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Long-term effects of perceived friendship with intelligent voice assistants on usage behavior, user experience, and social perceptions

Please always quote using this URN: urn:nbn:de:bvb:20-opus-313552
  • 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 socialSocial 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.show moreshow less

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Metadaten
Author: Carolin Wienrich, Astrid Carolus, André Markus, Yannik Augustin, Jan Pfister, Andreas Hotho
URN:urn:nbn:de:bvb:20-opus-313552
Document Type:Journal article
Faculties:Fakultät für Mathematik und Informatik / Institut für Informatik
Fakultät für Humanwissenschaften (Philos., Psycho., Erziehungs- u. Gesell.-Wissensch.) / Institut Mensch - Computer - Medien
Language:English
Parent Title (English):Computers
ISSN:2073-431X
Year of Completion:2023
Volume:12
Issue:4
Article Number:77
Source:Computers (2023) 12:4, 77. https://doi.org/10.3390/computers12040077
DOI:https://doi.org/10.3390/computers12040077
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Tag:anthropomorphism; human–computer interaction; intelligent voice assistant; long-term analysis; smart speaker; social interaction; social relationship; social role
Release Date:2024/03/11
Date of first Publication:2023/04/13
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International