Investigating Users' Preferences and Expectations for Always-Listening Voice Assistants
Journal article, 2019

Many consumers now rely on different forms of voice assistants, both stand-alone devices and those built into smartphones. Currently, these systems react to specific wake-words, such as "Alexa," "Siri," or "Ok Google." However, with advancements in natural language processing, the next generation of voice assistants could instead always listen to the acoustic environment and proactively provide services and recommendations based on conversations without being explicitly invoked. We refer to such devices as "always listening voice assistants" and explore expectations around their potential use. In this paper, we report on a 178-participant survey investigating the potential services people anticipate from such a device and how they feel about sharing their data for these purposes. Our findings reveal that participants can anticipate a wide range of services pertaining to a conversation; however, most of the services are very similar to those that existing voice assistants currently provide with explicit commands. Participants are more likely to consent to share a conversation when they do not find it sensitive, they are comfortable with the service and find it beneficial, and when they already own a stand-alone voice assistant. Based on our findings we discuss the privacy challenges in designing an always-listening voice assistant.

voice assistants

always listening

survey

Author

Madiha Tabassum

The University of North Carolina at Charlotte

Tomasz Kosinski

Chalmers, Computer Science and Engineering (Chalmers), Interaction design

Alisa Frik

University of California at Berkeley

Nathan Malkin

University of California at Berkeley

Primal Wijesekera

University of California at Berkeley

Serge Egelman

University of California at Berkeley

Heather Richter Lipford

The University of North Carolina at Charlotte

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

24749567 (eISSN)

Vol. 3 4 153:1-153:23 153

Subject Categories

Interaction Technologies

Information Science

Human Computer Interaction

DOI

10.1145/3369807

More information

Latest update

1/3/2024 9