The increased popularity of CUIs has motivated HCI work around specific approaches to research, design, and implementation, while also reflecting on these topics. However, current research is highly fragmented and lacks critical mass around topics such as theory, methods and design. Building this critical mass is a fundamentally multidisciplinary endeavour. CUIs involve language based interaction, either through speech or text, with another agent(s) or device(s). This type of interaction not only needs to engage with traditional HCI approaches, but also to embrace methods from communicative and social sciences. This is crucial for making progress towards human-centred conversational interfaces. Along with the recent ACM SIGCHI Conversational User Interfaces conference (ACM CUI), this special issue showcases research to further solidify the foundations of the field in these areas. Below we outline some key challenges faced by the field, describe the papers in this special issue, and then outline areas for future research.

Voice assistants are fundamentally changing the way we access information. However, voice assistants still leverage little about the web beyond simple search results. We introduce Firefox Voice, a novel voice assistant built on the open web ecosystem with an aim to expand access to information available via voice. Firefox Voice is a browser extension that enables users to use their voice to perform actions such as setting timers, navigating the web, and reading a webpage’s content aloud. Through an iterative development process and use by over 12,000 active users, we find that users see voice as a way to accomplish certain browsing tasks efficiently, but struggle with discovering functionality and frequently discontinue use. We conclude by describing how Firefox Voice enables the development of novel, open web-powered voice-driven experiences.

The advancement of text-to-speech (TTS) voices and a rise of commercial TTS platforms allow people to easily experience TTS voices across a variety of technologies, applications, and form factors. As such, we evaluated TTS voices for long-form content: not individual words or sentences, but voices that are pleasant to listen to for several minutes at a time. We introduce a method using a crowdsourcing platform and an online survey to evaluate voices based on listening experience, perception of clarity and quality, and comprehension. We evaluated 18 TTS voices, three human voices, and a text-only control condition. We found that TTS voices are close to rivaling human voices, yet no single voice outperforms the others across all evaluation dimensions. We conclude with considerations for selecting text-to-speech voices for long-form content.

Researchers and the media have become increasingly interested in protest users, or people who change (protest use) or stop (protest non-use) their use of a company's products because of the company's values and/or actions. Past work has extensively engaged with the phenomenon of technology non-use but has not focused on non-use (nor changed use) in the context of protest. With recent research highlighting the potential for protest users to exert leverage against technology companies, it is important for technology stakeholders to understand the prevalence of protest users, their motivations, and the specific tactics they currently use. In this paper, we report the results of two surveys (n = 463 and n = 398) of representative samples of American web users that examine if, how, and why people have engaged in protest use and protest non-use of the products of five major technology companies. We find that protest use and protest non-use are relatively common, with 30% of respondents in 2019 reporting they were protesting at least one major tech company. Furthermore, we identify that protest users' most common motivations were (1) concerns about business models that profit from user data and (2) privacy; and the most common tactics were (1) stopping use and (2) leveraging ad blockers. We also identify common challenges and roadblocks faced by active and potential protest users, which include (1) losing social connections and (2) the lack of alternative products. Our results highlight the growing importance of protest users in the technology ecosystem and the need for further social computing research into this phenomenon. We also provide concrete design implications for existing and future technologies to support or account for protest use and protest non-use.

Voice has become a widespread and commercially viable interaction mechanism with the introduction of voice assistants (VAs), such as Amazon’s Alexa, Apple’s Siri, Google Assistant, and Microsoft’s Cortana. Despite their prevalence, we do not have a detailed understanding of how these technologies are used in domestic spaces. To understand how people use VAs, we conducted interviews with 19 users, and analyzed the log files of 82 Amazon Alexa devices, totaling 193,665 commands, and 88 Google Home Devices, totaling 65,499 commands. In our analysis, we identified music, search, and IoT usage as the command categories most used by VA users. We explored how VAs are used in the home, investigated the role of VAs as scaffolding for Internet of Things device control, and characterized emergent issues of privacy for VA users. We conclude with implications for the design of VAs and for future research studies of VAs.

Research ethics is an important and timely topic. In academia, federally regulated Institutional Review Boards (IRBs) protect participants of human subjects research, and offer researchers a mechanism to assess the ethical implications of their work. Industry research labs are not subject to the same requirements, and may lack processes for research ethics review. We describe the creation of a new ethics framework and a research ethics submission system (RESS) within Microsoft Research (MSR). This RESS is customized to the needs of web researchers. We describe our iterative development process, including our assessment of the current state of web research, developing a framework of methods based on a survey of 358 research papers; build and evaluate our system with 14 users to identify the benefits and pitfalls of full deployment; evaluate how our system matches with existing federal regulations; and, suggest next steps for supporting ethical web research.

With the rapid increase in cloud services collecting and using user data to offer personalized experiences, ensuring that these services comply with their privacy policies has become a business imperative for building user trust. However, most compliance efforts in industry today rely on manual review processes and audits designed to safeguard user data, and therefore are resource intensive and lack coverage. In this paper, we present our experience building and operating a system to automate privacy policy compliance checking in Bing. Central to the design of the system are (a) Legal ease-a language that allows specification of privacy policies that impose restrictions on how user data is handled, and (b) Grok-a data inventory for Map-Reduce-like big data systems that tracks how user data flows among programs. Grok maps code-level schema elements to data types in Legal ease, in essence, annotating existing programs with information flow types with minimal human input. Compliance checking is thus reduced to information flow analysis of Big Data systems. The system, bootstrapped by a small team, checks compliance daily of millions of lines of ever-changing source code written by several thousand developers.

The rapid adoption of location tracking and mobile social networking technologies raises significant privacy challenges. Today our understanding of people's location sharing privacy preferences remains very limited, including how these preferences are impacted by the type of location tracking device or the nature of the locations visited. To address this gap, we deployed Locaccino, a mobile location sharing system, in a four week long field study, where we examined the behavior of study participants (n=28) who shared their location with their acquaintances (n=373.) Our results show that users appear more comfortable sharing their presence at locations visited by a large and diverse set of people. Our study also indicates that people who visit a wider number of places tend to also be the subject of a greater number of requests for their locations. Over time these same people tend to also evolve more sophisticated privacy preferences, reflected by an increase in time- and location-based restrictions. We conclude by discussing the implications our findings.

Many commerce websites post privacy policies to address Internet shoppers' privacy concerns. However, few users read or understand them. Iconic privacy indicators may make privacy policies more accessible and easier for users to understand: in this paper, we examine whether the timing and placement of online privacy indicators impact Internet users' browsing and purchasing decisions. We conducted a laboratory study where we controlled the placement of privacy information, the timing of its appearance, the privacy level of each website, and the price and items being purchased. We found that the timing of privacy information had a significant impact on how much of a premium users were willing to pay for privacy. We also found that timing had less impact when users were willing to examine multiple websites. Finally, we found that users paid more attention to privacy indicators when purchasing privacy-sensitive items than when purchasing items that raised minimal privacy concerns.

Feedback is viewed as an essential element of ubiquitous computing systems in the HCI literature for helping people manage their privacy. However, the success of online social networks and existing commercial systems for mobile location sharing which do not incorporate feedback would seem to call the importance of feedback into question. We investigated this issue in the context of a mobile location sharing system. Specifically, we report on the findings of a field de-ployment of Locyoution, a mobile location sharing system. In our study of 56 users, one group was given feedback in the form of a history of location requests, and a second group was given no feedback at all. Our major contribution has been to show that feedback is an important contributing factor towards improving user comfort levels and allaying privacy concerns. Participants' privacy concerns were reduced after using the mobile location sharing system. Additionally,our study suggests that peer opinion and technical savviness contribute most to whether or not participants thought they would continue to use a mobile location technology.

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Feedback is viewed as an essential element of ubiquitous computing systems in the HCI literature for helping people manage their privacy. However, the success of online social networks and existing commercial systems for mobile location sharing which do not incorporate feedback would seem to call the importance of feedback into question. We investigated this issue in the context of a mobile location sharing system. Specifically, we report on the findings of a field de-ployment of Locyoution, a mobile location sharing system. In our study of 56 users, one group was given feedback in the form of a history of location requests, and a second group was given no feedback at all. Our major contribution has been to show that feedback is an important contributing factor towards improving user comfort levels and allaying privacy concerns. Participants' privacy concerns were reduced after using the mobile location sharing system. Additionally,our study suggests that peer opinion and technical savviness contribute most to whether or not participants thought they would continue to use a mobile location technology.

In high-tech businesses ranging from Internet service providers to e-commerce websites and music stores like Apple iTun-es, there is considerable potential for collecting personal information about customers, monitoring their usage habits, or even exerting control over their behavior - for example, restricting what can be done with a purchased song. A privacy ceiling is an effective limit to these privacy intrusions, created by the perceived or actual legal liability of possessing too much information or control. As we show in this paper, the risk is not simply that of customer backlash, but liability for a customer's actions, owing to the ability to identify, report, or prevent them from taking those actions. In some cases high-tech businesses have been obligated to divulge their store of personal information or to police their customers at the demand of third parties; this unwanted result derives from the possession of too much information or control for the company's own good. We argue that vicarious infringement liability in particular creates a privacy ceiling, a point beyond which there is no economic incentive to intrude on a user's privacy; and, indeed, there is an incentive to architect one's business so that such intrusions are difficult or impossible.