Investigating Users’ Preferences and Expectations for Always-Listening Voice Assistants MADIHA TABASSUM, University of North Carolina at Charlotte, USA TOMASZ KOSIŃSKI, Chalmers University of Technology, Sweden ALISA FRIK, University of California, Berkeley / ICSI, USA NATHAN MALKIN, University of California, Berkeley, USA 153 PRIMAL WIJESEKERA, University of California, Berkeley / ICSI, USA SERGE EGELMAN, University of California, Berkeley / ICSI, USA HEATHER RICHTER LIPFORD, University of North Carolina at Charlotte, USA 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. Basedonour findings we discuss the privacy challenges in designing an always-listening voice assistant. CCS Concepts: • Human-centered computing → Personal digital assistants; User studies. Additional Key Words and Phrases: voice assistants, always listening, survey ACM Reference Format: Madiha Tabassum, Tomasz Kosiński, Alisa Frik, Nathan Malkin, Primal Wijesekera, Serge Egelman, and Heather Richter Lipford. 2019. Investigating Users’ Preferences and Expectations for Always-Listening Voice Assistants. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3, 4, Article 153 (December 2019), 23 pages. https://doi.org/10.1145/3369807 Authors’ addresses: Madiha Tabassum, University of North Carolina at Charlotte, Charlotte, NC, USA, [email protected]; Tomasz Kosiński, Chalmers University of Technology, Gothenburg, Sweden, [email protected]; Alisa Frik, University of California, Berkeley / ICSI, Berkeley, CA, USA, [email protected]; Nathan Malkin, University of California, Berkeley, Berkeley, CA, USA, [email protected]; Primal Wijesekera, University of California, Berkeley / ICSI, Berkeley, CA, USA, [email protected]; Serge Egelman, University of California, Berkeley / ICSI, Berkeley, CA, USA, [email protected]; Heather Richter Lipford, University of North Carolina at Charlotte, Charlotte, NC, USA, [email protected]. 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Almost 41% of adults in the U.S. have access to a stand-alone “smart speaker” in their homes [34]. Currently, these systems respond when explicitly invoked by a specific wake-word—such as “Alexa,” “Siri,” or “Ok Google”—and serve common functions such as answering questions and controlling other connected devices. Prominent players in the industry are trying to make voice assistants even more seamless. For instance, Google Home and Alexa offer a continued conversation feature (or “follow-up mode”) to allow users to make follow-up requests after the first command without repeating the wake-word [12, 13]. Alexa also has a feature called Drop In, which allows whitelisted users to begin an audio or video call without the other party manually picking up the call [2], effectively allowing remote parties to listen at any time. Looking forward, Amazon and Google have patented the ability of voice assistants to automatically extract keywords from ambient speech and use that to provide targeted ads to users [39]. With advancements in natural language processing technology, we can therefore expect that the next generation of voice assistants will offer proactive assistance based on the audio signals and conversations acquired from the acoustic environment. In other words, they will work without being explicitly invoked by users [29]. For example, future voice assistants could recognize when a user is talking about dinner plans and may suggest updating the calendar, inviting friends, or making a reservation—or even doing all of these things automatically. Allowing devices to utilize the entirety of a conversation, including its context, will potentially enable fully-fledged assistants that can fluidly support users in their daily lives without detracting from their interactions with others. Despite the potential to help users in their daily activities, always-listening voice assistants are virtually certain to raise privacy concerns. First, some consumers are resistant to adopting even the current keyword- triggered voice assistants, because they are uncomfortable with the devices’ audio-data collection during regular use [10, 18] and in the background [32]. Continuous listening is likely to deepen and extend that concern since all conversations may be subject to recording, and because these recordings could be available to third parties. Second, compared with keyword-triggered listening, there is a higher chance of sensitive information being recorded without users’ awareness. Users have expressed discomfort over controlling unprompted assistance [3] and unintended exposure of personal data [27] in such an environment. Third, these devices are more likely to violate users’ expectations of territorial privacy and embodied self-image. Territorial privacy represents the right of a person to determine individually when and how other entities are allowed to participate in his or her personal territory [16]. With keyword-triggered assistants, users actively control when the device is on. With devices that listen passively (i.e., without interrupting the conversation), users are likely to perceive less control over their private territory. With continuous access to audio data, it will be possible to identify and track people in their private spaces and make inferences about family dynamics, relationships, preferences, behaviors, and more. Moreover, research has shown that people tend to allow access to their data when it is used for a goal that they find beneficial or when the data is not sensitive in general[30]. On the other hand, people are more likely to deny data collection if they think the data is very personal or sensitive [30]. In order to understand how always-listening devices may fit into users’ day-to-day lives, it is important to investigate the trade-offs between the sensitivityof a conversation, the concerns about sharing its recording, and the benefits users receive. Specifically, it is critical to understand: what are people’s privacy expectations in an always-listening environment? What factors affect those expectations and the decision to adopt this technology? What benefits and services do people expect in exchange for sharing their conversations? What concerns do they have regarding using such a device? Our goal is to inform the design of always-listening systems that respect users’ privacy expectations. In this paper, we therefore investigate the following research questions: • What services do users expect always-listening voice assistants to provide based on their conversations? Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., Vol. 3, No. 4, Article 153. Publication date: December 2019. Investigating Users’ Preferences and Expectations for Always-Listening Voice Assistants • 153:3 • How useful are these potential services? Do people feel comfortable with them? • How do factors such as demographics, perceived comfort, and service usefulness affect users’ intentions to allow the voice assistant to access their conversations in exchange for services? To answer these questions, we conducted an online survey, in which 178 participants listened to 2-3 minute conversation snippets and answered questions regarding the services they could envision an always-listening voice assistant providing to them. Our results reveal that participants expect to receive a range of services, including those already available from existing voice assistants, as well as services unique to an always-listening device;