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In pseudonymous online fora like Reddit, the benefits of self-disclosure are often apparent to users (e.g., I can vent about my in-laws to understanding strangers), but the privacy risks are more abstract (e.g., will my partner be able to tell that this is me?). Prior work has sought to develop natural language processing (NLP) tools that help users identify potentially risky self-disclosures in their text, but none have been designed for or evaluated with the users they hope to protect. Absent this assessment, these tools will be limited by the social-technical gap: users need assistive tools that help them make informed decisions, not paternalistic tools that tell them to avoid self-disclosure altogether. To bridge this gap, we conducted a study withN=21 Reddit users; we had them use a state-of-the-art NLP disclosure detection model on two of their authored posts and asked them questions to understand if and how the model helped, where it fell short, and how it could be improved to help them make more informed decisions. Despite its imperfections, users responded positively to the model and highlighted its use as a tool that can help them catch mistakes, inform them of risks they were unaware of, and encourage self-reflection. However, our work also shows how, to be useful and usable, AI for supporting privacy decision-making must account for posting context, disclosure norms, and users' lived threat models, and provide explanations that help contextualize detected risks. 

The involvement of companies and public institutions in open-source software (OSS) has become widespread. While studies have explored the business models of for-profit organizations and their impact on software quality, little is known about their influence on OSS communities, especially in terms of diversity and inclusion. This knowledge gap is significant, considering that many organizations have the resources to enhance diversity and inclusion internally, but whether these efforts extend to OSS remains uncertain. To address this gap, we conducted interviews with maintainers of community-owned and organization-owned OSS projects, revealing tensions between organizations and their projects and identifying the impact of internal policies on OSS communities. Our findings reveal that, on the one hand, organization-owned projects often restrict external contributions due to stringent operating procedures and segmented communication, leading to limited external engagement. On the other hand, these organizations positively influence diversity and inclusion, notably in the representation and roles of women and the implementation of mentorship programs. 

Much of our modern digital infrastructure relies critically upon open sourced software. The communities responsible for building this cyberinfrastructure require maintenance and moderation, which is often supported by volunteer efforts. Moderation, as a non-technical form of labor, is a necessary but often overlooked task that maintainers undertake to sustain the community around an OSS project. This study examines the various structures and norms that support community moderation, describes the strategies moderators use to mitigate conflicts, and assesses how bots can play a role in assisting these processes. We interviewed 14 practitioners to uncover existing moderation practices and ways that automation can provide assistance. Our main contributions include a characterization of moderated content in OSS projects, moderation techniques, as well as perceptions of and recommendations for improving the automation of moderation tasks. We hope that these findings will inform the implementation of more effective moderation practices in open source communities. 

How do software engineers identify and act on their ethical concerns? Past work examines how software practitioners navigate specific ethical principles such as “fairness”, but this narrows the scope of concerns to implementing pre-specified principles. In contrast, we report self-identified ethical concerns of 115 survey respondents and 21 interviewees across five continents and in non-profit, contractor, and non-tech firms.We enumerate their concerns – military, privacy, advertising, surveillance, and the scope of their concerns – from simple bugs to questioning their industry’s entire existence. We illustrate howattempts to resolve concerns are limited by factors such as personal precarity and organizational incentives. We discuss how even relatively powerful software engineers often lacked the power to resolve their ethical concerns. Our results suggest that ethics interventions must expand from helping practitioners merely identify issues to instead helping them build their (collective) power to resolve them, and that tech ethics discussions may consider broadening beyond foci on AI or Big Tech. 

Open-source software projects have become an integral part of our daily life, supporting virtually every software we use today. Since open-source software forms the digital infrastructure, maintaining them is of utmost importance. We present Climate Coach, a dashboard that helps open-source project maintainers monitor the health of their community in terms of team climate and inclusion. Through a literature review and an exploratory survey (N=18), we identified important signals that can reflect a project’s health, and display them on a dashboard. We evaluated and refined our dashboard through two rounds of think-aloud studies (N=19). We then conducted a two-week longitudinal diary study (N=10) to test the usefulness of our dashboard. We found that displaying signals that are related to a project’s inclusion help improve maintainers’ management strategies. 

While the severe underrepresentation of women and non-binary people in open source is widely recognized, there is little empirical data on how the situation has changed over time and which subcommunities have been more effectively reducing the gender imbalance. To obtain a clearer image of gender representation in open source, we compiled and synthesized existing empirical data from the literature, and computed historical trends in the representation of women across 20 open source ecosystems. While inherently limited by the ability of automatic name-based gender inference to capture true gender identities at an individual level, our census still provides valuable population-level insights. Across all and in most ecosystems, we observed a promising upward trend in the percentage of women among code contributors over time, but also high variation in the percentage of women contributors across ecosystems. We also found that, in most ecosystems, women withdraw earlier from open-source participation than men. 

Open source software represents an important form of digital infrastructure as well as a pathway to technical careers for many developers, but women are drastically underrepresented in this setting. Although there is a good body of literature on open source participation, there is very little understanding of the participation trajectories and contribution experiences of women developers, and how they compare to those of men developers, in open source software projects. In order to understand their joining and participation trajectories, we conducted interviews with 23 developers (11 men and 12 women) who became core in an open source project. We identify differences in women and men's motivations for initial contributions and joining processes (e.g. women participating in projects that they have been invited to) and sustained involvement in a project. We also describe unique negative experiences faced by women contributors in this setting in each stage of participation. Our results have implications for diversifying participation in open source software and understanding open source as a pathway to technical careers. 

Account sharing is a common, if officially unsanctioned, practice among workgroups, but so far understudied in higher education. We interview 23 workgroup members about their account sharing practices at a U.S. university. Our study is the first to explicitly compare IT and non-IT observations of account sharing as a "normal and easy" workgroup practice, as well as to compare student practices with those of full-time employees. We contrast our results with those in prior works and offer recommendations for security design and for IT messaging. Our findings that account sharing is perceived as low risk by our participants and that security is seen as secondary to other priorities offer insights into the gap between technical affordances and social needs in an academic workplace such as this.?