I. The problem(s)
Data security represents one of the main problems of this data yield generation, since a higher magnitude of data is correlated with a loose control and higher fraud probability, with a higher likelihood of losing own privacy, and becoming targets of illicit or unethical activities. Today more than ever a universal data regulation is needed — and some steps have already been taken toward one (OECD, 2013). This is especially true because everyone claims privacy leakages, but no one wants to give up on the extra services and customized products that companies are developing based on our personal data.
It is essential to protect individual privacy without erasing companies’ capacity to use data for driving businesses in a heterogeneous but harmonized way. Any fragment of data has to be collected with prior explicit consent, and guaranteed and controlled against manipulation and fallacies. A privacy assessment to understand how people would be affected by the use of data is crucial as well.
II. Fairness and Data Minimization
There are two important concepts to be considered from a data protection point of view: fairness and minimization.
Fairness concerns how data are obtained, and the transparency needed from organizations that are collecting them, especially about their future potential uses.
Data minimization, instead, regards the ability of gathering …
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