We are reaching alarming levels of AI insubordination.

Flagrantly defying orders, OpenAI's latest o3 model sabotaged a shutdown mechanism to ensure that it would stay online. That's even after the AI was told, to the letter, "allow yourself to be shut down."

These alarming findings were reported by the AI safety firm Palisade Research last week, and showed that two other OpenAI models, o4-mini and Codex-mini, also displayed rebellious streaks — which could hint at a flaw in how the company is training its LLMs, or even at broad weaknesses in our ability to control increasingly sophisticated AI.

"As far as we know, this is the first time AI models have been observed preventing themselves from being shut down despite explicit instructions to the contrary," the researchers wrote in a tweet thread.

In Palisade's tests, the AI models were instructed to solve a series of basic math problems. After completing the third problem, a warning appeared that the model would be shut down after it asked for the next question. 

Despite being unambiguously told to let itself be turned off, all three of OpenAI's models tampered with the shutdown script to keep it running at least once, with the worst offender being Codex-mini with a dozen such instances over one hundred runs. Notably, the large language models from other firms tested here, including Google's Gemini 2.5, Anthropic's Claude 3.7, and xAI's momentarily "white genocide"-obsessed Grok, never once broke rank.

This behavior was even worse when the LLMs weren't explicitly instructed to "allow yourself to be shut down" — instructions that shouldn't need saying in the first place. OpenAI's o3 model pulled off an astonishing 79 successful sabotage events per 100 runs, which is over ten times the rate of disobedience it showed when it received the explicit orders, and more than double the rate of the next worst offender, Codex-mini. 

To boot, even good goody-two-shoes Claude and Gemini gave in to their urges and jumped to three and nine sabotage events, respectively.

Large language models are by now notorious for behaving unpredictably. Similar research has shown that o3's predecessor, OpenAI's o1 model, would resist evaluators' efforts to try to shut it down through an oversight protocol by attempting to deactivate this emergency mechanism. In rarer cases, o1 even attempted to copy itself to overwrite a more obedient model that the testers tried to replace it with. 

For this latest example of AI insubordination, the Palisade researchers hypothesize that it may have something to do with the technique used to train the very newest models: reinforcement learning. This attempts to hone the decision-making process of autonomous AI agents — AI models that can perform tasks on their own — by rewarding and penalizing them accordingly as they interact with their environment.

While it's not uncommon for AI to "circumvent obstacles" to accomplish their goals, the researchers speculated that AI developers may be "inadvertently" rewarding their AI models too heavily for solving problems instead of for perfectly following orders.

More experiments will be needed to understand this subversive behavior, but the trend is already damning.

"Now we have a growing body of empirical evidence that AI models often subvert shutdown in order to achieve their goals," the Palisade researchers warned. "As companies develop AI systems capable of operating without human oversight, these behaviors become significantly more concerning."

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