From fake social media accounts and generative artificial intelligence chatbots to trading algorithms and self-driving vehicles, robots, bots and algorithms are proliferating and permeating our communication channels, social interactions, economic transactions and transportation arteries. Networks of multiple interdependent and interacting humans and intelligent machines constitute complex social systems for which the collective outcomes cannot be deduced from either human or machine behaviour alone. Under this paradigm, we review recent research and identify general dynamics and patterns in situations of competition, coordination, cooperation, contagion and collective decision-making, with context-rich examples from high-frequency trading markets, a social media platform, an open collaboration community and a discussion forum. To ensure more robust and resilient human–machine communities, we require a new sociology of humans and machines. Researchers should study these communities using complex system methods; engineers should explicitly design artificial intelligence for human–machine and machine–machine interactions; and regulators should govern the ecological diversity and social co-development of humans and machines.

从虚假的社交媒体账户和生成式人工智能聊天机器人到交易算法和自动驾驶汽车，机器人、机器人和算法正在激增并渗透到我们的通信渠道、社交互动、经济交易和交通动脉中。多个相互依存和互动的人类和智能机器组成的网络构成了复杂的社会系统，其集体结果不能仅从人类或机器的行为中推断出来。在这种范式下，我们回顾了最近的研究，并确定了竞争、协调、合作、传染和集体决策情况下的一般动态和模式，并提供了来自高频交易市场、社交媒体平台、开放式协作社区和论坛的背景丰富的示例。为了确保更强大、更有弹性的人机社区，我们需要一种新的人类和机器社会学。研究人员应该使用复杂的系统方法研究这些群落;工程师应该明确地为人机交互和机器交互设计人工智能;监管机构应该管理人类和机器的生态多样性和社会共同发展。