Is privacy privacy ?

Author:

Nissim Kobbi1ORCID,Wood Alexandra2

Affiliation:

1. Department of Computer Science, Georgetown University, Washington, DC, USA

2. Berkman Klein Center for Internet & Society, Harvard University, MA, USA

Abstract

This position paper observes how different technical and normative conceptions of privacy have evolved in parallel and describes the practical challenges that these divergent approaches pose. Notably, past technologies relied on intuitive, heuristic understandings of privacy that have since been shown not to satisfy expectations for privacy protection. With computations ubiquitously integrated in almost every aspect of our lives, it is increasingly important to ensure that privacy technologies provide protection that is in line with relevant social norms and normative expectations. Similarly, it is also important to examine social norms and normative expectations with respect to the evolving scientific study of privacy. To this end, we argue for a rigorous analysis of the mapping from normative to technical concepts of privacy and vice versa. We review the landscape of normative and technical definitions of privacy and discuss specific examples of gaps between definitions that are relevant in the context of privacy in statistical computation. We then identify opportunities for overcoming their differences in the design of new approaches to protecting privacy in accordance with both technical and normative standards. This article is part of a discussion meeting issue ‘The growing ubiquity of algorithms in society: implications, impacts and innovations’.

Funder

US Census Bureau

Publisher

The Royal Society

Subject

General Physics and Astronomy,General Engineering,General Mathematics

Reference39 articles.

1. What privacy is for;Cohen JM;Harv. Law Rev.,2013

2. ‘I've got nothing to hide’ and other misunderstandings of privacy;Solove DJ;San Diego Law Rev.,2007

3. Gatewood G. 2001 Census Confidentiality and Privacy: 1790–2002. (http://www.census.gov/history/pdf/ConfidentialityMonograph.pdf)

4. Abowd JM. 2017 Why the Census Bureau Adopted Differential Privacy for the 2020 Census of Population. Presentation at Harvard University December 11.

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