From Privacy to Algorithms’ Fairness

This article aims to show how the legal and ethical debate – as far as ethics has become an indispensable complementary normative tool within legal frameworks – on the digital world in the United States (US) and the European Union (EU) has significantly opened up to include new dimensions other than privacy, particularly in connection with machine learning algorithms and Big Data. If privacy still remains the main interpretive construct to normatively forge the digital space, increasingly issues of discrimination, equal opportunity, fairness and, more broadly, models of justice, are entering the picture. While offering some examples of the inadequacy of privacy to cover new normative concerns related to Big Data and machine learning, the article also argues that attempts to grant algorithmic fairness represent just the first step in addressing the wider question about what models of digital justice we are willing to apply.