The limits of privacy in automated profiling and data mining

Abstract Automated profiling of groups and individuals is a common practice in our information society. The increasing possibilities of data mining significantly enhance the abilities to carry out such profiling. Depending on its application, profiling and data mining may cause particular risks such as discrimination, de-individualisation and information asymmetries. In this article we provide an overview of the risks associated with data mining and the strategies that have been proposed over the years to mitigate these risks. From there we shall examine whether current safeguards that are mainly based on privacy and data protection law (such as data minimisation and data exclusion) are sufficient. Based on these findings we shall suggest alternative policy options and regulatory instruments for dealing with the risks of data mining, integrating ideas from the field of computer science and that of law and ethics.