Search

Earlier this year, the European Commission (EC) registered the ‘Civil society initiative for a ban on biometric mass surveillance practices’, a European Citizens’ Initiative. Citizens are thus given the opportunity to authorize the EC to suggest the adoption of legislative instruments to permanently ban biometric mass surveillance practices. This contribution finds the above initiative particularly promising, as part of a new development of bans in the European Union (EU). It analyses the EU’s approach to facial, visual and biometric surveillance,3 with the objective of submitting some ideas that the European legislator could consider when strictly regulating such practices.

Following up on previous research conducted on post-GDPR lawmaking, this chapter seeks to explore a second wave of post-GDPR lawmaking, particularly regarding the European Strategy for Data and its relation with the field of data protection. For this purpose, a selection of case studies is analysed to look at whether EU lawmakers seek integration, denial or mimetics of the GDPR in different data-intensive activities that have been recently regulated or are soon to be. Following this analysis, the chapter explores different paths to explain the reasons and rationale behind the adopted approach and argues for careful integration with the legal rules of a pre-existing framework of the GDPR and its principles and rules. Only then will boundaries of data protection law be able to function properly. The chapter ends with a perspective on regulatory change in EU lawmaking on the Digital Single Market and its subsequent regulatory strategies as a result of this process.

Can satisfactory explanations for complex machine learning models be achieved in high-risk automated decision-making? How can such explanations be integrated into a data protection framework safeguarding a right to explanation? This article explores from an interdisciplinary point of view the connection between existing legal requirements for the explainability of AI systems set out in the General Data Protection Regulation (GDPR) and the current state of the art in the field of explainable AI. It studies the challenges of providing human legible explanations for current and future AI-based decision-making systems in practice, based on two scenarios of automated decision-making in credit scoring risks and medical diagnosis of COVID-19. These scenarios exemplify the trend towards increasingly complex machine learning algorithms in automated decision-making, both in terms of data and models. Current machine learning techniques, in particular those based on deep learning, are unable to make clear causal links between input data and final decisions. This represents a limitation for providing exact, human-legible reasons behind specific decisions, and presents a serious challenge to the provision of satisfactory, fair and transparent explanations. Therefore, the conclusion is that the quality of explanations might not be considered as an adequate safeguard for automated decision-making processes under the GDPR. Accordingly, additional tools should be considered to complement explanations. These could include algorithmic impact assessments, other forms of algorithmic justifications based on broader AI principles, and new technical developments in trustworthy AI. This suggests that eventually all of these approaches would need to be considered as a whole.

The GEMS, the expert group that had to advise the government on corona management, has been disbanded, but its advice on the corona barometer still exists. In this contribution Marc-Antoine Gavray and Paul De Hert indicate where the absence of lawyers and philosophers in the GEMS made itself felt.

Article 17 GDPR is about a right to have personal data deleted and not about any ‘right to be forgotten’: its paragraph 1 expressly states that ‘the data subject shall have the right to obtain from the controller the erasure of personal data con- cerning him or her without undue delay and the controller shall have the obligation to erase per- sonal data without undue delay’. The specificity of the wording leaves little doubt as to the exact scope of Article 17 of the GDPR.

Reprint of an article of 1996 SUMMARY: Introduction; 1 Principles of the democratic constitutional state; 1.1 The Recognition of Human Rights in their Double Function; 1.2 The Rule of Law; 1.3 Democracy; 2 The democratic constitutional state and the invention of two complementary legal tools of power control; 2.1 Limiting power through opacity tools; 2.2 Channelling power through transparency tools; 3 Privacy as a tool for opacity (creating zones of non-interference); 3.1 The negative role of privacy; 3.2 The positive role of privacy; 3.3 The non-absolute nature of privacy; 4 Data protection as a tool for transparency; 4.1 Introduction; 4.2 The rationale behind data protection; 4.3 Data protection as an opacity tool?; 4.4 The charter of fundamental rights of the european union; 5 The shift from opacity towards transparency in european human rights law; 5.1 European human rights law and the legality requirement; 5.2 The success of the legality requirement; 5.3 A critical comment about the strasbourg focus on the legality requirement; 5.4 The danger of proceduralisation; 5.5 A requirement fundamental to opacity: necessary in a democratic state; 6. Combining privacy and data protection 6.1 Combining the tools; 6.2 Determining the switch; 6.3 An example: camera surveillance; 6.4 A second example: passenger profiling; 6.5 Workable criteria?; Conclusion.1

In 2016 zorgde de GDPR voor een trilling in het landschap door op heldere wijze een hele reeks eisen te formuleren voor privacybeheer van data en die te koppelen aan streng toezicht door landelijke autoriteiten voor persoonsgegevens. Die gingen ook Europees meer en intens samenwerken. Met corona kwam vier jaar later de lakmoesproef.In de voorbije twee jaar heeft het rechtssysteem niet goed gefunctioneerd, met uitzondering van het GDPR-systeem. Er is te veel pragmatisme geweest en te weinig gekeken naar de rechtsprincipes.21 In het Engels spreken ze over democratic back sliding. Een rechtsprincipe onder vuur is dat van de verantwoordelijkheid van mensen met beleidspositie, zowel in het openbaar bestuur als in het middenveld. De democratie roert zich nu opnieuw, ook over privacy. De verlenging van de covidpas eind januari 2022 in België was een teleurstelling, want het draag- vlak voor dat instrument was tanend. Gelukkig en desondanks beweegt de politiek terug, zoals met de hoorzittingen in het Belgisch Parlement rond de vaccinatieplicht. Het Parlement moet duidelijk weer aan controle winnen en schijnt daar ook zin in te hebben, afgaande op de hoorzittingen over privacy, vaccinatie en CST. Opschonen wat er in de voorbije jaren, vaak tegen adviezen van de GBA, is opgebouwd in grote haast en top down zonder participatie en accountability. Reflecteren over de privacy-infrastructuur die het voor dit land wil

Transparency has been at the centre of the debate on algorithmic governance. However, when the GDPR was adopted in 2016, the legislator preferred to establish accountability as the core of the Regulation's principles, rather than transparency. Unfortunately, accountability does not yet seem to be playing the role it was assigned in the data protection ecosystem, at least when it comes to algorithmic decision-making. To turn this scenario around, we propose a reflective exercise in which we look at the concept of accountability and how it was introduced in the GDPR. By emphasising on the human element in algorithmic decision-making, we find a systematic and process-oriented accountability present in the GDPR. Following arguments already made in the literature, we hold that this kind of accountability is well suited for algorithmic governance. Moreover, we argue that it could be strengthened by the Commission's proposal for a Regulation on Artificial Intelligence.

Het Coronadebat en het gebruik van het Covid Safe Ticket (CST) heeft ons nieuwe inzichten gegeven in het fenomeen van nudges, ‘overheidsduwtjes in de gewenste richting’. Wat is het verschil tussen nudging en dwang en hoe verhoudt nudging zich met andere overheidsinterventies zoals drang, overreden, en advisering? Hebben de rechtsstaat en mensenrechten iet s te zeg gen over deze technieken, of beperkt het recht enkel dwang door de overheid en laat het nudging geheel over aan beleidsmakers? Waar staat het CST in dit breder verhaal over overheidstechnieken?, The Corona Debate and the use of the Covid Safe Ticket (CST) has given us new insights into the phenomenon of nudges, "government pushes in the desired direction". What is the difference between nudging and coercion and how does nudging relate to other government interventions such as coercion, persuasion, and counseling? Do the rule of law and human rights have anything to say about these techniques, or does the law only limit coercion by the government and leave nudging entirely to policy makers? Where does the CST stand in this broader story of government techniques?