The scholarly literature presents a dizzying array of diverging definitions of privacy. Privacy is equally ambiguous in practice, where it is invoked to protect a wide range of interests based on an equally wide range of justifications. While the frequency and intensity of privacy debates are evidence of its salience to contemporary life, its contestability has intensely troubling practical consequences. Privacy is decreed too fickle and indeterminate to be advanced through legislative, regulatory, and technical means. Ambiguity becomes an excuse for disregarding privacy claims-despite visceral and broad appeal, and vociferous support.
In this talk, I argue that privacy is an "essentially-contested concept," and that its contestability is a source of value and power that ought to be preserved. I then explore the power of a multi-dimensional analytic of privacy for advancing our understanding of privacy's meaning in specific contexts and contests. Using the analytic to unpack privacy claims in high-profile privacy cases reveals the complex array of privacy concepts raised by technical change. Privacy's essential contestability is key to its ongoing relevance and utility in political and social life but leveraging it requires analytical tools that help us ensure that efforts at design focus on the right privacy in a given context.

Deirdre K. Mulligan is an Associate Professor in the School of Information at UC Berkeley, co-Director of the Berkeley Center for Law & Technology, Chair of the Board of Directors of the Center for Democracy and Technology, a Fellow at the Electronic Frontier Foundation, and Policy lead for the NSF-funded TRUST Science and Technology Center. Prior to joining the School of Information in 2008, she was a Clinical Professor of Law, founding Director of the Samuelson Law, Technology & Public Policy Clinic, and Director of Clinical Programs at the UC Berkeley School of Law (Boalt Hall). Mulligan’s current research agenda focuses on information privacy and security, including exploring users' conceptions of privacy in the online environment and their relation to existing theories of privacy. Her comparative study of privacy practices in large corporations in five countries, conducted with UC Berkeley Law Prof. Kenneth Bamberger, will be published by MIT press this fall.

Privacy's place in software engineering development is tentatively made at best. Yet the effects of information leakage, an improperly made audit and so on are known to be expensive in monetary, legal and other terms. We present here learnings made in adopting ideas from safety-critical systems and disciplines where safety is a first-class concept, such as aviation and medicine. We outline our rationale and describe our experiences - both good and bad - and the necessary concepts that must be understood for successful application of such ideas.

Dr. Ian Oliver is a security specialist within Nokia Networks working on Network Function Virtualisation, 5G, Security and Privacy, He also holds a Research Fellow position at the University of Brighton working with the Visual Modelling Group. Prior to these he has worked as the privacy architect and officer for Here and Nokia Services; and for eleven years at Nokia Research Centre working with Semantic Web, UML, formal methods and hardware-software co-design. He has also worked at Helsinki University of Technology and Aalto University teaching formal methods and modelling with UML. He holds over 40 patents in areas such as The Internet of Things, semantic technologies and privacy. He is the author of the book Privacy Engineering: A data flow and ontological approach. More information can be found here: http://www.privacyengineeringbook.net.