The current societal challenges exceed the capacity of human individual or collective effort alone. As AI evolves, its role within human collectives is poised to vary from an assistive tool to a participatory member. Humans and AI possess complementary capabilities that, when synergized, can achieve a level of collective intelligence that surpasses the collective capabilities of either humans or AI in isolation. However, the interactions in human-AI systems are inherently complex, involving intricate processes and interdependencies. This review incorporates perspectives from network science to conceptualize a multilayer representation of human-AI collective intelligence, comprising a cognition layer, a physical layer, and an information layer. Within this multilayer network, humans and AI agents exhibit varying characteristics; humans differ in diversity from surface-level to deep-level attributes, while AI agents range in degrees of functionality and anthropomorphism. The interplay among these agents shapes the overall structure and dynamics of the system. We explore how agents' diversity and interactions influence the system's collective intelligence. Furthermore, we present an analysis of real-world instances of AI-enhanced collective intelligence. We conclude by addressing the potential challenges in AI-enhanced collective intelligence and offer perspectives on future developments in this field.

翻译：当前社会的挑战已超出人类个体或集体努力本身的能力范围。随着人工智能的发展，其在人类集体中的角色将从辅助工具演变为参与性成员。人类与人工智能具有互补能力，当协同作用时，可实现超越人类或人工智能单独集体能力的集体智能水平。然而，人机系统中的交互本质上是复杂的，涉及错综复杂的流程和相互依存关系。本综述融合网络科学的视角，构建了人类-人工智能集体智能的多层表征，包括认知层、物理层和信息层。在该多层网络中，人类与AI智能体展现出不同特征：人类在表层到深层属性维度上呈现多样性，而AI智能体则体现功能性与拟人化程度的梯度差异。这些智能体间的相互作用塑造了系统的整体架构与动态演化。我们探讨了智能体的多样性与交互如何影响系统的集体智能。此外，我们分析了AI增强集体智能的现实应用案例，最后针对该领域面临的潜在挑战展开讨论，并展望了未来发展方向。