Silver-Tongued and Sundry: Exploring Intersectional Pronouns with ChatGPT

要旨

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.

受賞
Honorable Mention
著者
Takao Fujii
Tokyo Institute of Technology, Tokyo, Japan
Katie Seaborn
Tokyo Institute of Technology, Tokyo, Japan
Madeleine Steeds
University College Dublin, Dublin, Ireland
論文URL

https://doi.org/10.1145/3613904.3642303

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Remote Presentations: Highlight on Diversity In HCI

Remote Sessions
10 件の発表
2024-05-15 18:00:00
2024-05-16 02:20:00