The rapid adoption of generative AI in software development has impacted the industry, yet its effects on developers with visual impairments remain largely unexplored. To address this gap, we used an Activity Theory framework to examine how developers with visual impairments interact with AI coding assistants. For this purpose, we conducted a study where developers who are visually impaired completed a series of programming tasks using a generative AI coding assistant. We uncovered that, while participants found the AI assistant beneficial and reported significant advantages, they also highlighted accessibility challenges. Specifically, the AI coding assistant often exacerbated existing accessibility barriers and introduced new challenges. For example, it overwhelmed users with an excessive number of suggestions, leading developers who are visually impaired to express a desire for ``AI timeouts.'' Additionally, the generative AI coding assistant made it more difficult for developers to switch contexts between the AI-generated content and their own code. Despite these challenges, participants were optimistic about the potential of AI coding assistants to transform the coding experience for developers with visual impairments. Our findings emphasize the need to apply activity-centered design principles to generative AI assistants, ensuring they better align with user behaviors and address specific accessibility needs. This approach can enable the assistants to provide more intuitive, inclusive, and effective experiences, while also contributing to the broader goal of enhancing accessibility in software development.

Recent prevalence of values-inclusive design research introduces the potential of conducting research with those whose values conflict with researchers' own values. This is the scenario we have found ourselves in as we conduct values-inclusive participatory design to develop and deploy critical digital literacy education in a rural Appalachian community. We present provocations which outline the ethical concerns we have grappled with in pursuit of conducting fair and responsible research for our participants, indirect stakeholders, and ourselves. Through consideration of these provocations, we have developed a preliminary approach for managing a research relationship with those with whom we disagree which we call Designing for Shared Values. This approach is a conflict-avoidant method for negotiating values in values-inclusive design. It centers around reflexivity as a mechanism to account for one's own values and potential impacts of design research outcomes on indirect stakeholders, while maintaining responsibility to prioritize beneficial outcomes to research participants.

As we built and deployed a digital storytelling system to teach digital literacy skills to rural Appalachians, we discovered key opportunities and challenges to promoting digital literacy in this region. We identified that the importance of storytelling in Appalachian culture made digital storytelling an effective means of teaching these skills to residents. However, the poor technology infrastructure at our study site posed challenges to our participants' ability to use technology and learn new skills. We found that poor infrastructure reinforces low self-efficacy, discouraging participants from using technology. In environments where computers are often slow and unreliable, it is not possible to form realistic expectations of how a computer should act. Therefore, it becomes difficult for users to untangle if the issues they encounter are because of usage errors or the technology. These findings highlight how infrastructure and self-efficacy should be accounted for together when conducting rural HCI research.

Simple domain-specific graphical languages and libraries can empower a variety of users to create application behavior and logic. However, it remains challenging to produce and maintain a heterogeneous set of client applications based on these descriptions, as each client typically requires the developers to both understand and embed the domain-specific logic. This is because application logic must be encoded to some extent in both the server and client sides.In this paper, we propose an alternative approach, which allows the specification of application logic to reside solely on the cloud. In our system, reusable application components are assembled on the cloud in different logical chains and the client is solely concerned with how data is displayed and gathered from users. In this way, the chaining of requests and responses is done by the cloud and the client side has no knowledge of the application logic. This means that the experts in the domain build modular cloud components, arrange them in logical chains, generate a simple user interface, and later leave it to client-side developers to customize the presentation.

Many initiatives have focused on attracting girls and young women (K-12 or college) to computer science education. However, professional women who never learned to program have been largely ignored, despite the fact that such individuals may have many opportunities to benefit from enhanced skills and attitudes about computer programming. To provide a convenient learning space for this population, we created and evaluated the impacts of a nine-week web development workshop that was carefully designed to be both comfortable and engaging for this population. In this article, we report how the professionals’ attitudes and skills grew over the course of the workshop and how they now expect to integrate these skills and attitudes into their everyday lives.

Crowdworkers depend on Amazon Mechanical Turk (AMT) as an important source of income and it is left to workers to determine which tasks on AMT are fair and worth completing. While there are existing tools that assist workers in making these decisions, workers still spend significant amounts of time finding fair labor. Difficulties in this process may be a contributing factor in the imbalance between the median hourly earnings ($2.00/hour) and what the average requester pays ($11.00/hour). In this paper, we study how novices and experts select what tasks are worth doing. We argue that differences between the two populations likely lead to the wage imbalances. For this purpose, we first look at workers' comments in TurkOpticon (a tool where workers share their experience with requesters on AMT). We use this study to start to unravel what fair labor means for workers. In particular, we identify the characteristics of labor that workers consider is of "good quality'' and labor that is of "poor quality'' (e.g., work that pays too little.) Armed with this knowledge, we then conduct an experiment to study how experts and novices rate tasks that are of both good and poor quality. Through our research we uncover that experts and novices both treat good quality labor in the same way. However, there are significant differences in how experts and novices rate poor quality labor, and whether they believe the poor quality labor is worth doing. This points to several future directions, including machine learning models that support workers in detecting poor quality labor, and paths for educating novice workers on how to make better labor decisions on AMT.

Crowd work has the potential of helping the financial recovery of regions traditionally plagued by a lack of economic opportunities, e.g., rural areas. However, we currently have limited information about the challenges facing crowd workers from rural and super rural areas as they struggle to make a living through crowd work sites. This paper examines the challenges and advantages of rural and super rural Amazon Mechanical Turk (MTurk) crowd workers and contrasts them with those of workers from urban areas. Based on a survey of 421 crowd workers from differing geographic regions in the U.S., we identified how across regions, people struggled with being onboarded into crowd work. We uncovered that despite the inequalities and barriers, rural workers tended to be striving more in micro-tasking than their urban counterparts. We also identified cultural traits, relating to time dimension and individualism, that offer us an insight into crowd workers and the necessary qualities for them to succeed on gig platforms. We finish by providing design implications based on our findings to create more inclusive crowd work platforms and tools.

Researchers in various fields have been discussing the ethics of field research, particularly their responsibility to provide concrete benefits to participants. For example, when designing technology for their participants the discussion has centered around how and whether the technology benefits participants. We argue, that design projects can be reoriented towards benefiting participants from the outset, by slightly changing the process, activities, and initial object of design. Focusing instead on how to immediately impact the goals of the participants, designers can then progressively introduce technology to scale their impact. In this paper we present an ongoing instantiation of this process in rural West Virginia, where we have been teaching computer classes at a local library. We have found that our participants and partners are more appreciative of our efforts, and that the data we are gathering is just as, if not more, rich than previous design methodologies that we have used.

Rapidly diffusing 'industry 4.0' technologies stand to impact a broad range of stakeholders. Prior to implementation, forward looking formative analyses can identify systems and policy designs to promote equitable benefit. We investigate this potential through an analysis of stakeholders to a potential drone implementation on a small commercial farm in Rwanda. Translating stakeholders' imaginaries within a post-colonial frame, we identify hopes and concerns related to agency and influenced by global and local systems of power. The findings highlight constraints that recommend system designs promoting local agency and control and policies designed to balance local data management against potentially 'extractive' multinational data transfer processes.

In recent years, the peer-to-peer economy has grown exponentially, particularly in the ride-sharing sector. This growth has been accompanied by a muddying between the sharing and gig economy, and it has become unclear when an activity is sharing a resource vs. providing a service. To unpack this difference, we studied two successful carpooling groups (university students traveling home and commuting among professionals), which we contrast with previous literature on ride-hailing apps (e.g., Uber). The two communities that we studied differ in that: professionals, had more routine ride-sharing needs based on their commute; and students, arranged rides to return home for school breaks or long weekends. We detail how common needs and backgrounds impacted how carpoolers treated each other. Leveraging these findings, we outline design paths for both the sharing and gig economies to better realize the ideas of the sharing economy.

Ride-sharing platforms have rapidly spread and disrupted ride hailing markets, resulting in conflicts between ride-sharing and taxi drivers. Taxi drivers claim that their counterparts have unfair advantages in terms of lower prices and a more stable customer base, making it difficult to earn a living. Local government entities have dealt with this disruption and conflict in different ways, often looking towards some form of regulation. While there have been discussions about what the regulation should be, there has been less work looking at what impacts regulations have on ride-sharing drivers and their usage of the platforms. In this paper we present our interview study of ride-sharing drivers in Taiwan, who have gone through three distinct phases of regulation. Drivers felt that regulations legitimized their work, while having to navigate consequences related to regulated access to platforms and fundamental changes to the "gig'' of ride-sharing.

Ride-sharing companies have been reshaping the structure and practice of ride-hailing work. At the same time, studies have been showing mixed driver experiences on the platform while many of the drivers are working part-time. In this research, we seek to understand why drivers on this platform are working part-time, how this impacts their view of the platform, and what this means for more accurately evaluating the design of these platforms. To investigate this question, we focused on situating ride-sharing in the lives and constellation of gigs that drivers maintain. We collected 53 survey responses and conducted 10 semi-structured interviews with drivers to probe these questions. We found that the extent that drivers categorize themselves as part-time is less about the number of hours worked and more about how dependent they are on ride-sharing income. The level of this dependency seemed to heavily influence how they interacted with the platform and their attitudes towards difficulties faced. It seemed to us that in some ways that the design or functioning of the platform almost pushed users towards working part-time. We discuss the importance of taking these different types of workers and their situations into consideration when evaluating the design and usability of these platforms.

Uber is a ride-sharing platform that is part of the 'gig-economy,' where the platform supports and coordinates a labor market in which there are a large number of ephemeral, piecemeal jobs. Despite numerous efforts to understand the impacts of these platforms and their algorithms on Uber drivers, how to better serve and support drivers with these platforms remains an open challenge. In this paper, we frame Uber through the lens of Stakeholder Theory to highlight drivers' position in the workplace, which helps inform the design of a more ethical and effective platform. To this end, we analyzed Uber drivers' forum discussions about their lived experiences of working with the Uber platform. We identify and discuss the impact of the stakes that drivers have in relation to both the Uber corporation and their passengers, and look at how these stakes impact both the platform and drivers' practices.

We report an investigation of how older adults engage in social activities and community events in support of their mental, physical, and emotional health. We focus on personal and collaborative agency in a community context, and construe health as an outcome that is coproduced by a person and other engaged community members. Using qualitative methods, we investigated the coproduction of health among members of retirement communities and people who are ageing in place. We found that our participants, irrespective of living arrangements, engaged in a diverse range of coproduction activities, including physical, socialising, service, discussion, and interest-based activities. We also identified desired but less-supported coproduction opportunities, such as opportunistic activities and the need to better appropriate social resources to enable coproductions. We draw from these findings to consider design implications of technological support for facilitating older adults to coproduce.

We present a lab study of multiple feedback designs for guiding small-scale arm-and-hand movement for people with visual impairments (PVI), so that they can reach out to and grasp an item on a shelf. Little attention has been paid to the guidance of small-scale arm-and-hand movements by PVI, yet this is an essential element of product acquisition in a grocery shopping task and other similar daily activities. We developed a feedback interface that allowed us to explore two types of auditory feedback (speech and tones), haptic vibration feedback, and a combination of both. The result of the study demonstrated that the multi-modal navigational feedback, specifically speech and haptic, was the most effective and preferred mode for small-scale navigation.

It is important to support independent living for people with visual impairments (PVI). Part of this can be accomplished with individual assistive technologies. However, in this paper we emphasize the social and collaborative needs for PVI to fully integrate into society as equals. The study assesses how PVI collaborate with different types of sighted partners when shopping together. We chose to study grocery shopping because it is a critical and challenging task for PVI. We conducted field observations and in-depth interviews with five PVI and their sighted shopping partners, including spouses, caseworkers, and store-provided courtesy shoppers. We found several factors that modulated these collaborations with varying forms of common ground: 1) knowledge about how to assist PVI; 2) interpersonal knowledge resulting from common experience and interpersonal relationship history; and 3) knowledge of shopping as a practice. We discuss our findings with respect to the implications for designing collaborative interactions.

Timebanking is a growing type of peer-to-peer service exchange, but is hampered by the effort of finding good transaction partners. We seek to reduce this effort by using a Matching Algorithm for Service Transactions (MAST). MAST matches transaction partners in terms of similarity of interests and complementarity of abilities and needs. We present an experiment involving data and participants from a real timebanking network, that evaluates the acceptability of MAST, and shows that such an algorithm can retrieve matches that are subjectively better than matches based on matching the category of people's historical offers or requests to the category of a current transaction request.

Isolation and loneliness has been shown to be a significant cause of disease and mortality among elderly adults. The coproduction of activity is one potential method of prevention, through the promotion of social interaction and community engagement. The present study aims to facilitate coproduction in a continuing care retirement community, promoting health and wellness in elderly adults. To achieve this, we engage in the participatory design of a public interactive display for organizing community activity. We explore design needs and usability concerns from elderly residents, and discuss the trajectory of co-design work to realize this technological intervention.

Email has become deeply embedded in many users’ daily lives. To investigate how email features in users lives, particularly how users attend to email, we ran a 2-week study that logged interactions with email and gathered diary entries related to individual sessions. Our study showed that the majority of attentional effort is around reading email and participating in conversations, as opposed to email management (deleting, moving, flagging emails). We found that participants attended to email primarily based on notifications, instead of the number of unread messages in their inbox. We present our results through answering several questions, and leverage conversation analysis, particularly conversational openings, to explicate several issues. Our findings point to inefficiencies in email as a communication medium, mainly, around how summons are (or are not) issued. This results in an increased burden on email users to maintain engagement and determine (or construct) the appropriate moment for interruption.

In this paper we describe a study exploring why users spend more time in email than originally intended, which we call getting lost in email. To study this phenomenon, we implemented an IMAP logger that also dispatched diary entries to collect data for twenty participants over a two week period. Most participants reported getting lost in email during both short and long sessions. Our analysis suggests two primary factors in getting lost: the number of emails awaiting a reply and whether or not the session caused an interruption. We conclude that much of the problem around getting lost in email is in managing the tension between promptly responding to messages while limiting engagement with email.

Crowdsourcing is a relatively new model of labor where both the workers and work providers are experiencing its growing pains. A dominant platform that implements this model of labor is Amazon Mechanical Turk (AMT). While AMT has evolved over the years, the changes have focused mainly on work providers and have not addressed the problems workers face (e.g. dealing with market volatility and unpaid time searching for work). In this paper we present emph{TurkBench}, a tool meant to provide workers with personalized market visualization and session management. We discuss the design philosophy of the tool, briefly discuss four Turkers' reaction to a demo, and outline future work.

Crowdsourcing is a key current topic in CSCW. We build upon findings of a few qualitative studies of crowdworkers. We conducted an ethnomethodological analysis of publicly available content on Turker Nation, a general forum for Amazon Mechanical Turk (AMT) users. Using forum data we provide novel depth and detail on how the Turker Nation members operate as economic actors, working out which Requesters and jobs are worthwhile to them. We show some of the key ways Turker Nation functions as a community and also look further into Turker-Requester relationships from the Turker perspective -- considering practical, emotional and moral aspects. Finally, following Star and Strauss [25] we analyse Turking as a form of invisible work. We do this to illustrate practical and ethical issues relating to working with Turkers and AMT, and to promote design directions to support Turkers and their relationships with Requesters.

Previous studies on Amazon Mechanical Turk (AMT), the most well-known marketplace for microtasks, show that the largest population of workers on AMT is U.S. based, while the second largest is based in India. In this paper, we present insights from an ethnographic study conducted in India to introduce some of these workers or "Turkers" -- who they are, how they work and what turking means to them. We examine the work they do to maintain their reputations and their work-life balance. In doing this, we illustrate how AMT's design practically impacts on turk-work. Understanding the "lived work" of crowdwork is a valuable first step for technology design.

Enterprise wikis commonly see low adoption rates, preventing them from reaching the critical mass that is needed to make them valuable. The high interaction costs for contributing content to these wikis is a key factor impeding wiki adoption. Much of the collaboration among knowledge workers continues to occur in email, which causes useful information to stay siloed in personal inboxes. In this demo we present Mail2Wiki, a system that enables easy contribution and initial curation of content from the personal space of email to the shared repository of a wiki.

Corporate wikis are affected by poor adoption rates. The high interaction costs required to organize and maintain information in these wikis are a key factor that limits broader adoption. We present VisualWikiCurator, a wiki extension designed to lower such costs by (a) recommending new content to easily update a wiki page, and (b) extracting structured data from the wiki page while providing new alternative visualizations of the data. The visualizations of extracted semantic data act both as alternative views and as tools to organize the page content. Since no information extraction algorithm is perfect with generic unstructured data, we use a mixed-initiative approach to allow users to refine machine-extracted metadata and easily re-organize the content in wiki pages.