Mechanisms of Crowd Intelligence Emergence in Human Societies: from Collective Behaviors to Culture Evolution (Invited)

doi:10.19678/j.issn.1000-3428.0253199

Abstract

Abstract:

Crowd intelligence has been highlighted as one of the five major trend directions in China's New Generation Artificial Intelligence Development Plan, and the question ″How does crowd intelligence emerge?″ was listed by Science in 2021 among 125 key scientific challenges for the future. Existing studies on intelligence emergence have largely focused on collective intelligence in biological groups (e.g., flocks of birds and schools of fish), emphasizing how simple individuals following local interaction rules can give rise to globally ordered behaviors. By contrast, crowd intelligence in human societies involves not only behavioral coordination and organization but also higher-order intelligence and richer connotations manifested in knowledge, culture, and innovation. To address this discrepancy and research gap, this study, for the first time, systematically reviews and clarifies the conceptual framework and core connotations of crowd intelligence in human societies. It conducts an in-depth analysis of seven representative emergent phenomena—crowd behavior, wisdom of crowds, consensus formation, social cooperation, social learning, knowledge and culture, and collective intelligence innovation—by summarizing their key mechanisms, major models, driving factors, and evolutionary regularities, thereby constructing a theoretical system for the emergence of crowd intelligence in human societies. Building on this foundation, the study further investigates the mapping pathways and mechanisms from human crowd intelligence to artificial crowd intelligence; extracts representative paradigms and essential implementation essentials of mechanism-driven artificial crowd intelligence systems; and provides fundamental theoretical and methodological support for the design, construction, and future development of artificial crowd intelligence systems oriented toward complex tasks.

Key words: human society, crowd behavior, crowd intelligence, social learning, culture formation, collective intelligence innovation

摘要：

群体智能是国家《新一代人工智能发展规划》提出的5个趋势方向之一, "群体智能是如何涌现的"也被《Science》于2021年列为未来亟待攻克的125个关键科学问题之一。当前关于群体智能涌现的研究多以鸟群、鱼群等生物集群为主要对象, 强调简单个体在局部交互规则下形成全局有序行为; 相比之下, 人类社会的群智涌现不仅包含行为层面的协同与组织, 更体现出知识、文化与创新层面的高阶智能与复杂内涵。面对这一差异与空白, 本文系统梳理与阐释人类社会群体智能的概念框架与核心内涵, 围绕人群行进、群体智慧、共识形成、社会合作、社会学习、知识文化与集智创新7类典型现象展开深入分析, 归纳其关键机制、主要模型、驱动要素与演化规律, 进而构建人类社会群智涌现理论体系。在此基础上, 进一步探讨人类群智向人工群智的映射路径与机理, 提炼群智机理驱动的典型人工群智系统范式与实现要点, 为面向复杂任务的人工群智系统设计、构建与发展提供基础理论依据与方法支撑。

关键词: 人类社会, 集体行为, 群体智能, 社会学习, 文化形成, 集智创新

GUO Bin, WU Lei, LIU Ximing, LI Mingze, ZHANG Zhouyangzi, LIU Sicong, YU Zhiwen. Mechanisms of Crowd Intelligence Emergence in Human Societies: from Collective Behaviors to Culture Evolution (Invited)[J]. Computer Engineering, 2026, 52(3): 1-40.

郭斌, 吴磊, 刘希明, 李明泽, 张周阳子, 刘思聪, 於志文. 人类社会群智涌现机理: 从集群行为到文化演化(特邀)[J]. 计算机工程, 2026, 52(3): 1-40.

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https://www.ecice06.com/EN/Y2026/V52/I3/1

Figures/Tables 6

Fig.1 Emergence mechanism, mapping mechanism, and typical applications of crowd intelligence in human societies

Fig.2 Generation mechanism and influencing factors of collective intelligence innovation

Fig.3 Cultural evolution

Fig.4 Simulation of artificial communities based on LLM— ′Stanford Town′

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