Social Identity in Human-Agent Interaction: A Primer

TL;DR

This paper introduces social identity theory and social categorization theory, exploring their relevance and application to artificial social agents like robots and chatbots, highlighting the importance of understanding social dynamics in human-agent interactions.

Contribution

It provides a primer on SIA, extrapolates its application to artificial agents, and discusses implications for human-agent social interactions and ethical considerations.

Findings

SIT and SCT can be applied to artificial social agents.

Understanding social identity in agents influences human interaction.

Emerging AI agents challenge traditional social models.

Abstract

Social identity theory (SIT) and social categorization theory (SCT) are two facets of the social identity approach (SIA) to understanding social phenomena. SIT and SCT are models that describe and explain how people interact with one another socially, connecting the individual to the group through an understanding of underlying psychological mechanisms and intergroup behaviour. SIT, originally developed in the 1970s, and SCT, a later, more general offshoot, have been broadly applied to a range of social phenomena among people. The rise of increasingly social machines embedded in daily life has spurned efforts on understanding whether and how artificial agents can and do participate in SIA activities. As agents like social robots and chatbots powered by sophisticated large language models (LLMs) advance, understanding the real and potential roles of these technologies as social entities is crucial. Here, I provide a primer on SIA and extrapolate, through case studies and imagined examples, how SIT and SCT can apply to artificial social agents. I emphasize that not all human models and sub-theories will apply. I further argue that, given the emerging competence of these machines and our tendency to be taken in by them, we experts may need to don the hat of the uncanny killjoy, for our own good.