The parallel rise of pervasive data collection platforms and computational methods for collecting, analyzing, and drawing inferences from large quantities of user data has advanced social computing research, investigating digital traces to understand mediated behaviors of individuals, groups, and societies. At the same time, methods employed to access these data have raised questions about ethical research practices. This article provides insights into U.S. institutional review boards’ (IRBs) attitudes and practices regulating social computing research. Through descriptive and inferential analysis of survey data from staff at 59 IRBs at research universities, we examine how IRBs evaluate the growing variety of studies using pervasive digital data. Findings unpack the difficulties IRB staff face evaluating increasingly technical research proposals while highlighting the belief in their ability to surmount these difficulties. They also indicate a lack of consensus among IRB staff about what should be reviewed and a willingness to work closely with researchers.

In recent years, the CHI community has seen significant growth in research on Human-Centered Responsible Artificial Intelligence. While different research communities may use different terminology to discuss similar topics, all of this work is ultimately aimed at developing AI that benefits humanity while being grounded in human rights and ethics, and reducing the potential harms of AI. In this special interest group, we aim to bring together researchers from academia and industry interested in these topics to map current and future research trends to advance this important area of research by fostering collaboration and sharing ideas.

The global coronavirus pandemic has raised important questions regarding how to balance public health concerns with privacy protections for individual citizens. In this essay, we evaluate contact tracing apps, which have been offered as a technological solution to minimize the spread of COVID-19. We argue that apps such as those built on Google and Apple’s “exposure notification system” should be evaluated in terms of the contextual integrity of information flows; in other words, the appropriateness of sharing health and location data will be contextually dependent on factors such as who will have access to data, as well as the transmission principles underlying data transfer. We also consider the role of prevailing social and political values in this assessment, including the large-scale social benefits that can be obtained through such information sharing. However, caution should be taken in violating contextual integrity, even in the case of a pandemic, because it risks a long-term loss of autonomy and growing function creep for surveillance and monitoring technologies.

Fitness trackers are an increasingly popular tool for tracking one’s health and physical activity. While research has evaluated how these mobile devices can improve health and well-being, few studies have empirically evaluated users’ privacy concerns that stem from the collection, aggregation, and sharing of personal fitness information (PFI). In this paper, we endeavor to gain a more complete picture of users’ experiences with fitness trackers and how they manage the privacy of personal fitness information. Using Communication Privacy Management (CPM) as a theoretical framework, we describe findings from survey and interview data regarding the benefits and drawbacks users perceive from using a fitness tracker, as well as how privacy concerns and behaviors map onto user strategies for managing privacy boundaries related to personal fitness information. We conclude by discussing how our findings contribute to theory and future information policy related to the growing wearable device ecosystem.

The future of work increasingly focuses on the collection and analysis of worker data to monitor communication, ensure productivity, reduce security threats, and assist in decision-making. The COVID-19 pandemic increased employer reliance on these technologies; however, the blurring of home and work boundaries meant these monitoring tools might also surveil private spaces. To explore workers’ attitudes toward increased monitoring practices, we present findings from a factorial vignette survey of 645 U.S. adults who worked from home during the early months of the pandemic. Using the theory of privacy as contextual integrity to guide the survey design and analysis, we unpack the types of workplace surveillance practices that violate privacy norms and consider attitudinal differences between male and female workers. Our findings highlight that the acceptability of workplace surveillance practices is highly contextual, and that reductions in privacy and autonomy at work may further exacerbate power imbalances, especially for vulnerable employees.