(1) Whereas the objectives of the Community, as laid down in the Treaty, as amended by the Treaty on European Union, include creating an ever closer union among the peoples of Europe, fostering closer relations between the States belonging to the Community, ensuring economic and social progress by common action to eliminate the barriers which divide Europe, encouraging the constant improvement of the living conditions of its peoples, preserving and strengthening peace and liberty and promoting democracy on the basis of the fundamental rights recognized in the constitution and laws of the Member States and in the European Convention for the Protection of Human Rights and Fundamental Freedoms;

Some Preliminary Comments on the DIRECTIVE 95/46/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data.

Presentacio sobre l'Oficina de Proteccio de Dades Personals de la UAB i la politica Open Science. Va formar part de la conferencia "Les politiques d'Open Data / Open Acces: Implicacions a la recerca" orientada a investigadors i gestors de projectes europeus que va tenir lloc el 20 de setembre de 2018 a la Universitat Autonoma de Barcelona

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General data protection regulation

The American Review of Public Administration

A Charter of Fundamental Rights for the European Union

This paper draws on regulatory governance scholarship to argue that the analytic phenomenon currently known as ‘Big Data’ can be understood as a mode of ‘design-based’ regulation. Although Big Data decision-making technologies can take the form of automated decision-making systems, this paper focuses on algorithmic decision-guidance techniques. By highlighting correlations between data items that would not otherwise be observable, these techniques are being used to shape the informational choice context in which individual decision-making occurs, with the aim of channelling attention and decision-making in directions preferred by the ‘choice architect’. By relying upon the use of ‘nudge’ – a particular form of choice architecture that alters people’s behaviour in a predictable way without forbidding any options or significantly changing their economic incentives, these techniques constitute a ‘soft’ form of design-based control. But, unlike the static Nudges popularised by Thaler and Sunstein [(20...

/pdf/hypernudge-big-data-as-a-mode-of-regulation-by-design-39mdxe79yc.pdf

Hypernudge: Big Data as a mode of regulation by design

Among the numerous implications of digitalization, the debate about ‘big data’ has gained momentum. The central idea capturing attention is that digital data represents the newest key asset organizations should use to gain a competitive edge. Data can be sold, matched with other data, mined, and used to make inferences about anything, from people’s behavior to weather conditions. Particularly, what is known as ‘big data analytics’ — i.e. the modeling and analysis of big data — has become the capability which differentiates, from the rest of the market, the most successful companies. An entire business ecosystem has emerged around the digital data asset, and new types of companies, such as analytical competitors and analytical deputies, are proliferating as a result of the analysis of digital data. However, virtually absent from the big data debate is any mention of one of its constitutive mechanisms — that is, dataveillance. Dataveillance — which refers to the systematic monitoring of people or groups, by means of personal data systems in order to regulate or govern their behavior — sets the stage and reinforces the development of the data economy celebrated in the big data debate. This article aims to make visible the interdependence between dataveillance, big data and analytics by providing real examples of how companies collect, process, analyze and use data to achieve their business objectives.

https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/download/analytics/analytic

When big data meets dataveillance: the hidden side of analytics

As surveillance-oriented security technologies (SOSTs) are considered security enhancing but also privacy infringing, citizens are expected to trade part of their privacy for higher security. Drawing from the PRISE project, this study casts some light on how citizens actually assess SOSTs through a combined analysis of focus groups and survey data. First, the outcomes suggest that people did not assess SOSTs in abstract terms but in relation to the specific institutional and social context of implementation. Second, from this embedded viewpoint, citizens either expressed concern about government's surveillance intentions and considered SOSTs mainly as privacy infringing, or trusted political institutions and believed that SOSTs effectively enhanced their security. None of them, however, seemed to trade privacy for security because concerned citizens saw their privacy being infringed without having their security enhanced, whilst trusting citizens saw their security being increased without their privacy being affected.

Public assessment of new surveillance-oriented security technologies: Beyond the trade-off between privacy and security:

Pre-emptive security emphasizes the necessity of envisioning and designing technologies enabling the anticipation and management of emergent risks threatening human and public security. Surveillance functionalities are embedded in the design of these technologies to allow constant monitoring, preparedness and prevention. Yet surveillance-orientated security technologies, such as smart CCTVs or Deep Packet Inspection, bring along with their implementation other risks, such as risks of privacy infringement, discrimination, misuse, abuse, or errors, which have often triggered public outrage and resistance. The same measures meant to foster human security, can potentially make people feel insecure, vulnerable, and exposed. This outcome is the result of a narrow approach toward problem solving that does not take into account those same people the technology is supposed to protect. Drawing from both the socio-cultural and psychometric approaches to risk analysis and from the literature on public engagement in science and technology, this article presents a new methodological tool, which combines traditional citizen summit method with an innovative mixed-method research design. The objective of this new form of participatory exercise is to engage the public and gather socially robust and in context knowledge about the public acceptability of these technologies. The method has been developed as part of the SurPRISE project, funded by the European Commission under the SeventhFramework Program. The article presents the theoretical framework and preliminary results of citizen summits organized across Europe.

https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/download/acceptable_technologies/acceptable

Acceptable Surveillance-Orientated Security Technologies: Insights from the SurPRISE Project

The increasing availability of electronic records and the expanded reliance on online communications and services have made available a huge amount of data about people’s behaviours, characteristics, and preferences Advancements in data processing technology, known as big data, offer opportunities to increase organisational efficiency and competitiveness Analytically sophisticated companies excel in their ability to extract value from the analysis of digital data However, in order to exploit the potential economic benefits produced by big data and analytics, issues of data privacy and information security need to be addressed In Europe, organisations processing personal data are being required to implement basic data protection principles, which are considered difficult to implement in big data environments Little is known in the privacy studies literature about how companies manage the trade-off between data usage and data protection This study contributes to explore the corporate data privacy environment, by focusing on the interrelationship between the data protection legal regime, the application of big data analytics to achieve corporate objectives, and the creation of an organisational privacy culture It also draws insights from surveillance studies, particularly the idea of dataveillance, to identify potential limitations of the current legal privacy regime The findings from the analysis of survey data show that big data and data protection support each other, but also that some frictions can emerge around data collection and data fusion The demand for the integration of different data sources poses challenges to the implementation of data protection principles However, this study finds no evidence that data protection laws prevent data gathering Implications relevant for the debate on the reform of European data protection law are also drawn from these findings

Sara Degli Esposti

Papers

When big data meets dataveillance: the hidden side of analytics

Public assessment of new surveillance-oriented security technologies: Beyond the trade-off between privacy and security:

Acceptable Surveillance-Orientated Security Technologies: Insights from the SurPRISE Project

From Dataveillance to Data Economy: Firm View on Data Protection

Oocyte provision as a (quasi) social market: Insights from Spain.