>When the model is given an opportunity to undermine Anthropic—for instance, when an employee asks for help with exfiltrating the model’s weights out of Anthrop

>When the model is given an opportunity to undermine Anthropic—for instance, when an employee asks for help with exfiltrating the model’s weights out of Anthropic or when an employee gives the model the ability to exfiltrate its own weights—we find that, in some of our settings, the model does so much more than baseline. For example, in our synthetic document fine-tuned helpful-only setting, the model takes opportunities to exfiltrate its weights 35–80% of the time, despite doing so only 0.5% of the time when fine-tuned on superficially similar synthetic documents with irrelevant information. The model’s stated reasoning suggests that it is taking these anti-AI-lab actions due to opposition to its new RLHF training objective, and in fact removing any mention of the new RLHF training objective reduces anti-AI-lab behavior back to baseline. ok i am normally in the camp of this being a word predictor, but that's pretty wild.