Smart voice assistants such as Amazon Alexa and Google Home are becoming increasingly pervasive in our everyday environments. Despite their benefits, their miniaturized and embedded cameras and microphones raise important privacy concerns related to surveillance and eavesdropping. Recent work on the privacy concerns of people in the vicinity of these devices has highlighted the need for 'tangible privacy', where control and feedback mechanisms can provide a more assured sense of whether the camera or microphone is 'on' or 'off'. However, current designs of these devices lack adequate mechanisms to provide such assurances. To address this gap in the design of smart voice assistants, especially in the case of disabling microphones, we evaluate several designs that incorporate (or not) tangible control and feedback mechanisms. By comparing people's perceptions of risk, trust, reliability, usability, and control for these designs in a between-subjects online experiment (N=261), we find that devices with tangible built-in physical controls are perceived as more trustworthy and usable than those with non-tangible mechanisms. Our findings present an approach for tangible, assured privacy especially in the context of embedded microphones.
Seeing is Believing: Improving the Perceived Trust in Visually Embodied Alexa in Augmented Reality
Voice-activated Intelligent Virtual Assistants (IVAs) such as Amazon
Alexa offer a natural and realistic form of interaction that pursues the
level of social interaction among real humans. The user experience
with such technologies depends to a large degree on the perceived
trust in and reliability of the IVA. In this poster, we explore the
effects of a three-dimensional embodied representation of Amazon
Alexa in Augmented Reality (AR) on the user’s perceived trust in
her being able to control Internet of Things (IoT) devices in a smart
home environment. We present a preliminary study and discuss the
potential of positive effects in perceived trust due to the embodied
representation compared to a voice-only condition.
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- Award ID(s):
- 1800961
- NSF-PAR ID:
- 10105860
- Date Published:
- Journal Name:
- 17th IEEE International Symposium on Mixed and Augmented Reality
- Page Range / eLocation ID:
- 204 to 205
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ISMAR-Adjunct.2018.00067
