Female by Default? – Exploring the Effect of Voice Assistant Gender and Pitch on Trait and Trust Attribution
Journal
Conference on Human Factors in Computing Systems (CHI)
Type
conference paper
Date Issued
2021-05
Author(s)
Tolmeijer, Suzanne
Wahdatehagh, Jalil
Bernstein, Abraham
Research Team
IWI6
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.
Language
English
Keywords
Gender-Ambiguous Voice
Gender Stereotypes
Trust Voice Assistants
Voice Design
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher place
Yokohama, Japan
Event Title
Conference on Human Factors in Computing Systems (CHI)
Event Location
Yokohama, Japan
Event Date
May 2021
Subject(s)
Division(s)
Eprints ID
263163
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JML_820.pdf
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Format
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