scispace - formally typeset
Open Access

ARTICLE 29 Data Protection Working Party

TLDR
In 2010, the European Data Protection Authorities (the Article 29 Working Party [WP29]) discussed the data protection and privacy implications of the Anti-Counterfeiting Trade Agreement (ACTA).
Abstract
At its plenary meeting on 12 and 13 July 2010, the European Data Protection Authorities (the Article 29 Working Party [WP29]) discussed the data protection and privacy implications of the Anti-Counterfeiting Trade Agreement (ACTA). For many years the negotiations on this new multilateral instrument were conducted behind closed doors. WP29 therefore welcomes the recent publication by the negotiators of a consolidated version of the current draft agreement. This enabled the members of WP29 to verify the earlier rumours on the content of the agreement and the possible implications for privacy and data protection that it may have. Since the negotiations are still ongoing, we are of course unable to give a full assessment as yet of whether or not ACTA will comply with European privacy and data protection legislation.

read more

Citations
More filters
Journal ArticleDOI

Counterfactual Explanations Without Opening the Black Box: Automated Decisions and the GDPR

TL;DR: It is suggested data controllers should offer a particular type of explanation, unconditional counterfactual explanations, to support these three aims, which describe the smallest change to the world that can be made to obtain a desirable outcome, or to arrive at the closest possible world, without needing to explain the internal logic of the system.
Proceedings ArticleDOI

Third-Party Web Tracking: Policy and Technology

TL;DR: The current policy debate surrounding third-party web tracking is surveyed and the FourthParty web measurement platform is presented, to inform researchers with essential background and tools for contributing to public understanding and policy debates about web tracking.
Journal ArticleDOI

Estimating the success of re-identifications in incomplete datasets using generative models

TL;DR: A generative copula-based method that can accurately estimate the likelihood of a specific person to be correctly re-identified, even in a heavily incomplete dataset, casting doubt on the adequacy of current anonymization practices.
Journal ArticleDOI

Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk

Bernard Lo
- 24 Feb 2015 - 
TL;DR: It is concluded that sharing data is in the public interest, but a multi-stakeholder effort is needed to develop a culture, infrastructure, and policies that will foster responsible sharing—now and in the future.
Book ChapterDOI

A design space for effective privacy notices

TL;DR: This paper surveys the existing literature on privacy notices and identifies challenges, requirements, and best practices for privacy notice design, and mapping out the design space for privacy notices by identifying relevant dimensions provides a taxonomy and consistent terminology of notice approaches.
References
More filters
Posted Content

Broken Promises of Privacy: Responding to the Surprising Failure of Anonymization

TL;DR: It is necessary to respond to the surprising failure of anonymization, and this Article provides the tools to do so.
Related Papers (5)