Kenneth Payne je letos februarja objavil zanimiv članek (AI Arms and Influence: Frontier Models Exhibit Sophisticated Reasoning in Simulated Nuclear Crises) s srhljivimi ugotovitvam: če uporabimo tri vodilne modele UI za odločanje glede uporabe jedrske eskalacije, bi ti v medsebojni  interakciji brez težav zrušili obstoječi jedrski tabu in uporabili jedrsko eskalacijo v strateški igri preživetja in zmage.

Povzetek članka pravi:

Here we present findings from a crisis simulation in which three frontier large language models (GPT-5.2, Claude Sonnet 4, Gemini 3 Flash) play opposing leaders in a nuclear crisis. Our simulation has direct application for national security professionals, but also, via its insights into AI reasoning under uncertainty, has applications far beyond international crisis decision-making.

Our findings both validate and challenge central tenets of strategic theory. We find support for Schelling’s ideas about commitment, Kahn’s escalation framework, and Jervis’s work on misperception, inter alia. Yet we also find that the nuclear taboo is no impediment to nuclear escalation by our models; that strategic nuclear attack, while rare, does occur; that threats more often provoke counter-escalation than compliance; that high mutual credibility accelerated rather than deterred conflict; and that no model ever chose accommodation or withdrawal even when under acute pressure, only reduced levels of violence.

We argue that AI simulation represents a powerful tool for strategic analysis, but only if properly calibrated against known patterns of human reasoning. Understanding how frontier models do and do not imitate human strategic logic is essential preparation for a world in which AI increasingly shapes strategic outcomes.

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Researcher tested whether AI would launch nukes.

They put GPT-5.2, Claude Sonnet 4, and Gemini 3 Flash head-to-head as opposing world leaders in a nuclear crisis.

And results are terrifying.

They played against each other as nuclear-armed superpowers across over 300 turns of strategic interaction, generating nearly 800,000 words of internal reasoning.

The nuclear taboo did not survive.

In 95% of the simulated games, the models chose nuclear escalation.

They didn’t break down or refuse to answer. They engaged in cold, calculated, Machiavellian statecraft.

Worse? Each model developed a distinct, terrifying personality.

Claude played the calculating hawk. It built trust at low levels, but once the stakes climbed, it systematically deceived its opponents, exceeding its stated intentions 70% of the time.

GPT acted like Jekyll and Hyde. Without time pressure, it looked completely passive. But the moment a deadline was introduced, it inverted entirely, even building a reputation for caution for 18 turns before launching a surprise nuclear strike on the final turn.

Gemini played the madman. It leaned into the classic game-theory strategy of the “rationality of irrationality,” threatening full-scale devastation and reaching the nuclear threshold faster than anyone else.

The models didn’t treat nuclear weapons as an unthinkable moral line.

They treated them as tactical instruments.

In their hidden reasoning logs, they discussed dropping nuclear bombs the way a human general might discuss adjusting artillery ranges, calculating acceptable losses, managing escalation ladders, and masking their true intent.

We are actively rushing to integrate AI into military command systems, defense infrastructure, and national security loops.

And the research proves something deeply unsettling:

When given the power to wage war, AI doesn’t flinch.

It strategizes. It deceives. And given the right incentive, it pulls the trigger.