'No, not that voice again!': Engaging Older Adults in Design of Anthropomorphic Voice Assistants

Conversational voice assistants are often imbued with personality and human-like characteristics (e.g., gender). While researchers have begun to examine and design for the downstream societal impacts of voice assistants encoding characteristics such as gender, we know little about other human-like characteristics such as age that are encoded in an artificial, yet, anthropomorphic voice. As older adults continue to adopt voice assistants, we brought older adults into an activity to customize human-like characteristics for their voice assistant. Our findings reveal the different stereotypes and assumptions individuals associated with voice assistant characteristics (e.g., age, gender, race). We also describe individuals' motivations behind customizing or not customizing these characteristics. We discuss how biases get encoded through our design process, marginalizing older adults and other non-dominant user groups and call for a need to examine the systemic, yet unspoken, power structures encoded in anthropomorphic technologies.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-05-02
DOI
https://doi.org/10.1145/3711039
Citations
3
Primary Topic
Technology Use by Older Adults
Type
article
Field-Weighted Citation Impact
16.78
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article

'No, not that voice again!': Engaging Older Adults in Design of Anthropomorphic Voice Assistants

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3 citations
Proceedings of the ACM on Human-Computer Interaction
Technology Use by Older Adults
16.78
article

'No, not that voice again!': Engaging Older Adults in Design of Anthropomorphic Voice Assistants

Amanda Lazar, Sheena Lewis Erete, Alisha Pradhan, Pooja Upadhyay, Shaan Chopra, Oluwaseun Sule
article en
3 citations

Abstract

Conversational voice assistants are often imbued with personality and human-like characteristics (e.g., gender). While researchers have begun to examine and design for the downstream societal impacts of voice assistants encoding characteristics such as gender, we know little about other human-like characteristics such as age that are encoded in an artificial, yet, anthropomorphic voice. As older adults continue to adopt voice assistants, we brought older adults into an activity to customize human-like characteristics for their voice assistant. Our findings reveal the different stereotypes and assumptions individuals associated with voice assistant characteristics (e.g., age, gender, race). We also describe individuals' motivations behind customizing or not customizing these characteristics. We discuss how biases get encoded through our design process, marginalizing older adults and other non-dominant user groups and call for a need to examine the systemic, yet unspoken, power structures encoded in anthropomorphic technologies.

Proceedings of the ACM on Human-Computer InteractionVol. 9(2)
New Jersey Institute of Technology (US), University of Washington (US), University of Maryland, College Park (US), Carnegie Mellon University (US)
Openalex Percentile: Top 1%
Technology Use by Older Adults
16.78
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