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.

How might the capabilities of voice assistants several decades in the future shape human society? To anticipate the space of possible futures for voice assistants, we asked 149 participants to each complete a story based on a brief story stem set in the year 2050 in one of five different contexts: the home, doctor's office, school, workplace, and public transit. Story completion as a method elicits participants' visions of possible futures, unconstrained by their understanding of current technological capabilities, but still reflective of current sociocultural values. Through a thematic analysis, we find these stories reveal the extremes of the capabilities and concerns of today's voice assistants---and artificial intelligence---such as improving efficiency and offering instantaneous support, but also replacing human jobs, eroding human agency, and causing harm through malfunction. We conclude by discussing how these speculative visions might inform and inspire the design of voice assistants and other artificial intelligence.

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.

This paper investigates whether voice assistants can play a useful role in the specialized work-life of the knowledge worker (in a biology lab). It is motivated both by promising advances in voice-input technology, and a long-standing vision in the community to augment scientific processes with voice-based agents. Through a reflection on our design process and a limited but fully functional prototype, Vitro, we find that scientists wanted a voice-enabled device that acted not a lab assistant, but lab equipment. Second, we discovered that such a device would need to be deeply embedded in the physical and social space in which it served scientists. Finally, we discovered that scientists preferred a device that supported their practice of "careful deviation" from protocols in their lab work. Through this research, we contribute implications for the design of voice-enabled systems in workplace settings.

When a smart device talks, what should its voice sound like? Voice-enabled devices are becoming a ubiquitous presence in our everyday lives. Simultaneously, speech synthesis technology is rapidly improving, making it possible to generate increasingly varied and realistic computerized voices. Despite the flexibility and richness of expression that technology now affords, today's most common voice assistants often have female-sounding, polite, and playful voices by default. In this paper, we examine the social consequences of voice design, and introduce a simple research framework for understanding how voice affects how we perceive and interact with smart devices. Based on the foundational paradigm of computers as social actors, and informed by research in human-robot interaction, this framework demonstrates how voice design depends on a complex interplay between characteristics of the user, device, and context. Through this framework, we propose a set of guiding questions to inform future research in the space of voice design for smart devices.

Peer review asks novices to take on an evaluator's role, yet novices often lack the perspective to accurately assess the quality of others' work. To help learners give feedback on their peers' work through an expert lens, we present the Juxtapeer peer review system for structured comparisons. We build on theories of learning through contrasting cases, and contribute the first systematic evaluation of comparative peer review. In a controlled experiment, 476 consenting learners across four courses submitted 1,297 submissions, 4,102 reviews, and 846 self assessments. Learners assigned to compare submissions wrote reviews and self-reflections that were longer and received higher ratings from experts than those who evaluated submissions one at a time. A second study found that a ranking of submissions derived from learners' comparisons correlates well with staff ranking. These results demonstrate that comparing algorithmically-curated pairs of submissions helps learners write better feedback.

Massive online classes are global and diverse. How can we harness this diversity to improve engagement and learning? Currently, though enrollments are high, students' interactions with each other are minimal: most are alone together. This isolation is particularly disappointing given that a global community is a major draw of online classes. This paper illustrates the potential of leveraging geographic diversity in massive online classes. We connect students from around the world through small-group video discussions. Our peer discussion system, Talkabout, has connected over 5,000 students in fourteen online classes. Three studies with 2,670 students from two classes found that globally diverse discussions boost student performance and engagement: the more geographically diverse the discussion group, the better the students performed on later quizzes. Through this work, we challenge the view that online classes are useful only when in-person classes are unavailable. Instead, we demonstrate how diverse online classrooms can create benefits that are largely unavailable in a traditional classroom.

In the physical classroom, peer interactions motivate students and expand their perspective. We suggest that synchronous peer interaction can benefit massive online courses as well. Talkabout organizes students into video discussion groups and allows instructors to determine group composition and discussion content. Using Talkabout, students pick a discussion time that suits their schedule. The system groups the students into small video discussions based on instructor preferences such as gender or geographic balance. To date, 2,474 students in five massive online courses have used Talkabout to discuss topics ranging from prejudice to organizational theory. Talkabout discussions are diverse: in one course, the median six-person discussion group had students from four different countries. Students enjoyed discussing in these diverse groups: the average student participated for 66 minutes, twice the course requirement. Students in more geographically distributed groups also scored higher on the final, suggesting that distributed discussions have educational value.