Ignorance is Bliss? The Effect of Explanations on Perceptions of Voice Assistants. Seymour, W. & Such, J. Proceedings of the ACM on Human-Computer Interaction, 2023. Publisher: Association for Computing Machinery Type: Article
Ignorance is Bliss? The Effect of Explanations on Perceptions of Voice Assistants [link]Paper  doi  abstract   bibtex   
Voice assistants offer a convenient and hands-free way of accessing computing in the home, but a key problem with speech as an interaction modality is how to scaffold accurate mental models of voice assistants, a task complicated by privacy and security concerns. We present the results of a survey of voice assistant users (n=1314) measuring trust, security, and privacy perceptions of voice assistants with varying levels of online functionality explained in different ways. We then asked participants to re-explain how these voice assistants worked, showing that while privacy explanations relieved privacy concerns, trust concerns were exacerbated by trust explanations. Participants' trust, privacy, and security perceptions also distinguished between first party online functionality from the voice assistant vendor and third party online functionality from other developers, and trust in vendors appeared to operate independently from device explanations. Our findings point to the use of analogies to guide users, targeting trust and privacy concerns, key improvements required from manufacturers, and implications for competition in the sector. © 2023 ACM.
@article{seymour_ignorance_2023,
	title = {Ignorance is {Bliss}? {The} {Effect} of {Explanations} on {Perceptions} of {Voice} {Assistants}},
	volume = {7},
	issn = {25730142},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85153928887&doi=10.1145%2f3579497&partnerID=40&md5=e90f6b633f3ff53c9f5fa49cb9ea6e05},
	doi = {10.1145/3579497},
	abstract = {Voice assistants offer a convenient and hands-free way of accessing computing in the home, but a key problem with speech as an interaction modality is how to scaffold accurate mental models of voice assistants, a task complicated by privacy and security concerns. We present the results of a survey of voice assistant users (n=1314) measuring trust, security, and privacy perceptions of voice assistants with varying levels of online functionality explained in different ways. We then asked participants to re-explain how these voice assistants worked, showing that while privacy explanations relieved privacy concerns, trust concerns were exacerbated by trust explanations. Participants' trust, privacy, and security perceptions also distinguished between first party online functionality from the voice assistant vendor and third party online functionality from other developers, and trust in vendors appeared to operate independently from device explanations. Our findings point to the use of analogies to guide users, targeting trust and privacy concerns, key improvements required from manufacturers, and implications for competition in the sector. © 2023 ACM.},
	language = {English},
	number = {CSCW1},
	journal = {Proceedings of the ACM on Human-Computer Interaction},
	author = {Seymour, William and Such, Jose},
	year = {2023},
	note = {Publisher: Association for Computing Machinery
Type: Article},
	keywords = {Ai assistant, Cognitive systems, Explanation, Hands-free, Mental model, Privacy and security, Privacy concerns, Scaffolds, Security and privacy, Third parties, Trust, Voice assistant},
}

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