AAP 2026 CONFERENCE

In our current digital technological age, it is said that our privacy matters more than ever. But despite no shortage of scholarly attention to the topic, we lack a comprehensive theory of what privacy is, why it matters, and when it matters. Privacy scholars are not shy about this state of affairs; in their view, our understanding of privacy is ""in disarray"", ""intractably vague"", ""a quagmire"", and so on.

In this talk, I argue that the difficulty of understanding privacy lies in how information flows --- personal or otherwise --- generate complex interactions in social settings. Using formal methods from complexity theory, I present a model of privacy in terms networked flows of normatively relevant personal information. This model brings basic questions of privacy into clearer focus. We see that privacy, understood as normatively appropriate personal information flows, matter because of how they affect people's abilities in ways that are normatively relevant. Importantly, we see that these abilities interact in ways that cannot be reduced to pairwise interactions, thus creating a problem of what I call Normative Complexity.

From this vantage point, the challenge of understanding privacy becomes tractable, though formidable. A comprehensive theory must allow us to describe how flows of personal information modulate the abilities of people interacting in a given setting. It should provide a way to normatively assess such patterns of personal information flow. And it should help guide us in arranging our social norms, technologies, and environments in terms of their privacy implications. The account I offer provides a foundation for this more comprehensive and systematic approach to understanding what privacy is, why it matters, and how it matters --- indeed, it seems, more than ever.