An Empirical Study on Expectation of Relationship Between Human and Smart Devices—With Smart Speaker as an Example

Wu, Shao-Ling; He, Sinan; Peng, Yu; Li, Weiying; Zhou, Moli; Guan, Daisong

doi:10.1109/dsc.2019.00090

Cited by 7 publications

(3 citation statements)

References 5 publications

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“…In other words, different expectations are attributed to the holder depending on the assigned social role. In addition, previous studies on AI-based technologies found that users attribute social roles to technology, which can affect their expectations and perceptions [8,30]. For example, users of IVAs often assign them either a tool-based role (e.g., assistant, service provider, tool) or a friend-based role (e.g., friend, family member, companion) [31].…”

Section: Voice Assistants As Social Actors In User Relationshipsmentioning

confidence: 99%

“…As the social relationships with voice assistants become more established, their impact on interactions, user experience, and self-disclosure becomes more apparent [5][6][7]. For example, a study by Wu, et al [8] showed that users assign different roles to IVAs and that this attribution, in turn, determines the expectations and usage patterns. Consistent with other research [9,10], Wu, He, Peng, Li, Zhou, and Guan [8] found that one of the most common roles assigned to IVAs was that of a "friend".…”

Section: Introductionmentioning

confidence: 99%

“…For example, a study by Wu, et al [8] showed that users assign different roles to IVAs and that this attribution, in turn, determines the expectations and usage patterns. Consistent with other research [9,10], Wu, He, Peng, Li, Zhou, and Guan [8] found that one of the most common roles assigned to IVAs was that of a "friend". Therefore, the present study precisely focuses on the attribution of IVAs as friends.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

et al. 2023

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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.

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Section: Voice Assistants As Social Actors In User Relationshipsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

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Influencing Factors for Users’ Privacy and Security Protection Behavior in Smart Speakers: Insights from a Swiss User Study

Ebbers

Karaboga

2023

Lecture Notes in Computer Science

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Smart speakers pose several risks to security and privacy, which users can counter with protective measures. This paper investigates the factors contributing to the adoption of protective measures by smart speaker users. Using survey data from Swiss participants, we first captured four different combinations of users with (no) concerns and (no) measures. We then used six factors to examine which of these influence protective behavior. Our findings reveal that whether or not protective measures are taken is affected by the usage context, usage duration, gender, opinion toward emotion recognition, and reasons for acquisition, but not by model/manufacturer, age and education level. With our results, we want to contribute to the ongoing discussion about influencing factors on concerns and protective measures, using the smart speaker domain as an example.

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Enabling progressive system integration for AIoT and speech-based HCI through semantic-aware computing

Chang

2021

J Supercomput

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An Empirical Study on Expectation of Relationship Between Human and Smart Devices—With Smart Speaker as an Example

Cited by 7 publications

References 5 publications

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

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

Influencing Factors for Users’ Privacy and Security Protection Behavior in Smart Speakers: Insights from a Swiss User Study

Enabling progressive system integration for AIoT and speech-based HCI through semantic-aware computing

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