# Neither "Hear" Nor "Their": Interrogating Gender Neutrality in Robots

arXiv: https://arxiv.org/abs/2205.00183 · HTML: https://mlsanity.com/paper/2205.00183/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Apr 2022.

## Built on by (most cited first, 5 of 5)

- [Can Voice Assistants Sound Cute? Towards a Model of Kawaii Vocalics](https://mlsanity.com/paper/2304.12809/) (2023)
- [Human-Centric Aware UAV Trajectory Planning in Search and Rescue Missions Employing Multi-Objective Reinforcement Learning with AHP and Similarity-Based Experience Replay](https://mlsanity.com/paper/2402.18487/) (2024)
- [Social Identity in Human-Agent Interaction: A Primer](https://mlsanity.com/paper/2508.16609/) (2025)
- [Inter(sectional) Alia(s): Ambiguity in Voice Agent Identity via Intersectional Japanese Self-Referents](https://mlsanity.com/paper/2506.01998/) (2025)
- [Operationalizing Perceptions of Agent Gender: Foundations and Guidelines](https://mlsanity.com/paper/2603.26682/) (2026)

## Abstract (arXiv)

Gender is a social framework through which people organize themselves-and non-human subjects, including robots. Research stretching back decades has found evidence that people tend to gender artificial agents unwittingly, even with the slightest cue of humanlike features in voice, body, role, and other social features. This has led to the notion of gender neutrality in robots: ways in which we can avoid gendering robots in line with human models, as well explorations of extra-human genders. This rapid review critically surveyed the literature to capture the state of art on gender neutrality in robots that interact with people. We present findings on theory, methods, results, and reflexivity. We interrogate the very idea that robot gender/ing can be neutral and explore alternate ways of approaching gender/ing through the design and study of robots interacting with people.