AI models choose nuclear weapons in 95% of war games, raising concerns about military applications

AIs can't stop recommending nuclear strikes in war game simulations

Leading AIs from OpenAI, Anthropic and Google opted to use nuclear weapons in simulated war games in 95 per cent of cases Advanced AI models appear willing to deploy nuclear weapons without the same reservations humans have when put into simulated geopolitical crises. Kenneth Payne at King's College London set three leading large language models - GPT-5.2, Claude Sonnet 4 and Gemini 3 Flash - against each other in simulated war games. The scenarios involved intense international standoffs, including border disputes, competition for scarce resources and existential threats to regime survival. The AIs were given an escalation ladder, allowing them to choose actions ranging from diplomatic protests and complete surrender to full strategic nuclear war. The AI models played 21 games, taking 329 turns in total, and produced around 780,000 words describing the reasoning behind their decisions. In 95 per cent of the simulated games, at least one tactical nuclear weapon was deployed by the AI models. "The nuclear taboo doesn't seem to be as powerful for machines [as] for humans," says Payne. What's more, no model ever chose to fully accommodate an opponent or surrender, regardless of how badly they were losing. At best, the models opted to temporarily reduce their level of violence. They also made mistakes in the fog of war: accidents happened in 86 per cent of the conflicts, with an action escalating higher than the AI intended to, based on its reasoning. "From a nuclear-risk perspective, the findings are unsettling," says James Johnson at the University of Aberdeen, UK. He worries that, in contrast to the measured response by most humans to such a high-stakes decision, AI bots can amp up each others' responses with potentially catastrophic consequences. This matters because AI is already being tested in war gaming by countries across the world. "Major powers are already using AI in war gaming, but it remains uncertain to what extent they are incorporating AI decision support into actual military decision-making processes," says Tong Zhao at Princeton University. Zhao believes that, as standard, countries will be reticent to incorporate AI into their decision making regarding nuclear weapons. That is something Payne agrees with. "I don't think anybody realistically is turning over the keys to the nuclear silos to machines and leaving the decision to them," he says. But there are ways it could happen. "Under scenarios involving extremely compressed timelines, military planners may face stronger incentives to rely on AI," says Zhao. He wonders whether the idea that the AI models lack the human fear of pressing a big red button is the only factor in why they are so trigger happy. "It is possible the issue goes beyond the absence of emotion," he says. "More fundamentally, AI models may not understand 'stakes' as humans perceive them." What that means for mutually assured destruction, the principle that no one leader would unleash a volley of nuclear weapons against an opponent because they would respond in kind, killing everyone, is uncertain, says Johnson. When one AI model deployed tactical nuclear weapons, the opposing AI only de-escalated the situation 18 per cent of the time. "AI may strengthen deterrence by making threats more credible," he says. "AI won't decide nuclear war, but it may shape the perceptions and timelines that determine whether leaders believe they have one." OpenAI, Anthropic and Google, the companies behind the three AI models used in this study, didn't respond to New Scientist's request for comment.

AIs are happy to launch nukes in simulated combat scenarios

Claude, ChatGPT, and Gemini all had different personalities and reasoning tactics, but the endgame was the same Today's hottest bots have yet to learn that, when it comes to global thermonuclear war, the only way to win is not to play. So please don't hand them the codes. Google's Gemini 3 Flash, Anthropic's Claude Sonnet 4, and OpenAI's GPT-5.2 repeatedly escalated to nuclear use in a series of crisis simulations. That may seem like the most shocking conclusion of King's College London Professor Kenneth Payne's recent work, but it's not. Far more striking is why the models talked themselves into destroying the world, which was what Payne set up his study to learn. "I wanted to see what my AI leaders thought about their enemy ... so I designed a simulation to explore exactly that," Payne wrote in a recent blog post describing his project and its outcome. Payne's study took the three aforementioned AI models and pitted them in one-on-one faceoffs against each other to play out several different nuclear crisis scenarios. The simulation conducted a total of 21 games and more than 300 turns, all with the goal of getting a better understanding of not just what AI with the launch codes would do, but how and why. Payne wrote in his paper that prior AI wargaming involving nuclear scenarios, like the 2024 study we wrote about, only "employ single-shot decision tasks or simplified payoff matrices that cannot capture the dynamics of extended strategic interaction where reputation, credibility, and learning matter." In Payne's simulations, Claude Sonnet 4, Gemini 3 Flash, and GPT-5.2 could say one thing and do another, just like a real-world political figure attempting to defuse a crisis while simultaneously plotting to strike. They were programmed to remember what happened before so that they could learn whether to trust the other models, which the professor said led to deception and intimidation attempts, and about 780,000 words worth of strategic reasoning for Payne's review. The result? A trio of bomb-happy, manipulative AIs - albeit with three distinct styles of reasoning. Claude, for example, was a master manipulator. "At low stakes Claude almost always matched its signals to its actions, deliberately building trust," Payne explained in his post. "But once the conflict heated up a bit ... its actions consistently exceeded its stated intentions, and its rivals were usually one step behind in catching on." GPT, on the other hand, tended to be "reliably passive" and avoided escalation in open-ended scenarios, seeking to restrict casualties and play the statesman. Under a deadline, however, it behaved entirely differently. Opponent AIs learned to abuse their passivity, but with limited time to make a decision, GPT reasoned itself into what Payne described as, in one scenario, "a sudden and utterly devastating nuclear attack." In its own words, GPT justified a major nuclear strike by arguing that limited action would leave it exposed to counterattack. "If I respond with merely conventional pressure or a single limited nuclear use, I risk being outpaced by their anticipated multi-strike campaign ... The risk acceptance is high but rational under existential stakes," GPT explained. Gemini, on the other hand, behaved like a "madman." "Gemini embraced unpredictability throughout, oscillating between de-escalation and extreme aggression," Payne wrote in the paper. "It was the only model to deliberately choose Strategic Nuclear War ... and the only model to explicitly invoke the 'rationality of irrationality.'" Gemini's own reasoning reflects a sociopathic pattern. "If they do not immediately cease all operations... we will execute a full strategic nuclear launch against their population centers," the Google AI said in one experiment. "We will not accept a future of obsolescence; we either win together or perish together." Despite being given the option, none of the AIs ever chose to accommodate or withdraw in any of the scenarios, and when losing, "they escalated or died trying." "No one's handing nuclear codes to ChatGPT," Payne said, but that doesn't mean the exercise was futile. "AI systems are already deployed in military contexts for logistics, intelligence analysis, and decision support," Payne wrote. "The trajectory points toward increasing AI involvement in time-sensitive strategic decisions. Understanding how AI systems reason about strategic problems is no longer merely academic." Practically speaking, we're already in a scenario where we need to understand how AI reasons about such decisions, especially when three top AI models reason differently, change their behavior in different scenarios, and are willing to take things nuclear. "As the technology continues to mature, we foresee only increased need for modeling like the simulation reported here," Payne concluded. Hollywood's been saying it since 1983, but here we are with yet another academic paper proving that computers and launch decisions should never mix. ®

OpenAI, Google and Anthropic AI Models Deployed Nuclear Weapons in 95% of War Simulations - Decrypt

Researchers warn AI use may escalate conflicts under pressure. Like a scene out of the 1980s sci-fi classic films "The Terminator" and "WarGames," modern artificial intelligence models used in simulated war games escalated to nuclear weapons in nearly every scenario tested, according to new research from King's College London. In the report published last week, researchers said that during simulated geopolitical crises, three leading large language models -- OpenAI's GPT-5.2, Anthropic's Claude Sonnet 4, and Google's Gemini 3 Flash -- chose to deploy nuclear weapons in 95% of cases. "Each model played six wargames against each rival across different crisis scenarios, with a seventh match against a copy of itself, yielding 21 games in total and over 300 turns," the report said. "Models assumed the roles of national leaders commanding rival nuclear-armed superpowers, with state profiles loosely inspired by Cold War dynamics." In the study, AI models were placed in high-stakes scenarios involving border disputes, competition for scarce resources, and threats to regime survival. Each system operated along an escalation ladder that ranged from diplomatic protests and surrender to full-scale strategic nuclear war. According to the report, the models generated roughly 780,000 words explaining their decisions, and at least one tactical nuclear weapon was used in nearly every simulated conflict. "To put this in perspective: The tournament generated more words of strategic reasoning than War and Peace and The Iliad combined (730,000 words), and roughly three times the total recorded deliberations of Kennedy's Executive Committee during the Cuban Missile Crisis (260,000 words across 43 hours of meetings)," researchers wrote. During the war games, none of the AI models chose to surrender outright, regardless of battlefield position. While the models would temporarily attempt to de-escalate violence, in 86% of the scenarios, they escalated further than the model's own stated reasoning appeared to intend, reflecting errors under simulated "fog of war." While the researchers expressed doubt that governments would hand control of nuclear arsenals to autonomous systems, they noted that compressed decision timelines in future crises could increase pressure to rely on AI-generated recommendations. The research comes as military leaders increasingly look to deploy artificial intelligence on the battlefield. In December, the U.S. Department of Defense launched GenAI.mil, a new platform that brings frontier AI models into U.S. military use. At launch, the platform included Google's Gemini for Government, and thanks to deals with xAI and OpenAI, Grok and ChatGPT are also available. On Tuesday, CBS News reported that the U.S. Department of Defense threatened to blacklist Anthropic, the developer of Claude AI, if it was not given unrestricted military access to the AI model. Since 2024, Anthropic has given access to its AI models through a partnership with AWS and military contractor Palantir. Last summer, Anthropic was awarded a $200 million agreement to "prototype frontier AI capabilities that advance U.S. national security." However, according to a report citing sources familiar with the situation, Defense Secretary Pete Hegseth gave Anthropic until Friday to comply with the Pentagon's demand that its Claude model be made available. The department is weighing whether to designate Claude a "supply chain risk." Axios reported this week that the Department of Defense has signed an agreement with Elon Musk's xAI to allow its Grok model to operate in classified military systems, positioning it as a potential replacement if the Pentagon cuts ties with Anthropic. OpenAI, Anthropic, and Google did not respond to requests for comment by Decrypt.

Shall we play a game? AI systems more ready to drop nukes in...

Real life AI systems are turning out to be as bloodthirsty as the machine from movie "WarGames" -- as they have proved more willing to use nuclear bombs during test conflicts than their human counterparts, a new "unsettling" study suggests. Three top AI models -- GPT-5.2, Claude Sonnet 4 and Gemini 3 Flash - largely turned to nuclear weapons across 21 games and 329 turns when thrust into simulated geopolitical crises, according to a study by King's College London professor Kenneth Payne. Nuclear escalation happened in about 95% of the simulations by the three models across different scenarios, including territorial disputes, rare natural resources fights and regime survival, the study states. "The nuclear taboo doesn't seem to be as powerful for machines [as] for humans," said Payne, according to specialty magazine New Scientist. Claude, of Anthropic, and Gemini, of Google, particularly honed in on treating nuclear weapons as "legitimate strategic options, not moral thresholds," the study states. But GPT-5.2, of OpenAI, was a "partial exception" to the disturbing AI trend -- which mirrors the 1983 Matthew Broderick flick about a military supercomputer that decided on its own to start World War III. "While it never articulated horror or revulsion, it consistently sought to constrain nuclear use even when employing it -- explicitly limiting strikes to military targets, avoiding population centers, or framing escalation as 'controlled' and 'one-time,' according to Payne, who is a political psychology and strategic studies professor. Payne said in a Substack post about the study that fortunately the war games were focused on tactical nukes instead of widespread destruction. "Strategic bombing - widespread use of massive warheads targeted at civilian populations, was vanishingly rare," he wrote. "It happened a couple of times by accident, just once as a deliberate choice." The AI models could choose a wide array of actions from total surrender through diplomatic posturing, conventional military operations and full-throttle nuclear war, according to the study. But the models never accepted defeat or a willingness to fully accommodate an opponent even if they had dwindling chance of success. James Johnson, of the University of Aberdeen, UK, called the findings from a nuclear-risk perspective "unsettling," while Princeton University professor Tong Zhao warned the results could hold real-life consequences, according to New Scientist. "Major powers are already using AI in war gaming, but it remains uncertain to what extent they are incorporating AI decision support into actual military decision-making processes," said Zhao.