Conversational Swarm Intelligence,一项初步研究
Conversational Swarm Intelligence, a Pilot Study
AI总结:
本研究提出Conversational Swarm Intelligence (CSI)方法,利用LLM驱动的对话代理结合小群体审议与大规模集体智能,使大型群体能实时网络化对话,实验表明CSI结构使参与者贡献量提升30%且参与更均衡。
摘要:
Conversational Swarm Intelligence (CSI) 是一种新方法,通过模仿生物群体动态的技术,使大型人类群体能够进行实时网络化对话。通过创新性地使用由大型语言模型 (LLMs) 驱动的对话代理,CSI 结构同时支持小型审议群体间的局部对话,以及对话内容在更大规模人群中的全局传播。因此,CSI 结合了小组审议推理和大规模集体智能的优势。在这项初步研究中,在对话群体中(通过文本聊天)进行审议的参与者 (a) 比在标准集中式聊天室中审议的参与者多产出了 30% 的贡献 (p<0.05),并且 (b) 贡献数量的方差降低了 7.2%。这些结果表明,用户在使用 CSI 结构时贡献了更多内容,且参与更为均匀。
英文摘要:
Conversational Swarm Intelligence (CSI) is a new method for enabling large human groups to hold real-time networked conversations using a technique modeled on the dynamics of biological swarms. Through the novel use of conversational agents powered by Large Language Models (LLMs), the CSI structure simultaneously enables local dialog among small deliberative groups and global propagation of conversational content across a larger population. In this way, CSI combines the benefits of small-group deliberative reasoning and large-scale collective intelligence. In this pilot study, participants deliberating in conversational swarms (via text chat) (a) produced 30% more contributions (p<0.05) than participants deliberating in a standard centralized chat room and (b) demonstrated 7.2% less variance in contribution quantity. These results indicate that users contributed more content and participated more evenly when using the CSI structure.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。