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Since the beginning of the COVID-19 pandemic, videoconferencing platforms have become an essential part of our social, educational, and work lives. Furthermore, the United States continues to grapple with criminal justice reform, employing processes such as restorative justice to replace antiquated punitive approaches to justice with a focus on the multifaceted needs of communities. Essential to the delivery of restorative justice, restorative justice practitioners are community members trained in the process and approaches of restorative practice. Like everyone else, restorative justice practitioners have transitioned from historically in-person facilitation to online facilitation, integrating videoconferencing platforms into their justice-related work. Diverse communities within Human-Computer Interaction (HCI) have been examined in light of their digital transitions and the utilization of various digital tools, including videoconferencing platforms prompted by the pandemic. However, the distinctive perspective of restorative justice practitioners in adapting restorative approaches to an online format is unexplored. Therefore, our research examines how restorative practitioners use videoconferencing platforms for justice-related interventions. To do so, we conducted six semi-structured focus group interviews with 22 US-based restorative facilitators to learn about their experiences with online delivery of restorative justice. Our research revealed that restorative facilitators uphold restorative values in their online delivery by embracing the restorative facilitation process and fostering dialogue. Furthermore, we posit that the Human-Computer Interaction (HCI) community can acquire valuable insights from restorative practitioners on nurturing and sustaining intimacy and connection online. 

People go online for information and support about sensitive topics like depression, infertility, death, or divorce. However, what happens when such topics are algorithmically recommended to them even if they are not looking for it? This article examines people's self-diagnostic behaviors based on algorithmically-recommended content, for example, wondering if they might have depression because an algorithm pushed that topic into their view. Specifically, it examines what happens when the sensitive content is not generated by users, but by companies in the form of targeted advertisements. This paper explores these questions in three parts. The first part reviews literature on self-diagnosis and targeted advertising. The second part presents a mixed-methods study of how targeted ads can enable self-diagnostic reactions. The third part reflects on the mechanisms that influence self-diagnosis and examines potential regulatory implications. 

Non-consensual intimate media (NCIM) involves sharing intimate content without the depicted person's consent, including 'revenge porn' and sexually explicit deepfakes. While NCIM has received attention in legal, psychological, and communication fields over the past decade, it is not sufficiently addressed in computing scholarship. This paper addresses this gap by linking NCIM harms to the specific technological components that facilitate them. We introduce thesociotechnical stack, a conceptual framework designed to map the technical stack to its corresponding social impacts. The sociotechnical stack allows us to analyze sociotechnical problems like NCIM, and points toward opportunities for computing research. We propose a research roadmap for computing and social computing communities to deter NCIM perpetration and support victim-survivors through building and rebuilding technologies.