# Robot's Gendering Trouble: A Scoping Review of Gendering Humanoid Robots and its Effects on HRI

arXiv: https://arxiv.org/abs/2207.01130 · HTML: https://mlsanity.com/paper/2207.01130/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jul 2022.

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

- [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)
- [An Empirical Design Justice Approach to Identifying Ethical Considerations in the Intersection of Large Language Models and Social Robotics](https://mlsanity.com/paper/2406.06400/) (2024)
- [Super Kawaii Vocalics: Amplifying the "Cute" Factor in Computer Voice](https://mlsanity.com/paper/2507.06235/) (2025)
- [Operationalizing Perceptions of Agent Gender: Foundations and Guidelines](https://mlsanity.com/paper/2603.26682/) (2026)

## Abstract (arXiv)

The discussion around the problematic practice of gendering humanoid robots has risen to the foreground in the last few years. To lay the basis for a thorough understanding of how robot's "gender" has been understood within the Human-Robot Interaction (HRI) community - i.e., how it has been manipulated, in which contexts, and which effects it has yield on people's perceptions and interactions with robots - we performed a scoping review of the literature. We identified 553 papers relevant for our review retrieved from 5 different databases. The final sample of reviewed papers included 35 papers written between 2005 and 2021, which involved a total of 3902 participants. In this article, we thoroughly summarize these papers by reporting information about their objectives and assumptions on gender (i.e., definitions and reasons to manipulate gender), their manipulation of robot's "gender" (i.e., gender cues and manipulation checks), their experimental designs (e.g., demographics of participants, employed robots), and their results (i.e., main and interaction effects). The review reveals that robot's "gender" does not affect crucial constructs for the HRI, such as likability and acceptance, but rather bears its strongest effect on stereotyping. We leverage our different epistemological backgrounds in Social Robotics and Gender Studies to provide a comprehensive interdisciplinary perspective on the results of the review and suggest ways to move forward in the field of HRI.