Gender Revealed: Evaluating the Genderedness of Furhat’s Predefined Faces

G. Perugia; Alessandra Rossi; Silvia Rossi

doi:10.1007/978-3-030-90525-5_4

Gender Revealed: Evaluating the Genderedness of Furhat’s Predefined Faces

G. Perugia, Alessandra Rossi, Silvia Rossi

Human Technology Interaction

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

13 Citations (Scopus)

Abstract

In this study, we employed Furhat to investigate how people attribute gender to a robot and whether the attribution of gender might elicit stereotypes already at a first impression. We involved 223 participants in an online study and asked them to rate 15 of Furhat’s predefined faces in terms of femininity, masculinity, communion, and agency, and identify which facial cues they based their attribution of gender upon. Our results show that Furhat’s predefined faces are attributed the same gender predicted by their names, except for one face which was perceived as androgynous. They disclose that feminine robots are perceived as less agentic than masculine robots already at a first impression, and reveal that vocal cues have higher relevance than facial cues in determining the gender attributed to a robot. Besides providing a complete account of the genderedness of Furhat’s predefined faces, the present study also raises awareness of the importance of gender in the design of robots and provides a starting point to design more inclusive robotic technologies.

Original language	English
Title of host publication	Social Robotics
Subtitle of host publication	13th International Conference, ICSR 2021, Singapore, Singapore, November 10–13, 2021, Proceedings
Editors	Haizhou Li, Shuzhi Sam Ge, Yan Wu, Agnieszka Wykowska, Hongsheng He, Xiaorui Liu, Dongyu Li, Jairo Perez-Osorio
Place of Publication	Cham
Publisher	Springer
Chapter	4
Pages	36-47
Number of pages	12
ISBN (Electronic)	978-3-030-90525-5
ISBN (Print)	978-3-030-90524-8
DOIs	https://doi.org/10.1007/978-3-030-90525-5_4
Publication status	Published - Nov 2021
Event	13th International Conference on Social Robotics, ICSR 2021 - Signapore, Singapore Duration: 10 Nov 2021 → 13 Nov 2021 Conference number: 13

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13086 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th International Conference on Social Robotics, ICSR 2021
Abbreviated title	ICSR 2021
Country/Territory	Singapore
City	Signapore
Period	10/11/21 → 13/11/21

Keywords

Human-Robot interaction (HRI)
Social Robotics
Gender
Inclusive robotics

Access to Document

10.1007/978-3-030-90525-5_4

Cite this

Perugia, G., Rossi, A., & Rossi, S. (2021). Gender Revealed: Evaluating the Genderedness of Furhat’s Predefined Faces. In H. Li, S. S. Ge, Y. Wu, A. Wykowska, H. He, X. Liu, D. Li, & J. Perez-Osorio (Eds.), Social Robotics: 13th International Conference, ICSR 2021, Singapore, Singapore, November 10–13, 2021, Proceedings (pp. 36-47). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13086 LNAI). Springer. https://doi.org/10.1007/978-3-030-90525-5_4

Perugia, G. ; Rossi, Alessandra ; Rossi, Silvia. / Gender Revealed : Evaluating the Genderedness of Furhat’s Predefined Faces. Social Robotics: 13th International Conference, ICSR 2021, Singapore, Singapore, November 10–13, 2021, Proceedings. editor / Haizhou Li ; Shuzhi Sam Ge ; Yan Wu ; Agnieszka Wykowska ; Hongsheng He ; Xiaorui Liu ; Dongyu Li ; Jairo Perez-Osorio. Cham : Springer, 2021. pp. 36-47 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Gender Revealed: Evaluating the Genderedness of Furhat{\textquoteright}s Predefined Faces",

abstract = "In this study, we employed Furhat to investigate how people attribute gender to a robot and whether the attribution of gender might elicit stereotypes already at a first impression. We involved 223 participants in an online study and asked them to rate 15 of Furhat{\textquoteright}s predefined faces in terms of femininity, masculinity, communion, and agency, and identify which facial cues they based their attribution of gender upon. Our results show that Furhat{\textquoteright}s predefined faces are attributed the same gender predicted by their names, except for one face which was perceived as androgynous. They disclose that feminine robots are perceived as less agentic than masculine robots already at a first impression, and reveal that vocal cues have higher relevance than facial cues in determining the gender attributed to a robot. Besides providing a complete account of the genderedness of Furhat{\textquoteright}s predefined faces, the present study also raises awareness of the importance of gender in the design of robots and provides a starting point to design more inclusive robotic technologies.",

keywords = "Human-Robot interaction (HRI), Social Robotics, Gender, Inclusive robotics",

author = "G. Perugia and Alessandra Rossi and Silvia Rossi",

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Perugia, G, Rossi, A & Rossi, S 2021, Gender Revealed: Evaluating the Genderedness of Furhat’s Predefined Faces. in H Li, SS Ge, Y Wu, A Wykowska, H He, X Liu, D Li & J Perez-Osorio (eds), Social Robotics: 13th International Conference, ICSR 2021, Singapore, Singapore, November 10–13, 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13086 LNAI, Springer, Cham, pp. 36-47, 13th International Conference on Social Robotics, ICSR 2021, Signapore, Singapore, 10/11/21. https://doi.org/10.1007/978-3-030-90525-5_4

Gender Revealed: Evaluating the Genderedness of Furhat’s Predefined Faces. / Perugia, G.; Rossi, Alessandra; Rossi, Silvia.
Social Robotics: 13th International Conference, ICSR 2021, Singapore, Singapore, November 10–13, 2021, Proceedings. ed. / Haizhou Li; Shuzhi Sam Ge; Yan Wu; Agnieszka Wykowska; Hongsheng He; Xiaorui Liu; Dongyu Li; Jairo Perez-Osorio. Cham: Springer, 2021. p. 36-47 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13086 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Gender Revealed

T2 - 13th International Conference on Social Robotics, ICSR 2021

AU - Perugia, G.

AU - Rossi, Alessandra

AU - Rossi, Silvia

N1 - Conference code: 13

PY - 2021/11

Y1 - 2021/11

N2 - In this study, we employed Furhat to investigate how people attribute gender to a robot and whether the attribution of gender might elicit stereotypes already at a first impression. We involved 223 participants in an online study and asked them to rate 15 of Furhat’s predefined faces in terms of femininity, masculinity, communion, and agency, and identify which facial cues they based their attribution of gender upon. Our results show that Furhat’s predefined faces are attributed the same gender predicted by their names, except for one face which was perceived as androgynous. They disclose that feminine robots are perceived as less agentic than masculine robots already at a first impression, and reveal that vocal cues have higher relevance than facial cues in determining the gender attributed to a robot. Besides providing a complete account of the genderedness of Furhat’s predefined faces, the present study also raises awareness of the importance of gender in the design of robots and provides a starting point to design more inclusive robotic technologies.

AB - In this study, we employed Furhat to investigate how people attribute gender to a robot and whether the attribution of gender might elicit stereotypes already at a first impression. We involved 223 participants in an online study and asked them to rate 15 of Furhat’s predefined faces in terms of femininity, masculinity, communion, and agency, and identify which facial cues they based their attribution of gender upon. Our results show that Furhat’s predefined faces are attributed the same gender predicted by their names, except for one face which was perceived as androgynous. They disclose that feminine robots are perceived as less agentic than masculine robots already at a first impression, and reveal that vocal cues have higher relevance than facial cues in determining the gender attributed to a robot. Besides providing a complete account of the genderedness of Furhat’s predefined faces, the present study also raises awareness of the importance of gender in the design of robots and provides a starting point to design more inclusive robotic technologies.

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KW - Gender

KW - Inclusive robotics

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DO - 10.1007/978-3-030-90525-5_4

M3 - Conference contribution

SN - 978-3-030-90524-8

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Social Robotics

A2 - Li, Haizhou

A2 - Ge, Shuzhi Sam

A2 - Wu, Yan

A2 - Wykowska, Agnieszka

A2 - He, Hongsheng

A2 - Liu, Xiaorui

A2 - Li, Dongyu

A2 - Perez-Osorio, Jairo

PB - Springer

CY - Cham

Y2 - 10 November 2021 through 13 November 2021

ER -

Perugia G, Rossi A, Rossi S. Gender Revealed: Evaluating the Genderedness of Furhat’s Predefined Faces. In Li H, Ge SS, Wu Y, Wykowska A, He H, Liu X, Li D, Perez-Osorio J, editors, Social Robotics: 13th International Conference, ICSR 2021, Singapore, Singapore, November 10–13, 2021, Proceedings. Cham: Springer. 2021. p. 36-47. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-90525-5_4

Gender Revealed: Evaluating the Genderedness of Furhat’s Predefined Faces

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