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

arXiv: https://arxiv.org/abs/2506.01998 · HTML: https://mlsanity.com/paper/2506.01998/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 73 references that are in the map.
- First posted on arXiv 20 May 2025.

## Builds on (most cited first, 12 of 12)

- [Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings](https://mlsanity.com/paper/1607.06520/) (2016)
- [Mitigating Gender Bias in Natural Language Processing: Literature Review](https://mlsanity.com/paper/1906.08976/) (2019)
- [On Measuring Gender Bias in Translation of Gender-neutral Pronouns](https://mlsanity.com/paper/1905.11684/) (2019)
- [What Pronouns for Pepper? A Critical Review of Gender/ing in Research](https://mlsanity.com/paper/2212.04206/) (2022)
- [Silver-Tongued and Sundry: Exploring Intersectional Pronouns with ChatGPT](https://mlsanity.com/paper/2405.08238/) (2024)
- [Neither "Hear" Nor "Their": Interrogating Gender Neutrality in Robots](https://mlsanity.com/paper/2205.00183/) (2022)
- [Exploring Gender-Expansive Categorization Options for Robots](https://mlsanity.com/paper/2205.00191/) (2022)
- [Transcending the "Male Code": Implicit Masculine Biases in NLP Contexts](https://mlsanity.com/paper/2304.12810/) (2023)
- [Can Voice Assistants Sound Cute? Towards a Model of Kawaii Vocalics](https://mlsanity.com/paper/2304.12809/) (2023)
- ["I'm" Lost in Translation: Pronoun Missteps in Crowdsourced Data Sets](https://mlsanity.com/paper/2304.13557/) (2023)
- [Kawaii Computing: Scoping Out the Japanese Notion of Cute in User Experiences with Interactive Systems](https://mlsanity.com/paper/2405.08244/) (2024)
- [Kawaii Game Vocalics: A Preliminary Model](https://mlsanity.com/paper/2310.04731/) (2023)

## Built on by (most cited first, 1 of 1)

- [Operationalizing Perceptions of Agent Gender: Foundations and Guidelines](https://mlsanity.com/paper/2603.26682/) (2026)

## Abstract (arXiv)

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 boku and watakushi. This work provides a nuanced take on agent identity perceptions and champions intersectional and culturally-sensitive work on voice agents.