Female by Default? – Exploring the Effect of Voice Assistant Gender and Pitch on Trait and Trust Attribution

Item Type Conference or Workshop Item (Paper)
Abstract Gendered voice based on pitch is a prevalent design element in many contemporary Voice Assistants (VAs) but has shown to strengthen harmful stereotypes. Interestingly, there is a dearth of research that systematically analyses user perceptions of different voice genders in VAs. This study investigates gender-stereotyping across two different tasks by analyzing the influence of pitch (low, high) and gender (women, men) on stereotypical trait ascription and trust formation in an exploratory online experiment with 234 participants. Additionally, we deploy a gender-ambiguous voice to compare against gendered voices. Our findings indicate that implicit stereotyping occurs for VAs. Moreover, we can show that there are no significant differences in trust formed towards a gender-ambiguous voice versus gendered voices, which highlights their potential for commercial usage.
Authors Tolmeijer, Suzanne; Zierau, Naim; Janson, Andreas; Wahdatehagh, Jalil; Leimeister, Jan Marco & Bernstein, Abraham
Research Team IWI6
Journal or Publication Title Conference on Human Factors in Computing Systems (CHI)
Language English
Keywords Gender-Ambiguous Voice, Gender Stereotypes, Trust Voice Assistants, Voice Design
Subjects business studies
information management
HSG Classification contribution to scientific community
Refereed Yes
Date May 2021
Place of Publication Yokohama, Japan
Event Title Conference on Human Factors in Computing Systems (CHI)
Event Location Yokohama, Japan
Event Dates May 2021
Publisher DOI https://doi.org/10.1145/3411763.3451623
Depositing User Dr. Mahei Li
Date Deposited 14 May 2021 10:56
Last Modified 20 Jul 2022 17:45
URI: https://www.alexandria.unisg.ch/publications/263163

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Tolmeijer, Suzanne; Zierau, Naim; Janson, Andreas; Wahdatehagh, Jalil; Leimeister, Jan Marco & Bernstein, Abraham: Female by Default? – Exploring the Effect of Voice Assistant Gender and Pitch on Trait and Trust Attribution. 2021. - Conference on Human Factors in Computing Systems (CHI). - Yokohama, Japan.

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https://www.alexandria.unisg.ch/id/eprint/263163
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