Long-Term Effects of Perceived Friendship with Intelligent Voice Assistants on Usage Behavior, User Experience, and Social Perceptions

Author:

Wienrich Carolin1ORCID,Carolus Astrid2ORCID,Markus André1ORCID,Augustin Yannik2ORCID,Pfister Jan3,Hotho Andreas3

Affiliation:

1. Institute Human-Computer-Media, Psychology of Intelligent Interactive Systems, University of Wuerzburg, Oswald-Külpe-Weg 82, 97074 Wuerzburg, Germany

2. Institute Human-Computer-Media, Media Psychology, University of Wuerzburg, Oswald-Külpe-Weg 82, 97074 Wuerzburg, Germany

3. Data Science, Institute for Computer Sciences, University of Wuerzburg, 97074 Wuerzburg, Germany

Abstract

Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human–AI interactions.

Funder

Bavarian Research Institute for Digital Transformation

Publisher

MDPI AG

Subject

Computer Networks and Communications,Human-Computer Interaction

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