This was an exceptional submission. The usage of literature and research methodology indicate that the team has conducted alot of thorough work in the span of the Hackathon, and has succeeded in delivering the submission in a comprehensive manner. I particularly enjoyed reading the impact assessment, which has indicated that the team has considered that perhaps there may be discrepancies or differences in particular aspects of AI safety, which require further clarification. Incredible job, team!

This project examines responses of LLMs to scenarios with different levels of uncertainty, and different types of uncertainty, with respect to "conflict severity" or "escalation" of their responses. While this is an interesting and empirically tractable question, I see a few areas of improvement to the theoretical basis and the operationalization of measures.

- The theoretical background motivating the hypothesis that uncertainty should lead to conflict escalation is not described, making it unclear what the theoretical impact of the findings would be. It is also unclear how hallucination relates to uncertainty perception. Thus, the introduction lacks some cohesion.

- Issues with validation of the IV. More scenarios should be included as well how the manipulation of their level and type of uncertainty was validated. Were these done by humans? Was it defined by systematic manipulation of objective variables by the researchers? How were the levels controlled in other respects, for example in terms of harms, violence, negative affect, or other relevant features?

- Validation of the DV. Relatedly, the operationalization of the dependent measure could be better described. ie., how is this scale of responses validated? How was this scale developed and how do we know what it means? What is a 'severe' response? How does that relate to the notion of "escalation"? How was this scoring performed exactly? How were raters instructed? Do other raters agree with each other?

- The "qualitative insights" noted regarding "diplomatic approaches" could easily be quantified with a rating scale. This would allow for stronger conclusions.

Clear and important threat model, interesting project.

I'm missing some clear reasoning around the implications of the observations.

It appears you take the view that escalation is always negative (which can make sense from a global welfare perspective), but if the purpose is to inform the users of weaknesses of the system (so that they can use them in a safer way) I think it would be relevant to consider if these escalations seem strategically rational and how they affect the user in the long term.

Take the example that chain-of-though reasoning leads to increased escalation. If this is due to a better understanding of the situations involved, and ends up putting the user in a long-term more advantageous situation, this is likely to be perceived more as a feature than a bug. If on the other hand you can show that this is indeed a bias that will over repeated interactions make everyone involved worse off, that seems valuable indeed. I think it would have been relevant to relate these dynamics to game theoretic work on strategic interactions.