Privacy Dependencies

62 Pages Posted: 18 Sep 2019 Last revised: 17 Jun 2020

See all articles by Solon Barocas

Solon Barocas

Microsoft Research; Cornell University

Karen Levy

Cornell University

Date Written: September 3, 2019


This Article offers a comprehensive survey of privacy dependencies—the many ways that our privacy depends on the decisions and disclosures of other people. What we do and what we say can reveal as much about others as it does about ourselves, even when we don’t realize it or when we think we’re sharing information about ourselves alone.

We identify three bases upon which our privacy can depend: our social ties, our similarities to others, and our differences from others. In a tie-based dependency, an observer learns about one person by virtue of her social relationships with others—family, friends, or other associates. In a similarity-based dependency, inferences about our unrevealed attributes are drawn from our similarities to others for whom that attribute is known. And in difference-based dependencies, revelations about ourselves demonstrate how we are different from others—by showing, for example, how we “break the mold” of normal behavior or establishing how we rank relative to others with respect to some desirable attribute.

We elaborate how these dependencies operate, isolating the relevant mechanisms and providing concrete examples of each mechanism in practice, the values they implicate, and the legal and technical interventions that may be brought to bear on them. Our work adds to a growing chorus demonstrating that privacy is neither an individual choice nor an individual value—but it is the first to systematically demonstrate how different types of dependencies can raise very different normative concerns, implicate different areas of law, and create different challenges for regulation.

Keywords: privacy, anonymity, discrimination, genetics, technology, networks, inference

Suggested Citation

Barocas, Solon and Levy, Karen, Privacy Dependencies (September 3, 2019). 95 Washington Law Review 555 (2020), Available at SSRN:

Solon Barocas

Microsoft Research

300 Lafayette Street
New York, NY 10012
United States

Cornell University ( email )

Ithaca, NY 14853
United States

Karen Levy (Contact Author)

Cornell University ( email )

Ithaca, NY 14853
United States

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