# Not Only WEIRD but "Uncanny"? A Systematic Review of Diversity in Human-Robot Interaction Research

arXiv: https://arxiv.org/abs/2304.08750 · HTML: https://mlsanity.com/paper/2304.08750/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Apr 2023.

## Built on by (most cited first, 8 of 8)

- [Cultural Bias in Explainable AI Research: A Systematic Analysis](https://mlsanity.com/paper/2403.05579/) (2024)
- [Coimagining the Future of Voice Assistants with Cultural Sensitivity](https://mlsanity.com/paper/2403.17599/) (2024)
- [Social Identity in Human-Agent Interaction: A Primer](https://mlsanity.com/paper/2508.16609/) (2025)
- [Encoding Inequity: Examining Demographic Bias in LLM-Driven Robot Caregiving](https://mlsanity.com/paper/2503.05765/) (2025)
- [Qualitative Approaches to Voice UX](https://mlsanity.com/paper/2404.14736/) (2024)
- [WEIRD ICWSM: How Western, Educated, Industrialized, Rich, and Democratic is Social Computing Research?](https://mlsanity.com/paper/2406.02090/) (2024)
- [Operationalizing Perceptions of Agent Gender: Foundations and Guidelines](https://mlsanity.com/paper/2603.26682/) (2026)
- [Responsible Personalisation: The Double-Edged Sword of Personalisation in Human-Robot Interaction](https://mlsanity.com/paper/2607.06344/) (2026)

## Abstract (arXiv)

Critical voices within and beyond the scientific community have pointed to a grave matter of concern regarding who is included in research and who is not. Subsequent investigations have revealed an extensive form of sampling bias across a broad range of disciplines that conduct human subjects research called "WEIRD": Western, Educated, Industrial, Rich, and Democratic. Recent work has indicated that this pattern exists within human-computer interaction (HCI) research, as well. How then does human-robot interaction (HRI) fare? And could there be other patterns of sampling bias at play, perhaps those especially relevant to this field of study? We conducted a systematic review of the premier ACM/IEEE International Conference on Human-Robot Interaction (2006-2022) to discover whether and how WEIRD HRI research is. Importantly, we expanded our purview to other factors of representation highlighted by critical work on inclusion and intersectionality as potentially underreported, overlooked, and even marginalized factors of human diversity. Findings from 827 studies across 749 papers confirm that participants in HRI research also tend to be drawn from WEIRD populations. Moreover, we find evidence of limited, obscured, and possible misrepresentation in participant sampling and reporting along key axes of diversity: sex and gender, race and ethnicity, age, sexuality and family configuration, disability, body type, ideology, and domain expertise. We discuss methodological and ethical implications for recruitment, analysis, and reporting, as well as the significance for HRI as a base of knowledge.