Online social networks often create echo chambers where people only hear opinions reinforcing their beliefs. An echo chamber often generates polarization, leading to conflicts caused by people with radical opinions, such as the January 6, 2021, attack on the US Capitol. The echo chamber has been viewed as a human-specific problem, but this implicit assumption is becoming less reasonable as large language models, such as ChatGPT, acquire social abilities. In response to this situation, we investigated the potential for polarization to occur among a group of autonomous AI agents based on generative language models in an echo chamber environment. We had AI agents discuss specific topics and analyzed how the group's opinions changed as the discussion progressed. As a result, we found that the group of agents based on ChatGPT tended to become polarized in echo chamber environments. The analysis of opinion transitions shows that this result is caused by ChatGPT's high prompt understanding ability to update its opinion by considering its own and surrounding agents' opinions. We conducted additional experiments to investigate under what specific conditions AI agents tended to polarize. As a result, we identified factors that strongly influence polarization, such as the agent's persona. These factors should be monitored to prevent the polarization of AI agents.

翻译：在线社交网络常常形成回音室效应，使人们只能听到强化自身信念的观点。回音室通常会导致观点极化，进而引发持有激进观点者造成的冲突，例如2021年1月6日对美国国会大厦的袭击。回音室现象此前被视为人类特有的问题，但随着ChatGPT等大型语言模型获得社交能力，这一潜在假设正变得不再成立。为应对这一情况，我们研究了基于生成式语言模型的自主AI智能体群体在回音室环境中出现极化的可能性。我们安排AI智能体就特定主题进行讨论，并分析讨论过程中群体观点的演变趋势。结果表明，基于ChatGPT的智能体群体在回音室环境中确实倾向于出现极化。观点迁移分析显示，这一结果源于ChatGPT强大的提示理解能力——它能通过综合自身及周围智能体的观点来更新自身立场。我们进一步通过实验探究了促使AI智能体出现极化的具体条件，最终识别出智能体人格等强烈影响极化的关键因素。为防止AI智能体出现极化现象，需对这些因素进行持续监测。