Social Robot Encouraging Two Strangers to Talk with Each Other for Their Relationships

Ise, Naoki; Iio, Takamasa

doi:10.1145/3434074.3447147

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…In an example of cissexism, Choi et al [102] decided to recruit from a women's college because "typically women are in charge of cleaning their houses." Similarly, Ise and Iio [103] decided to exclude women because of the gender and age combinations they wished to recruit but also because in their pilot tests they felt that "females tend[ed] to have more utterances." Von der Pütten et al [104] prescribed the sex/gender of participants based on video.…”

Section: Sex and Gendermentioning

confidence: 99%

Not Only WEIRD but “Uncanny”? A Systematic Review of Diversity in Human–Robot Interaction Research

Seaborn

Barbareschi

Chandra

2023

Int J of Soc Robotics

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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.

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Section: Sex and Gendermentioning

confidence: 99%