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Contribution Details

Type Conference or Workshop Paper
Scope Contributions to practice
Published in Proceedings Yes
Title Female by Default? – Exploring the Effect of Voice Assistant Gender and Pitch on Trait and Trust Attribution
Organization Unit
  • Contribution from another University/Organization than University of Zurich
  • Suzanne Tolmeijer
  • Naim Zierau
  • Andreas Janson
  • Jalil Sebastian Wahdatehagh
  • Jan Marco Marco Leimeister
  • Abraham Bernstein
  • Yoshifumi Kitamura
  • Aaron Quigley
  • Katherine Isbister
  • Takeo Igarashi
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
  • English
ISBN 9781450380959
Page Range 1 - 7
Event Title CHI '21: CHI Conference on Human Factors in Computing Systems
Event Type conference
Event Location Yokohama Japan
Event Start Date June 8 - 2021
Event End Date June 13 - 2021
Place of Publication New York, NY, USA
Publisher ACM
Abstract Text 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.
Digital Object Identifier 10.1145/3411763.3451623
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