Personal Data, Algorithms and Profiling in the EU: Overcoming the Binary Notion ofPersonal Data through Quantum Mechanics
In this paper I propose to analyse the binary notion of personal data and highlight its limits, in order to propose a different conception of personal data. From a risk regulation perspective, the binary notion of personal data is not particularly fit for purpose, considering that data collection and information flows are tremendously big and complex. As a result, the use of a binary system to determine the applicability of EU data protection law may be a simplistic approach. In an effort of bringing physics and law together, certain principles elaborated within the quantum theory are surprisingly applicable to data protection law, and can be used as guidance to shed light on many of today’s data complexities. Lastly, I will discuss the implications and the effects that certain processing operations may have on the possibility of qualifying certain data as personal. In other terms, how the chances to identify certain data as personal is dependent upon the processing operations that a data controller might put in place.
|Persistent URL||dx.doi.org/10.5553/ELR.000114, hdl.handle.net/1765/115660|
|Series||Erasmus Law Review|
|Journal||Erasmus Law Review|
El Khoury, A. (2019). Personal Data, Algorithms and Profiling in the EU: Overcoming the Binary Notion ofPersonal Data through Quantum Mechanics. Erasmus Law Review, 11(3), 165–177. doi:10.5553/ELR.000114