Digital technologies play a role in the cognitive work of managing households, yet much of this labour remains invisible, making it harder to share, delegate, or value. Existing tools support household tasks but focus on visible activities such as chores or planning, leaving unclear how hidden domestic labour is supported. To address this, we surveyed 50 participants and conducted qualitative analysis. We found that value-driven labour, such as managing household vision and values, shapes other labours yet remains least visible and hardest to delegate. Domains like inclusion and special events appear salient in everyday life yet remain largely unsupported by current tools. We found that while family management is collaborative, most tools remain oriented to single users. We contribute an empirical mapping of digital support and gaps across six forms of family management labour, and offer a foundation for anticipating how emerging domestic technologies may support or inadvertently reshape this work.

Bossware, software that monitors worker activity, is a common feature of workplaces. What do workers know about these tools and how they relate to their rights at work? We explored this question through two studies. Study 1 surveyed 100 workers to assess their understanding of work monitoring terminology. Participants were confident in their knowledge of key terms but struggled to accurately define them. Study 2 explored awareness of legal protection in relation to work monitoring through 19 semi-structured online interviews. We found that awareness varied with industry and work role, but was generally low and lacked certainty. Participants were largely skeptical of the use of bossware, questioning its necessity. Limited knowledge of monitoring terminology and legal protection at work further weakens workers' ability to notice and challenge the use of monitoring tools in their workplaces. We finish by speculating on whether educating workers about bossware and workplace rights would help.

I argue that epistemologies of workplace surveillance are shifting in fundamental ways, and so critiques must shift accordingly. I begin the paper by relating Scientific Management to Human-Centred Computing’s ways of knowing through a study of ‘metaverse’ virtual reality workplaces. From this, I develop two observations. The first is that today’s workplace measurement science does not resemble the science that Taylor developed for Scientific Management. Contemporary workplace science is more passive, more intermediated and less controlled. The second observation is that new forms of workplace measurement challenge the norms of empirical science. Instead of having credentialed human witnesses observe phenomena and agree facts about them, we instead make outsourced, uncredentialed stochastic machine witnesses responsible for producing facts about work. With these observations in mind, I assert that critiques of workplace surveillance still framed by Taylorism will not be fit for interrogating workplace surveillance practices of the future.

Research suggests that the temporal flexibility advertised to crowdworkers by crowdsourcing platforms is limited by both client-imposed constraints (e.g., strict completion times) and crowdworkers’ tooling practices (e.g., multitasking). In this article, we explore an additional contributor to workers’ limited temporal flexibility: the design of crowdsourcing platforms, namely requiring crowdworkers to be ‘on call’ for work. We conducted two studies to investigate the impact of having to be ‘on call’ on workers’ schedule control and job control. We find that being ‘on call’ impacted (1) participants’ ability to schedule their time and stick to planned work hours, and (2) the pace at which participants worked and took breaks. The results of the two studies suggest that the ‘on-demand’ nature of crowdsourcing platforms can limit workers’ temporal flexibility by reducing schedule control and job control. We conclude the article by discussing the implications of the results for (a) crowdworkers, (b) crowdsourcing platforms, and (c) the wider platform economy.

Abstract Over the past few decades, a small but growing group of people have worked remotely from their homes. With the arrival of the coronavirus pandemic, millions of people found themselves joining this group overnight. In this position paper, we examine the kinds of work that ‘went remote’ in response to the pandemic, and consider the ways in which this transition was influenced by (and in turn came to influence) contemporary trends in digital workplace measurement and evaluation. We see that employers appeared reluctant to let certain classes of employee work remotely. When the pandemic forced staff home, employers compensated by turning to digital surveillance tools, even though, as we argue, these tools seem unable to overcome the significant conceptual barriers to understanding how people are working. We also observed that, in the United Kingdom context, the pandemic didn’t mean remote work for a significant proportion of the population. We assert that, to maximize its impact, ‘future of work’ research in human-centred computing must be more inclusive and representative of work, rather than focusing on the experiences of knowledge workers and those involved in new forms of work.

Data collection is often a laborious enterprise that forms part of the wider craft skill of doing research. In this essay, I try to understand whether parts of research processes in Human-Centred Computing (HCC) have been commodified, with a particular focus on data collection. If data collection has been commodified, do researchers act as producers or consumers in the process? And if researchers are consumers, has data collection become a consumption experience? If so, what are the implications of this? I explore these questions by considering the status of craft and consumption in the research process and by developing examples of consumption experiences. I note the benefits of commodity research artefacts, while highlighting the potentially deleterious effects consumption experiences could have on our ability to generate insights into the relations between people and technology. I finish the paper by relating consumption experiences to contemporary issues in HCC and lay out a programme of empirical work that would help answer some of the questions this paper raises.

Despite the many technological advances over the past few decades designed to support remote working (also referred to as working from home, teleworking, etc.), prior to 2020 there had not been a l...

People integrate digital services into their day-to-day lives, often with the assumption that they will always be available. What happens when these services close down? The introduction of services might be carefully planned, but their closure may not benefit from the same degree of consideration. A more developed understanding of the effects of closures might make it possible to minimize negative consequences for users. This paper builds on sustainability, digital memories, and collaborative-work research through an empirical investigation of service closure. Fifty-five participants completed a questionnaire that solicited experiences of service closure and attitudes toward prospective closure. Through a qualitative analysis of participant responses, we synthesized six themes that reflected the practical and emotional effects of service closure on people: disempowerment, disconnection, loss of capability, trust, time and effort, and notice periods. We make suggestions for ways that service features related to these themes might be managed during closure, but also identify less tractable challenges: as part of this investigation, we introduce and develop the concept of service patinas to describe the important but entirely service-bound data that contextualize digital artefacts.

Although e-mail interfaces have not changed much in the past decade, how we manage our inbox has changed a lot, as a result of the growing number of messages we receive (The Radicati Group, 2015) a...

Crowdworkers receive no formal training for managing their tasks, time or working environment. To develop tools that support such workers, an understanding of their preferences and the constraints they are under is essential. We asked 317 experienced Amazon Mechanical Turk workers about factors that influence their task and time management. We found that a large number of the crowdworkers score highly on a measure of polychronicity; this means that they prefer to frequently switch tasks and happily accommodate regular work and non-work interruptions. While a preference for polychronicity might equip people well to deal with the structural demands of crowdworking platforms, we also know that multitasking negatively affects workers' productivity. This puts crowdworkers' working preferences into conflict with the desire of requesters to maximize workers' productivity. Combining the findings of prior research with the new knowledge obtained from our participants, we enumerate practical design options that could enable workers, requesters and platform developers to make adjustments that would improve crowdworkers' experiences.

Recent scandals involving data from participatory research have contributed to broader public concern about online privacy. Such concerns might make people more reluctant to participate in research that asks them to volunteer personal data, compromising many researchers' data collection. We tested several motivational messages that encouraged participation in a citizen science project. We measured people's willingness to disclose personal information. While participants were less likely to share sensitive data than neutral data, disclosure behaviour was not affected by attitudes to privacy. Importantly, we found that citizen scientists who were exposed to a motivational message that emphasised 'learning' were more likely to share sensitive information than those presented with other types of motivational cues. Our results suggest that priming individuals with motivational messages can increase their willingness to contribute personal data to a project, even if the request pertains to sensitive information.

The use of emoji in digital communication can convey a wealth of emotions and concepts that otherwise would take many words to express. Emoji have become a popular form of communication, with researchers claiming emoji represent a type of "ubiquitous language" that can span different languages. In this paper however, we explore how emoji are also used in highly personalised and purposefully secretive ways. We show that emoji are repurposed for something other than their "intended" use between close partners, family members and friends. We present the range of reasons why certain emoji get chosen, including the concept of "emoji affordance" and explore why repurposing occurs. Normally used for speed, some emoji are instead used to convey intimate and personal sentiments that, for many reasons, their users cannot express in words. We discuss how this form of repurposing must be considered in tasks such as emoji-based sentiment analysis.

Mobile devices are increasingly used while watching video, both as a secondary device and for dedicated viewing. However, devices frequently issue notifications that can interrupt viewing. This study investigated the effect of interruptions from notifications on viewer immersion. Participants watched 10 minutes of a movie without notifications, and 10 minutes while receiving message notifications. There were two participant groups: one watched video on a 30-inch monitor with messages sent to a separate smartphone; while another watched on a smartphone while also receiving messages on it. Viewer immersion was assessed after each condition via questionnaire. We also considered message response times. Results showed that immersion scores were lower when the video was interrupted with notifications, regardless of viewing device. Message response times were fastest when using the phone as a secondary device. Our results suggest that device-driven interruptions should be minimised for an immersive film experience.

Data-entry is a common activity that is usually performed accurately. When errors do occur though, people are poor at spotting them even if they are told to check their input. We considered whether making people pause for a brief moment before confirming their input would make them more likely to check it. We ran a lab experiment to test this idea. We found that task lockouts encouraged checking. Longer lockout durations made checking more likely. We ran a second experiment on a crowdsourcing platform to find out whether lockouts would still be effective in a less controlled setting. We discovered that longer lockouts induced workers to switch to other activities. This made the lockouts less effective. To be useful in practice, the duration of lockouts needs to be carefully calibrated. If lockouts are too brief they will not encourage checking. If they are too long they will induce switching.

The Internet of Things is connecting an ever-increasing number of devices. These devices often require access to personal information, but their meagre user interfaces usually do not permit traditional modes of authentication. On such devices, one-time pairing codes are often used instead. This pairing process can involve transcribing randomly generated alphanumeric codes, which can be frustrating, slow and error-prone. In this paper, we present an improved pairing method that uses sets of English words instead of random strings. The word method, although longer in terms of character length, allows users to pair devices more quickly, whilst still maintaining the complexity necessary for secure interactions.

Link-shortening services save space and make the manual entry of URLs less onerous. Short links are often included on printed materials so that people using mobile devices can quickly enter URLs. Although mobile transcription is a common use-case, link-shortening services generate output that is poorly suited to entry on mobile devices: links often contain numbers and capital letters that require time consuming mode switches on touch screen keyboards. With the aid of computational modeling, we identified problems with the output of a link-shortening service, bit.ly. Based on the results of this modeling, we hypothesized that longer links that are optimized for input on mobile keyboards would improve link entry speeds compared to shorter links that required keyboard mode switches. We conducted a human performance study that confirmed this hypothesis. Finally, we applied our method to a selection of different non-word mobile data-entry tasks. This work illustrates the need for service design to fit the constraints of the devices people use to consume services.

Obtaining high-quality data from crowds can be difficult if contributors do not give tasks sufficient attention. Attention checks are often used to mitigate this problem, but, because the roots of inattention are poorly understood, checks often compel attentive contributors to complete unnecessary work. We investigated a potential source of inattentiveness during crowdwork: multitasking. We found that workers switched to other tasks every 5 minutes, on average. There were indications that increasing switch frequency negatively affected performance. To address this, we tested an intervention that encouraged workers to stay focused on our task after multitasking was detected. We found that our intervention reduced the frequency of task switching. It also improves on existing attention checks because it does not place additional demands on workers who are already focused. Our approach shows that crowds can help to overcome some of the limitations of laboratory studies by affording access to naturalistic multitasking behavior.

Number entry is a common task in many domains. In safety-critical environments such as air traffic control or on hospital wards, incorrect number entry can have serious harmful consequences. Research has investigated how interface designs can help prevent users from making number entry errors. In this paper, we present an experimental evaluation of two possible interface designs aimed at helping users detect number entry errors using the idea of a checksum: an additional (redundant) number that is related to the to-be-entered numbers in such a way that it is sufficient to verify the correctness of the checksum, as opposed to checking each of the entered numbers. The first interface requires users to check their own work with the help of the checksum; the second requires the user to enter the checksum along with the other numbers so that the system can do the checking. In each case, two numbers needed to be entered, while the third number served as a checksum. With the first interface, users caught only 36% of their errors. The second interface resulted in all errors being caught, but the need to enter the checksum increased entry time by 46%. When participants were allowed to choose between the two interfaces, they chose the second interface in only 12% of the cases. Although these results cannot be generalized to other specific contexts, the results illustrate the strengths and weaknesses of each way of using checksums to catch number entry errors. Hence our study can serve as a starting point for efforts to improve each method.