The rise of social media has raised questions about the vitality of privacy values and concerns about threats to privacy. The convergence of politics with social media use amplifies the privacy concerns traditionally associated with political organizing, particularly when marginalized groups and minority politics are involved. Despite the importance of these issues, there has been little empirical exploration of how privacy governs political activism and organizing in online environments. This chapter explores how privacy concerns shape political organizing on Facebook, through detailed case studies of how groups associated with March for Science, Day Without Immigrants (“DWI”), and Women’s March govern information flows. These cases address distinct issues, while operating in similar contexts and on the same timescales, allowing for the exploration of privacy in governance of personal information flows in political organizing and Facebook sub-communities. Privacy practices and concerns differed between the cases, depending on factors such as the nature of the group, the political issues it confronts, and its relationships to other organizations or movements.

This introduction to Governing Privacy in Knowledge Commons discusses how meta-analysis of past case studies has yielded additional questions to supplement the GKC framework, based on the specific governance challenges around personal information. Based on this renewed understanding, a series of new case studies are organized around the different roles that personal information play in commons arrangements. The knowledge commons perspective highlights the interdependence between knowledge flows aimed at creative production and personal information flows. Madelyn will discuss how those who systematically study knowledge commons governance with an eye toward knowledge production routinely encounter privacy concerns and values, along with rules in use that govern appropriate personal information flow.

Conceptualizing privacy as information flow rules-in-use constructed within a commons governance arrangement, we adapt the Governing Knowledge Commons (GKC) framework to study the formal and informal governance of information flows. We incorporate Helen Nissenbaum's “privacy as contextual integrity” approach, defining privacy in terms of contextually appropriate flows of personal information. While Nissenbaum's framework treats contextual norms as largely exogenous and emphasizes their normative valence, the GKC framework provides a systematic method to excavate personal information rules-in-use that actually apply in specific situations and interrogate governance mechanisms that shape rules-in-use. After discussing how the GKC framework can enrich privacy research, we explore empirical evidence for contextual integrity as governance within the GKC framework through meta-analysis of previous knowledge commons case studies, revealing three governance patterns within the observed rules-in-use for personal information flow. Our theoretical analysis provides strong justification for a new research agenda using the GKC framework to explore privacy as governance.

Internet of things (IoT) adds Internet connectivity to familiar devices, such as toasters and televisions, data flows no longer align with existing user expectations about these products. Studying techno-social change in the IoT context involves measuring what people expect of IoT device information flows as well as how these expectations and underlying social norms emerge and change. We want to design and govern technology in ways that adhere to people's expectations of privacy and other important ethical considerations. To do so effectively, we need to understand how techno-social changes in the environment (context) can lead to subtle shifts in information flows. CI is a useful framework for identifying and evaluating such shifts as a gauge for knowledge commons governance. This chapter explores key aspects behind privacy norm formation and evolution.