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How are people using current smart home technologies, and how do they conceptualize future ones that are more interconnected and more capable than those available today? We deployed an online survey study to 150 participants to investigate use of and opinions about smart speakers, home robots, virtual assistants, and other smart home devices.We also gauged how impressions of connected smart home devices are shaped by the way the devices interact with one another. Through a mixed-methods qualitative and quantitative approach, we found that people mostly use single devices for single functions, and have simple and brief interactions with virtual assistants. However, they imagine their future devices to have more control over the physical environment (i.e., interact with each other) and envision them interacting with people in more socially complex ways. These findings motivate design considerations and research directions for connected smart home technologies. 

Social agents and robots are moving into front-line positions in brick and mortar services, taking on roles where they directly interact with customers. These agents could potentially recognize customers to personalize service. Will customers like this, or might they feel monitored and profiled? Robots could also re-embody (move their “personality” between one body and another) in order to take on multiple roles that are typically performed by different people. Will this make customers feel more taken care of, or will it raise concerns about the robot’s competence and expertise? Our work investigates when robots should and should not recognize customers and re-embody. Our online study used storyboards to present possible future interactions between robots and customers across several different service contexts. Our findings suggest that people generally accept robots identifying customers and taking on vastly different roles. However, in some contexts, these robot behaviors seem creepy and untrustworthy. 

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. 

People take to social media to share their thoughts, joys, and sorrows. A recent popular trend has been to support and mourn people and pets that have died as well as other objects that have suffered catastrophic damage. As several popular robots have been discontinued, including the Opportunity Rover, Jibo, and Kuri, we are interested in how language used to mourn these robots compares to that to mourn people, animals, and other objects. We performed a study in which we asked participants to categorize deidentified Twitter reactions as referencing the death of a person, an animal, a robot, or another object. Most reactions were labeled as being about humans, which suggests that people use similar language to describe feelings for animate and inanimate entities. We used a natural language toolkit to analyze language from a larger set of tweets. A majority of tweets about Opportunity included second-person ("you") and gendered third-person pronouns (she/he versus it), but terms like "R.I.P" were reserved almost exclusively for humans and animals. Our findings suggest that people verbally mourn robots similarly to living things, but reserve some language for people. 

Service robots often perform their main functions in public settings, interacting with more than one person at a time. How these robots should handle the affairs of individual users while also behaving appropriately when others are present is an open question. One option is to design for flexible agent embodiment: letting agents take control of different robots as people move between contexts. Through structured User Enactments, we explored how agents embodied within a single robot might interact with multiple people. Participants interacted with a robot embodied by a singular service agent, agents that re-embody in different robots and devices, and agents that co-embody within the same robot. Findings reveal key insights about the promise of re-embodiment and co-embodiment as design paradigms as well as what people value during interactions with service robots that use personalization. 

Human-robot interactions that involve multiple robots are becoming common. It is crucial to understand how multiple robots should transfer information and transition users between them. To investigate this, we designed a 3 x 3 mixed design study in which participants took part in a navigation task. Participants interacted with a stationary robot who summoned a functional (not explicitly social) mobile robot to guide them. Each participant experienced the three types of robot-robot interaction: representative (the stationary robot spoke to the participant on behalf of the mobile robot), direct (the stationary robot delivered the request to the mobile robot in a straightforward manner), and social (the stationary robot delivered the request to the mobile robot in a social manner). Each participant witnessed only one type of robot-robot communication: silent (the robots covertly communicated), explicit (the robots acknowledged that they were communicating), or reciting (the stationary robot said the request aloud). Our results show that it is possible to instill socialness in and improve likability of a functional robot by having a social robot interact socially with it. We also found that covertly exchanging information is less desirable than reciting information aloud.