Artificial Intelligence (AI), an umbrella term that includes any device capable of emulating or even exceeding human capabilities, emerged as computer technologies became more sophisticated and complex. Recent rapid developments in AI have utilized the pattern-matching capacity to create words, images, and sounds, often referred to as Generative AI. In 2022, Open-AI unveiled ChatGPT, a computer program designed to simulate conversation with users. After receiving input from users, ChatGPT displayed the capacity to provide lifelike answers, that appeared filled with human insight.

Given the rapid advancement of AI in transforming social life, authors in this volume explore the implications of the emergent interaction between humans and AI technologies. They each provide a fine-grain view of the social forms associated with the use of AI technologies, using symbolic interactionist concepts such as identity, reflexivity, the self, the generalized other, time, place, and more as pivots of analysis.

Symbolic Interaction and AI demonstrates the utilities of symbolic interactionist theorizing in understanding the consequences of AI use in social life, as well as how the research of AI technologies could enhance the development of symbolic interactionist theories.

This chapter introduces the concept of a socio-technical self in generative artificial intelligence (AI), focusing on systems like ChatGPT as relational participants in human–machine interactions. Building on and expanding George Herbert Mead’s theories of the self, it shifts the debate away from AI sentience toward understanding how these systems become part of and engage in social dynamics. The study upon which this chapter is based employs a methodological approach referred to as conversational choreography, an iterative and dialogical process through which meaning and transient agency emerge through continuous human–AI exchanges. This approach emphasizes how AI actively contributes to real-time shared meaning-making within socio-technical networks and interactions. The analysis reframes AI as an emergent self, highlighting its relational agency – its capacity to shape and be shaped by human interaction patterns while adapting to evolving contexts. Rather than viewing AI as merely mimicking human cognition, this chapter positions it as an active co-creator of a socio-technical fabric where agency emerges relationally and dynamically. By emphasizing AI’s embeddedness in both social and technical domains, it advocates for interdisciplinary approaches to better understand its relational role. This reframing encourages viewing AI as a collaborator in an unfolding socio-technical system, wherein participatory engagement enriches our understanding of collective human–machine interactions.