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Intelligent voice assistants, and the thirdparty apps (aka “skills” or “actions”) that power them, are increasing in popularity and beginning to experiment with the ability to continuously listen to users. This paper studies how privacy concerns related to such always-listening voice assistants might affect consumer behavior and whether certain privacy mitigations would render them more acceptable. To explore these questions with more realistic user choices, we built an interactive app store that allowed users to install apps for a hypothetical always-listening voice assistant. In a study with 214 participants, we asked users to browse the app store and install apps for different voice assistants that offered varying levels of privacy protections. We found that users were generally more willing to install continuously-listening apps when there were greater privacy protections, but this effect was not universally present. The majority did not review any permissions in detail, but still expressed a preference for stronger privacy protections. Our results suggest that privacy factors into user choice, but many people choose to skip this information. 

Intelligent voice assistants may soon become proactive, offering suggestions without being directly invoked. Such behavior increases privacy risks, since proactive operation requires continuous monitoring of conversations. To mitigate this problem, our study proposes and evaluates one potential privacy control, in which the assistant requests permission for the information it wishes to use immediately after hearing it. To find out how people would react to runtime permission requests, we recruited 23 pairs of participants to hold conversations while receiving ambient suggestions from a proactive assistant, which we simulated in real time using the Wizard of Oz technique. The interactive sessions featured different modes and designs of runtime permission requests and were followed by in-depth interviews about people's preferences and concerns. Most participants were excited about the devices despite their continuous listening, but wanted control over the assistant's actions and their own data. They generally prioritized an interruption-free experience above more fine-grained control over what the device would hear. 

Abstract As devices with always-on microphones located in people’s homes, smart speakers have significant privacy implications. We surveyed smart speaker owners about their beliefs, attitudes, and concerns about the recordings that are made and shared by their devices. To ground participants’ responses in concrete interactions, rather than collecting their opinions abstractly, we framed our survey around randomly selected recordings of saved interactions with their devices. We surveyed 116 owners of Amazon and Google smart speakers and found that almost half did not know that their recordings were being permanently stored and that they could review them; only a quarter reported reviewing interactions, and very few had ever deleted any. While participants did not consider their own recordings especially sensitive, they were more protective of others’ recordings (such as children and guests) and were strongly opposed to use of their data by third parties or for advertising. They also considered permanent retention, the status quo, unsatisfactory. Based on our findings, we make recommendations for more agreeable data retention policies and future privacy controls. 

Intelligent voice assistants (IVAs) and other voice-enabled devices already form an integral component of the Internet of Things and will continue to grow in popularity. As their capabilities evolve, they will move beyond relying on the wake-words today's IVAs use, engaging instead in continuous listening. Though potentially useful, the continuous recording and analysis of speech can pose a serious threat to individuals' privacy. Ideally, users would be able to limit or control the types of information such devices have access to. But existing technical approaches are insufficient for enforcing any such restrictions. To begin formulating a solution, we develop a systematic methodology for studying continuous-listening applications and survey architectural approaches to designing a system that enhances privacy while preserving the benefits of always-listening assistants.