As large language models (LLMs) are increasingly used in morally sensitive domains, it is crucial to understand how persona traits affect their moral reasoning and persuasive behavior. We present the first large-scale study of multi-dimensional persona effects in AI-AI debates over real-world moral dilemmas. Using a 6-dimensional persona space (age, gender, country, class, ideology, and personality), we simulate structured debates between AI agents over 131 relationship-based cases. Our results show that personas affect initial moral stances and debate outcomes, with political ideology and personality traits exerting the strongest influence. Persuasive success varies across traits, with liberal and open personalities reaching higher consensus and win rates. While logit-based confidence grows during debates, emotional and credibility-based appeals diminish, indicating more tempered argumentation over time. These trends mirror findings from psychology and cultural studies, reinforcing the need for persona-aware evaluation frameworks for AI moral reasoning.

翻译：随着大型语言模型（LLM）日益应用于道德敏感领域，理解角色特质如何影响其道德推理与说服行为至关重要。本研究首次针对现实世界道德困境中AI-AI辩论的多维角色效应展开大规模实证分析。通过构建六维角色空间（年龄、性别、国家、阶级、意识形态与人格特质），我们在131个基于人际关系的情境案例中模拟了结构化AI代理辩论。研究结果表明：角色特质显著影响初始道德立场与辩论结果，其中政治意识形态与人格特质的作用最为突出；不同特质在说服效能上存在差异，自由派与开放性人格达成更高共识且胜率更优；尽管辩论过程中基于逻辑的置信度持续增长，情感诉求与可信度策略的效力却逐渐衰减，表明论证方式随时间推移趋于理性化。这些趋势与心理学及文化研究领域的既有发现相互印证，进一步突显了建立角色感知的AI道德推理评估框架的必要性。