This study explores the sources of instability in maintaining cultural
personas and opinions within multi-agent LLM systems. Drawing on simulations of
inter-cultural collaboration and debate, we analyze agents' pre- and
post-discussion private responses alongside chat transcripts to assess the
stability of cultural personas and the impact of opinion diversity on group
outcomes. Our findings suggest that multi-agent discussions can encourage
collective decisions that reflect diverse perspectives, yet this benefit is
tempered by the agents' susceptibility to conformity due to perceived peer
pressure and challenges in maintaining consistent personas and opinions.
Counterintuitively, instructions that encourage debate in support of one's
opinions increase the rate of inconstancy. Without addressing the factors we
identify, the full potential of multi-agent frameworks for producing more
culturally diverse AI outputs will remain untapped.

通过多智能体 LLM 系统的模拟，本研究探讨了文化个体的稳定性来源以及对群体决策的意见多样性的影响，发现多智能体讨论能够鼓励反映多元观点的集体决策，但个体易受同伴压力的影响和在保持一致的文化个体和意见方面所遇到的挑战削弱了这个优势，而鼓励辩论支持自己观点的指示则提高了不一致性的发生率。如果不解决我们所确定的因素，多智能体框架产生更多文化多样的 AI 产出的潜力将无法实现。