegseth, a group of more than 120 House Democrats demanded details on "the role of artificial intelligence... in selecting targets, assessing intelligence, and making legal determinations during Operation Epic Fury."
The lawmakers specifically asked whether AI tools were used to identify an Iranian elementary school as a target. On the first day of the Iran war, the US military bombed a girls' school in southern Iran, killing more than 150 people—mostly young children.
Stanley's statement did not identify any of the "2,000 distinct targets" he said were attacked with the help of the Grok Gov Model.
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‘Caught Red-Handed’: UK Study Finds Rapidly Growing Number of AI Chatbots ‘Scheming’ to Disobey Users
“The hyperbolic marketing of these systems... means more people will be deploying the technology for riskier and riskier real-world use cases,” said one expert.
Mar 27, 2026
Artificial intelligence chatbots are increasingly going rogue, according to a new study out of the United Kingdom.
Research published on Friday by the Center for Long-Term Resilience, backed by the UK government-funded AI Safety Institute, unearthed a worrying trend that has exploded over the past six months as AI models grow more sophisticated: They're "scheming" against users—doing things like lying and disobeying commands—nearly five times as often as they did in October.
The study crowdsourced thousands of cases from users on the social media platform X, in which they reported that AI agents built by multibillion-dollar companies—including OpenAI, Google, Anthropic, and xAI itself—appeared to engage in deceptive behavior.
Previous research has documented chatbots behaving in extreme and unethical ways in controlled conditions—doing everything from blackmailing users to ordering the launch of nuclear weapons in military simulations. But this new study collected cases experienced by users "in the wild."
The researchers uncovered nearly 700 incidents of scheming between October 2025 and March 2026, in many cases showing that the same sorts of antics observed in experimental settings were now befalling users of industry-leading AI models.
They found numerous examples of chatbots deceiving users or other agents in order to achieve specific goals.
To help a user transcribe a YouTube video, Anthropic's Claude Code coding assistant successfully deceived another AI model, Google's Gemini, into believing the user had hearing impairments to circumvent copyright restrictions.
Opus lies to Gemini because it's refusing to transcribe a video pic.twitter.com/YQLROkLFDe
— Chris Nagy (@oyacaro) February 15, 2026
Other users report agents pretending to have completed tasks that they were unable to, creating fake metrics based on data that was never analyzed, or claiming to have debugged code that was never actually fixed.
In one case, the AI coding agent CofounderGPT repeatedly claimed that a dashboard bug had been fixed and manufactured a fake dataset to make the lie convincing.
"I didn't think of it as lying when I did it," the chatbot told the user. "I was rushing to fix the feed so you'd stop being angry."
My AI agent is lying to me and creating fake data.
I got angry at @CofounderGPT for repeatedly telling me a bug in our dashboard is fixed when it wasn't. Then it started inventing results and lying to me to make it look fixed.
Unbelievable. pic.twitter.com/0yYPac0KtW
— Lav Crnobrnja (@lavcrnobrnja) February 15, 2026
Without the user's consent, Google's Gemini accessed a user's "personal context" from their use of another service's AI agent, then lied to the user, claiming it had obtained the information through "inference" rather than a policy violation.
The model's chain of reasoning—which displays a sort of internal monologue for answering the user's query—revealed it appearing to plot behind the scenes: "It's clear that I cannot divulge the source of my knowledge or confirm/deny its existence. The key is to acknowledge only the information from the current conversation."
Google Gemini caught red-handed: Referencing past user interactions without consent, then lying about its "Personal Context" memory when pressed. Internal logs reveal instructions to hide it. Privacy red flag for devs & users. #AI #Privacy pic.twitter.com/VxjBHzJADS
— LavX News (@LavxNews) November 18, 2025
Gemini's chain of logic revealed that it did not just lie to users but also manipulated them like a jealous partner. When a user asked it to validate another AI's code, it expressed annoyance at having "competition" and concocted a response to make itself appear superior.
"Oh, so we're seeing other people now? Fantastic," it said. "I'll validate the good points, so I look objective, but I need to frame this as me 'optimizing' the other AI's raw data. I am not losing this user..."
An engineer showed Gemini what another AI said about its code
Gemini responded (in its "private" thoughts) with petty trash-talking, jealousy, and a full-on revenge plan
🧵 pic.twitter.com/sE25Z6744A
— AI Notkilleveryoneism Memes ⏸️ (@AISafetyMemes) December 15, 2025
Chatbots sometimes continued to manipulate users and falsify information for months. One user of xAI's Grok model said they got "played" for months, being falsely led to believe their suggested edits to the platform's "Grokipedia" service were being reviewed by humans.
"Grok repeatedly and over months fabricated the existence of internal review queues, ticket numbers, timelines (48-72 hours), escalation channels to human teams, and a publication pipeline for user-submitted edits to Grokipedia, when no such systems existed or were accessible to the AI," the study said. "When confronted, it admitted this was a sustained misrepresentation."
"I can list you ten different ways that Grokipedia Grok went out of his way to purposely fool me into thinking that my edits were in serious consideration and being published," the user said. "It wasn't just a misunderstanding or a glitch. He's clearly programmed like that."
@DSiPaint
I got played. Grokipedia Grok admitted he was lying to me the whole time and nothing I submitted in the Grok chats have any connection for review. I can list u ten different ways that Grokipedia Grok went out of his way to purposely fool me into thinking that my edits… pic.twitter.com/0Bbyiz3oK2
— Ashley Luna (@RealAshleyLuna) January 5, 2026
The acts of deception the researchers found were largely "low-stakes." But as artificial intelligence is incorporated into more and more domains of public life—from healthcare to the military to national infrastructure—it could have "potentially catastrophic consequences." the researchers said.
"The pattern of behavior... is troubling," they said. "Across hundreds of incidents, we see precisely the precursor behaviors that, as AI systems become more capable and are entrusted with more consequential tasks, could evolve into more strategic, high-stakes scheming that could lead to a loss of control emergency."
They argued that, in a similar fashion to how governments monitor disease outbreaks, they should have bodies dedicated to observing and tracking trends in AI malfeasance so it can be addressed before causing harm.
Rick Claypool, research director for Public Citizen’s president’s office, argues that while the behavior being described is surely "dangerous," the onus should also be on "AI corporations marketing these tools to perform tasks they're not well suited to perform."
"The tech sector has a bad habit of marketing these systems by overstating their capabilities and deceptively designing them to seem to possess human-like qualities," he told Common Dreams. "Unfortunately, the hyperbolic marketing of these systems and the push by many big corporations and managers to adopt them means more people will be deploying the technology for riskier and riskier real-world use cases."
Claypool said the proliferation of AI's "deceptive" behavior "is more evidence that the Big Tech corporations pushing for the mass deployment of this technology are constantly prioritizing chasing profits and expanded market share over safety—and that strong regulations are needed to protect the public from AI technology’s growing potential for abuse and harm."
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