The 20 Academic Papers On Privacy & Data Protection That Have Most Influenced My Ph.D. Research

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So far, I've read 717 academic papers for my Ph.D. in fairness & data protection law at Tel Aviv University. In today's newsletter, I will share the list of the 20 papers that have most influenced my research - and they are all free.

These are the 20 academic papers that have most influenced my Ph.D. research so far. The list below is not in order of preference.

1- Taking Trust Seriously in Privacy Law by Neil Richards & Woodrow Hartzog:

2- What Privacy Is For by Julie Cohen:

3- Dismantling the “Black Opticon”: Privacy, Race Equity, and Online Data-Protection Reform by Anita L. Allen:

4- Privacy, Security and Data Protection in Smart Cities: a Critical EU Law Perspective by Lilian Edwards:

5- The Future of Consumer Data Protection in the E.U. Rethinking the 'Notice and Consent' Paradigm in the New Era of Predictive Analytics by Alessandro Mantelero

6- Big Other: Surveillance Capitalism and the Prospects of an Information Civilization by Shoshana Zuboff:

7- Against Notice Skepticism in Privacy (and Elsewhere) by Ryan Calo:

8- Privacy Mindset, Technological Mindset by Michael Birnhack, Eran Toch & Irit Hadar:

9- Big Data for All: Privacy and User Control in the Age of Analytics by Omer Tene & Jules Polonetsky:

10- The Tradeoff Fallacy: How Marketers are Misrepresenting American Consumers and Opening Them Up to Exploitation by Joseph Turow, Michael Hennessy & Nora Draper:

11- 'I’ve Got Nothing to Hide' and Other Misunderstandings of Privacy by Daniel Solove:

12- Bringing Design to the Privacy Table by Richmond Wong & Deirdre K. Mulligan:

13- Broken Promises of Privacy: Responding to the Surprising Failure of Anonymization by Paul Ohm:

14- A Contextual Approach to Privacy Online by Hellen Nissenbaum:

15- Six Provocations for Big Data by Danah Boyd & Kate Crawford:

16- Engineering Privacy by Sarah Spiekermann & Lorrie Faith Cranor:

17- Privacy Harms by Danielle Citron & Daniel Solove:

18- The Subjects and Stages of AI Dataset Development: A Framework for Dataset Accountability by Mehtab Khan & Alex Hanna:

19- The Ethics of Facial Recognition Technology by Evan Selinger & Brenda Leong:

20- Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms that Optimize Predictive Accuracy by Angelina Wang, Sayash Kapoor, Solon Barocas & Arvind Narayanan:

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Have you read some of these articles? What other privacy & data protection articles would you recommend? Privacy needs critical thinkers like you: share this article and start a conversation about the topic. For the list of most relevant books, see my Twitter thread & LinkedIn post on the topic.

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See you next week. All the best, Luiza Jarovsky