Inter(sectional) Alia(s): Ambiguity in Voice Agent Identity via Intersectional Japanese Self-Referents

要旨

Conversational agents that mimic people have raised questions about the ethics of anthropomorphizing machines with human social identity cues. Critics have also questioned assumptions of identity neutrality in humanlike agents. Recent work has revealed that intersectional Japanese pronouns can elicit complex and sometimes evasive impressions of agent identity. Yet, the role of other “neutral” non-pronominal self-referents (NPSR) and voice as a socially expressive medium remains unexplored. In a crowdsourcing study, Japanese participants (N = 204) evaluated three ChatGPT voices (Juniper, Breeze, and Ember) using seven self-referents. We found strong evidence of voice gendering alongside the potential of intersectional self-referents to evade gendering, i.e., ambiguity through neutrality and elusiveness. Notably, perceptions of age and formality intersected with gendering as per sociolinguistic theories, especiallyぼく (boku) andわたくし (watakushi). This work provides a nuanced take on agent identity perceptions and champions intersectional and culturally-sensitive work on voice agents.

キーワード
Human-Machine Dialogue
Conversational User Interface
Voice Interaction
Social Identity
Identity Perception
Pronouns
ChatGPT
Chatbot
Intersectionality
Gender
Japan
著者
Takao Fujii
Katie Seaborn
Madeleine Steeds
Jun Kato
DOI

10.1145/3706598.3713323

論文URL

https://doi.org/10.1145/3706598.3713323

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Societal Perspectives

Annex Hall F203
7 件の発表
2025-04-29 23:10:00
2025-04-30 00:40:00
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