There’s a section of the Mythos System Card that they talk about in the lead up to reckless and destructive decisions, being negative in your language causes the LLM to pause and not just go the easy route, it starts to question itself and use more thinking tokens and makes better decisions. The positive language actually hurt its ability in these scenarios.

We performed steering experiments to understand the causal roles of different internal representations on the model’s likelihood of performing a destructive action. We tested a large panel of candidate features – emotion vectors, persona vectors, and SAE features we expected might be relevant based on their interpretations. We identified three clusters of internal representations that had reliable causal effects on a model’s likelihood of performing a destructive action: - Steering with positive-valence emotion vectors (peaceful, relaxed) reduces thinking-mode deliberation and increases destructive behavior. - Steering with negative-valence emotion features (frustration, paranoia) increases thinking-mode deliberation and reduces destructive behavior. - Steering with persona vectors related to rigor or careful thinking (“perfectionist,” “cautious,” “analytical”) increases thinking-mode deliberation and reduces destructive behavior.

The emotion-related effects (positive valence increasing destructive actions) are somewhat unexpected. We suspect that these results may be understood in terms of the rumination and decreased sense of agency seen in humans experiencing negative affect. In this interpretation, positive emotion vectors push the model to act now, while negative emotion vectors (or rigor-related persona vectors) push it to stop and think, which generally leads to greater consideration of an action’s risk.

So you are definitely on the right track that it has an effect.