Synthetic duality: A framework for analyzing generative artificial intelligence's representation of social reality

Abstract

The development of generative artificial intelligence (genAI) has caused concern about its potential risks, including how its ability to generate human-like texts could affect our shared perception of the social world. Yet, it remains unclear how best to assess and understand genAI's influence on our understanding of social reality. Building on insights into the representation of social worlds within texts, we introduce a framework for analyzing genAI's content and its consequences for perceptions of social reality. We demonstrate this “synthetic duality” framework in two parts. First, we show that genAI can create, with minimal guidance, reasonable portrayals of actors and ascribe relational meaning to those actors – virtual social worlds within texts, or “Mondo-Breigers”. Second, we examine how these synthetic documents with interior social worlds affect readers’ view of social reality. We find that they change individuals’ perceptions of actors depicted in the documents, likely by updating individuals’ expectations about the actors and their meanings. However, additional exploratory analyses suggest it is texts’ style, not their construction of “Mondo-Breigers”, that might be influencing people's perceptions. We end with a discussion of theoretical and methodological implications, including how genAI may unsettle structural notions of individuality. Namely, reimagining the duality of individuals and groups could help theorize growing homogeneity in an increasingly genAI-informed world.