Silver-Tongued and Sundry: Exploring Intersectional Pronouns with ChatGPT

Abstract

ChatGPT is a conversational agent built on a large language model. Trained on a significant portion of human output, ChatGPT can mimic people to a degree. As such, we need to consider what social identities ChatGPT simulates (or can be designed to simulate). In this study, we explored the case of identity simulation through Japanese first-person pronouns, which are tightly connected to social identities in intersectional ways, i.e., intersectional pronouns. We conducted a controlled online experiment where people from two regions in Japan (Kanto and Kinki) witnessed interactions with ChatGPT using ten sets of first-person pronouns. We discovered that pronouns alone can evoke perceptions of social identities in ChatGPT at the intersections of gender, age, region, and formality, with caveats. This work highlights the importance of pronoun use for social identity simulation, provides a language-based methodology for culturally-sensitive persona development, and advances the potential of intersectional identities in intelligent agents.

Honorable Mention award (top 5%) at CHI '24

References in corpus (5)

• What Pronouns for Pepper? A Critical Review of Gender/ing in Research
• Can Voice Assistants Sound Cute? Towards a Model of Kawaii Vocalics
• Transcending the "Male Code": Implicit Masculine Biases in NLP Contexts
• Exploring Gender-Expansive Categorization Options for Robots
• "I'm" Lost in Translation: Pronoun Missteps in Crowdsourced Data Sets

Cited by in corpus (3)

• Social Identity in Human-Agent Interaction: A Primer
• More-than-Human Storytelling: Designing Longitudinal Narrative Engagements with Generative AI
• Inter(sectional) Alia(s): Ambiguity in Voice Agent Identity via Intersectional Japanese Self-Referents