%0 Conference Paper %1 ls_leimeister %A Tolmeijer, Suzanne %A Zierau, Naim %A Janson, Andreas %A Wahdatehagh, Jalil %A Leimeister, Jan Marco %A Bernstein, Abraham %B Conference on Human Factors in Computing Systems (CHI) %C Yokohama, Japan %D 2021 %K Gender-Ambiguous_Voice Gender_Stereotypes Trust Voice_Assistants Voice_Design itegpub pub_abe pub_aja pub_jwa pub_nzi pub_sto u3bpub %R 10.1145/3411763.3451623 %T Female by Default? – Exploring the Effect of Voice Assistant Gender and Pitch on Trait and Trust Attribution %U http://pubs.wi-kassel.de/wp-content/uploads/2021/05/JML_820.pdf %X 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.

@inproceedings{ls_leimeister, 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.}, added-at = {2021-05-14T12:47:32.000+0200}, address = {Yokohama, Japan}, author = {Tolmeijer, Suzanne and Zierau, Naim and Janson, Andreas and Wahdatehagh, Jalil and Leimeister, Jan Marco and Bernstein, Abraham}, biburl = {https://www.bibsonomy.org/bibtex/2edd211d28249449cb0a6530ff77fde80/ls_leimeister}, booktitle = {Conference on Human Factors in Computing Systems (CHI)}, doi = {10.1145/3411763.3451623}, eventdate = {may 2021}, eventtitle = {Conference on Human Factors in Computing Systems (CHI)}, interhash = {d505bdf41e127f7148bd36d9138d6713}, intrahash = {edd211d28249449cb0a6530ff77fde80}, keywords = {Gender-Ambiguous_Voice Gender_Stereotypes Trust Voice_Assistants Voice_Design itegpub pub_abe pub_aja pub_jwa pub_nzi pub_sto u3bpub}, language = {english}, timestamp = {2023-02-03T10:45:49.000+0100}, title = {Female by Default? – Exploring the Effect of Voice Assistant Gender and Pitch on Trait and Trust Attribution}, url = {http://pubs.wi-kassel.de/wp-content/uploads/2021/05/JML_820.pdf}, venue = {Yokohama, Japan}, year = 2021 }