Legal and Ethical Issues in Big Data Discourse

The use of big data is shaping the current data ecosystem with the promise of major advances in key societal sectors like healthcare, government and business, but also raises a number of complex ethical issues related to privacy, ownership, confidentiality, transparency and non-discrimination. It follows that major ethical concerns such as informed consent, confidentiality, privacy and de-identification are put under renewed scrutiny, while reformulating human rights in the light of data usage has become a pressing requirement. For this reason, the intersection between big data and law is gaining momentum among researchers, who remark on the emergence of novel configurations of basic rights and, at the same time, on the innovations that big data brings about in legal science. The chapter concentrates on regulatory frameworks in data protection that attempt to respond to ethical issues posed by big data acquisition, processing, storage and use, especially in those instances in which it sidesteps current directives. The focus is on the European Union’s General Data Protection Regulation (GDPR), its inspiring principles, i.e., fairness, accountability and transparency, main actors, i.e., data subjects, controllers and processors, and criticalities, in particular the notion of purpose. The discourse analysis of the Regulation is set against the background of the 1995 Data Protection Directive (DPD), which predated social media and online services, and the Charter of Fundamental Rights of the European Union, which established data protection as a stand-alone right. By focusing on a number of lexico-grammatical choices and discursive strategies, the analysis illustrates the complexity of data protection against the dematerialisation of the economy in the big data ecosystem and hints at the difficulty to harmonise Member States’ multiple views on privacy. It explores the discursive overlap of law and ethics and the impact that the legal curb on data processing and repurposing is generating.