Towards Collective Superintelligence, a Pilot Study
2023 International Conference on Human-Centered Cognitive Systems (HCCS)(2023)
摘要
Conversational Swarm Intelligence (CSI) is a new technology that enables
human groups of potentially any size to hold real-time deliberative
conversations online. Modeled on the dynamics of biological swarms, CSI aims to
optimize group insights and amplify group intelligence. It uses Large Language
Models (LLMs) in a novel framework to structure large-scale conversations,
combining the benefits of small-group deliberative reasoning and large-group
collective intelligence. In this study, a group of 241 real-time participants
were asked to estimate the number of gumballs in a jar by looking at a photo.
In one test case, individual participants entered their estimation in a
standard survey. In another test case, participants converged on groupwise
estimates collaboratively using a prototype CSI text-chat platform called
Thinkscape. The results show that when using CSI, the group of 241 participants
estimated within 12% of the correct answer, which was significantly more
accurate (p<0.001) than the average individual (mean error of 55%) and the
survey-based Wisdom of Crowd (error of 25%). The group using CSI was also more
accurate than an estimate generated by GPT 4 (error of 42%). This suggests that
CSI is a viable method for enabling large, networked groups to hold coherent
real-time deliberative conversations that amplify collective intelligence.
Because this technology is scalable, it could provide a possible pathway
towards building a general-purpose Collective Superintelligence (CSi).
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关键词
Collective Learning,Standard Survey,Online Chat,Swarm Intelligence,Wisdom Of The Crowd,Real-Time System,Artificial Intelligence,Natural Language,Mean Absolute Error,Unique Solution,Videoconferencing,Honey Bee,Smaller Error,Large School,Lateral Line,Traditional Survey,Neighboring Groups,Chat Rooms,Fish Schools,AI Systems,Viable Path
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