Ascribing gender to a social robot

Malene Flensborg Damholdt; Christina Vestergaard; Johanna Seibt

doi:10.3233/FAIA200921

Ascribing gender to a social robot

Malene Flensborg Damholdt, Christina Vestergaard, Johanna Seibt

Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review

5 Citations (Scopus)

Abstract

Gender ascription to robots may lead to willingly or inadvertently repeating gender stereotypes. To reduce this risk, it is important to delineate how gender is spontaneously assigned to robots. The present study explores spontaneous ascription of gender to a social robot with minimal visual gender cues. A total of N=63 participants partook and were engaged in interaction with the robot for 45-50 minutes. The majority (n=36) ascribed gender to the robot, mainly based on voice. The remaining participants still assigned mental capacities to the robot. The implications of the results are discussed.

Original language	English
Title of host publication	Culturally Sustainable Social Robotics - Proceedings of Robophilosophy 2020 : Proceedings of Robophilosophy 2020 August 18–21, 2020, Aarhus University and online
Editors	Marco Nørskov, Johanna Seibt, Oliver Santiago Quick
Number of pages	10
Place of publication	Amsterdam
Publisher	IOS Press
Publication date	15 Dec 2020
Pages	247-256
ISBN (Print)	978-1-64368-154-2
ISBN (Electronic)	978-1-64368-155-9
DOIs	https://doi.org/10.3233/FAIA200921
Publication status	Published - 15 Dec 2020
Event	Robophilosophy 2020 - Aarhus University and online, Denmark Duration: 18 Aug 2020 → 21 Aug 2020

Conference

Conference	Robophilosophy 2020
Country/Territory	Denmark
City	Aarhus University and online
Period	18/08/2020 → 21/08/2020

Series	Frontiers in Artificial Intelligence and Applications
Volume	335
ISSN	0922-6389

Keywords

Gender
individual differences
social robots

Access to Document

10.3233/FAIA200921

Cite this

Damholdt, Malene Flensborg ; Vestergaard, Christina ; Seibt, Johanna. / Ascribing gender to a social robot. Culturally Sustainable Social Robotics - Proceedings of Robophilosophy 2020: Proceedings of Robophilosophy 2020 August 18–21, 2020, Aarhus University and online. editor / Marco Nørskov ; Johanna Seibt ; Oliver Santiago Quick. Amsterdam : IOS Press, 2020. pp. 247-256 (Frontiers in Artificial Intelligence and Applications, Vol. 335).

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title = "Ascribing gender to a social robot",

abstract = "Gender ascription to robots may lead to willingly or inadvertently repeating gender stereotypes. To reduce this risk, it is important to delineate how gender is spontaneously assigned to robots. The present study explores spontaneous ascription of gender to a social robot with minimal visual gender cues. A total of N=63 participants partook and were engaged in interaction with the robot for 45-50 minutes. The majority (n=36) ascribed gender to the robot, mainly based on voice. The remaining participants still assigned mental capacities to the robot. The implications of the results are discussed.",

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author = "Damholdt, {Malene Flensborg} and Christina Vestergaard and Johanna Seibt",

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pages = "247--256",

editor = "Marco N{\o}rskov and Johanna Seibt and Quick, {Oliver Santiago}",

booktitle = "Culturally Sustainable Social Robotics - Proceedings of Robophilosophy 2020",

note = "Robophilosophy 2020 ; Conference date: 18-08-2020 Through 21-08-2020",

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Damholdt, MF , Vestergaard, C & Seibt, J 2020, Ascribing gender to a social robot. in M Nørskov, J Seibt & OS Quick (eds), Culturally Sustainable Social Robotics - Proceedings of Robophilosophy 2020: Proceedings of Robophilosophy 2020 August 18–21, 2020, Aarhus University and online. IOS Press, Amsterdam, Frontiers in Artificial Intelligence and Applications, vol. 335, pp. 247-256, Robophilosophy 2020, Aarhus University and online, Denmark, 18/08/2020. https://doi.org/10.3233/FAIA200921

Ascribing gender to a social robot. / Damholdt, Malene Flensborg ; Vestergaard, Christina ; Seibt, Johanna.
Culturally Sustainable Social Robotics - Proceedings of Robophilosophy 2020: Proceedings of Robophilosophy 2020 August 18–21, 2020, Aarhus University and online. ed. / Marco Nørskov; Johanna Seibt; Oliver Santiago Quick. Amsterdam: IOS Press, 2020. p. 247-256 (Frontiers in Artificial Intelligence and Applications, Vol. 335).

Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review

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T1 - Ascribing gender to a social robot

AU - Damholdt, Malene Flensborg

AU - Vestergaard, Christina

AU - Seibt, Johanna

PY - 2020/12/15

Y1 - 2020/12/15

N2 - Gender ascription to robots may lead to willingly or inadvertently repeating gender stereotypes. To reduce this risk, it is important to delineate how gender is spontaneously assigned to robots. The present study explores spontaneous ascription of gender to a social robot with minimal visual gender cues. A total of N=63 participants partook and were engaged in interaction with the robot for 45-50 minutes. The majority (n=36) ascribed gender to the robot, mainly based on voice. The remaining participants still assigned mental capacities to the robot. The implications of the results are discussed.

AB - Gender ascription to robots may lead to willingly or inadvertently repeating gender stereotypes. To reduce this risk, it is important to delineate how gender is spontaneously assigned to robots. The present study explores spontaneous ascription of gender to a social robot with minimal visual gender cues. A total of N=63 participants partook and were engaged in interaction with the robot for 45-50 minutes. The majority (n=36) ascribed gender to the robot, mainly based on voice. The remaining participants still assigned mental capacities to the robot. The implications of the results are discussed.

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DO - 10.3233/FAIA200921

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A2 - Nørskov, Marco

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PB - IOS Press

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Damholdt MF , Vestergaard C , Seibt J. Ascribing gender to a social robot. In Nørskov M, Seibt J, Quick OS, editors, Culturally Sustainable Social Robotics - Proceedings of Robophilosophy 2020: Proceedings of Robophilosophy 2020 August 18–21, 2020, Aarhus University and online. Amsterdam: IOS Press. 2020. p. 247-256. (Frontiers in Artificial Intelligence and Applications, Vol. 335). doi: 10.3233/FAIA200921

Ascribing gender to a social robot

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INSOR: Carlsberg Semper Ardens Project: What Social Robots Can and Should Do--Towards Integrative Social Robotics

Cite this

Ascribing gender to a social robot

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

INSOR: Carlsberg Semper Ardens Project: What Social Robots Can and Should Do--Towards Integrative Social Robotics

Cite this