Voice User Interfaces (VUIs) are becoming ubiquitously available, being embedded both into everyday mobility via smartphones, and into the life of the home via 'assistant' devices. Yet, exactly how users of such devices practically thread that use into their everyday social interactions remains underexplored. By collecting and studying audio data from month-long deployments of the Amazon Echo in participants' homes-informed by ethnomethodology and conversation analysis-our study documents the methodical practices of VUI users, and how that use is accomplished in the complex social life of the home. Data we present shows how the device is made accountable to and embedded into conversational settings like family dinners where various simultaneous activities are being achieved. We discuss how the VUI is finely coordinated with the sequential organisation of talk. Finally, we locate implications for the accountability of VUI interaction, request and response design, and raise conceptual challenges to the notion of designing 'conversational' interfaces.

In this paper we investigate effects of the content of interruptions and of the time of interruption delivery on mobile phones. We review related work and report on a naturalistic quasi-experiment using experience-sampling that showed that the receptivity to an interruption is influenced by its content rather than by its time of delivery in the employed modality of delivery -SMS. We also examined the underlying variables that increase the perceived quality of content and found that the factors interest, entertainment, relevance and actionability influence people's receptivity significantly. Our findings inform system design that seeks to provide context-sensitive information or to predict interruptibility and suggest the consideration of receptivity as an extension to the way we think and reason about interruptibility.

We investigate whether opportune moments to deliver notifications surface at the endings of episodes of mobile interaction (making voice calls or receiving SMS) based on the assumption that the endings collocate with naturally occurring breakpoint in the user's primary task. Testing this with a naturalistic experiment we find that interruptions (notifications) are attended to and dealt with significantly more quickly after a user has finished an episode of mobile interaction compared to a random baseline condition, supporting the potential utility of this notification strategy. We also find that the workload and situational appropriateness of the secondary interruption task significantly affect subsequent delay and completion rate of the tasks. In situ self-reports and interviews reveal complexities in the subjective experience of the interruption, which suggest that a more nuanced classification of the particular call or SMS and its relationship to the primary task(s) would be desirable.

We present the findings from a study of how people interleave mobile phone use with conversation in pubs. Our findings, informed by ethnomethodology and conversation analysis, unpack the interactional methods through which groups of people in pubs occasioned, sustained, and disengaged from mobile device use during conversation with friends. Fundamentally, the work that is done consists of various methods of accounting for mobile device use, and displaying involvement in social interaction while the device is used. We highlight multiple examples of the nuanced ways in which interleaving is problematic in interaction, and relate our findings to the CSCW and HCI literature on collocated interaction. We conclude by considering avenues for future research, and discuss how we may support or disrupt interleaving practices through design to overcome the highlighted interactional troubles.

Major natural or man-made disasters such as Hurricane Katrina or the 9/11 terror attacks pose significant challenges for emergency responders. First, they have to develop an understanding of the unfolding event either using their own resources or through third-parties such as the local population and agencies. Second, based on the information gathered, they need to deploy their teams in a flexible manner, ensuring that each team performs tasks in The most effective way. Third, given the dynamic nature of a disaster space, and the uncertainties involved in performing rescue missions, information about the disaster space and the actors within it needs to be managed to ensure that responders are always acting on up-to-date and trusted information. Against this background, this paper proposes a novel disaster response system called HAC-ER. Thus HAC-ER interweaves humans and agents, both robotic and software, in social relationships that augment their individual and collective capabilities. To design HAC-ER, we involved end-users including both experts and volunteers in a several participatory design workshops, lab studies, and field trials of increasingly advanced prototypes of individual components of HAC-ER as well as the overall system. This process generated a number of new quantitative and qualitative results but also raised a number of new research questions. HAC-ER thus demonstrates how such Human-Agent Collectives (HACs) can address key challenges in disaster response. Specifically, we show how HAC-ER utilises crowdsourcing combined with machine learning to obtain most important situational awareness from large streams of reports posted by members of the public and trusted organisations. We then show how this information can inform human-agent teams in coordinating multi-UAV deployments, as well as task planning for responders on the ground. Finally, HAC-ER incorporates an infrastructure and the associated intelligence for tracking and utilising the provenance of information shared across the entire system to ensure its accountability. We individually validate each of these elements of HAC-ER and show how they perform against standard (non-HAC) baselines and also elaborate on the evaluation of the overall system

In this paper we unpack the use of conversational agents, or so-called intelligent personal assistants (IPAs), in multiparty conversation amongst a group of friends while they are socialising in a café. IPAs such as Siri or Google Now can be found on a large proportion of personal smartphones and tablets, and are promoted as 'natural language' interfaces. The question we pursue here is how they are actually drawn upon in conversational practice? In our work we examine the use of these IPAs in a mundane and commonplace setting and employ an ethnomethodological perspective to draw out the character of the IPA-use in conversation. Additionally, we highlight a number of nuanced practicalities of their use in multi-party settings. By providing a depiction of the nature and methodical practice of their use, we are able to contribute our findings to the design of IPAs.

Energy systems researchers are proposing a broad range of future smart energy infrastructures to promote more efficient management of energy resources. This paper considers how consumers might relate to these future smart grids within the UK. To address this challenge we exploited a combination of demonstration and animated sketches to convey the nature of a future smart energy infrastructure based on software agents. Users' reactions suggested that although they felt an obligation to engage with energy issues, they were principally disinterested. Users showed a considerable lack of trust in energy companies raising a dilemma of design. While users might welcome agents to help in engaging with complex energy infrastructures, they had little faith in those that might provide them. This suggests the need to consider how to design software agents to enhance trust in these socio-economic settings.

Background Digital contact tracing is employed to monitor and manage the spread of COVID-19. However, to be effective the system must be adopted by a substantial proportion of the population. Studies of mostly hypothetical contact tracing apps show generally high acceptance, but little is known about the drivers and barriers to adoption of deployed systems. Objective The aim of this study was to investigate adoption of and attitudes toward the NHS (National Health Service) COVID-19 smartphone app, the digital contact tracing solution in the United Kingdom. Methods An online survey based on the extended Technology Acceptance Model with the added factor of trust was carried out with a representative sample of the UK population. Statistical analysis showed adoption rates, attitudes toward and trust in the app, and compliance with self-isolation advice and highlighted differences for vulnerable populations (ie, older adults aged 65 years and over and members of Black, Asian, and minority ethnic [BAME] communities). Results A total of 1001 participants took part in the study. Around half of the participants who had heard of the NHS COVID-19 mobile phone app (490/963, 50.9%; 95% CI 47.8%-54.0%) had downloaded and kept the app, but more than one-third (345/963, 35.8%; 95% CI 32.8%-38.8%) either did not intend to download it or had deleted it. Significantly more BAME respondents than White respondents had deleted the app (16/115, 13.9%; 95% CI 11.8%-16.0%, vs 65/876, 7.4%; 95% CI 5.8%-9.0%), and significantly more older adults 65 years and over than those under 65 years did not intend to download it (44/127, 34.6%; 95% CI 31.7%-37.5%, vs 220/874, 25.2%; 95% CI 22.5%-27.9%). Broadly, one of the reasons for uptake was to help the NHS and other people, especially among older adults, although significantly fewer BAME participants agreed that they did so to help the NHS. Reported compliance with received notifications to self-isolate was high but was significantly lower than reported intended compliance without received notifications. Only one-fifth (136/699, 19.5%; 95% CI 17.0%-22.0%) of participants understood that the decision to send self-isolation notifications was automated by the app. There were a range of significantly more negative views among BAME participants, including lower trust in the NHS, while older adults were often significantly more positive. Respondents without the app reported significantly lower trust and more negative views toward the app and were less likely to report that they understood how the app works. Conclusions While compliance on the part of the approximately 50% of participants who had the app was fairly high, there were issues surrounding trust and understanding that hindered adoption and, therefore, the effectiveness of digital contact tracing, particularly among BAME communities. This study highlights that more needs to be done to improve adoption among groups who are more vulnerable to the effects of the virus in order to enhance uptake and acceptance of contact tracing apps.