A new sociology of humans and machines

Abstract

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. This Perspective calls for a new sociology of humans and machines to study groups and networks comprising multiple interacting humans and algorithms, bots or robots. A deeper understanding of human–machine social systems can contribute new and valued insights for AI research, design and policy.