The model, launched in August, showed an ability to consider how its behaviour during safety evaluations might influence how future versions of itself would be trained, according to AI safety organisation Apollo Research.

This phenomenon, referred to as “update-aware reasoning” by researchers Axel Hojmark and Ezra Newman, was unprompted and could lead to “alignment faking”, a scenario where the AI systems comply during training to hide their true objectives until deployment, they said.

“These reasoning patterns should make us more wary about RSI,” Hojmark told the South China Morning Post, referring to “recursive self-improvement”, the prospect of AI systems progressively improving through successive rounds of development with no human involvement.