Abstract
This chapter provides and introduction to this book and an overview of all chapters. First, it is pointed out what this book is about: discrimination and privacy issues of data mining and profiling and solutions (both technological and non-technological) for these issues. A large part of this book is based on research results of a project on how and to what extent legal and ethical rules can be integrated in data mining algorithms to prevent discrimination. Since this is an introductory chapter, it is explained what data mining and profiling are and why we need these tools in an information society. Despite this unmistakable need, however, data mining and profiling may also have undesirable effects, particularly discriminatory effects and privacy infringements. This creates dilemmas on how to deal with data mining and profiling. Regulation may take place using laws, norms, market forces and code (i.e., constraints in the architecture of technologies). This chapter concludes with an overview of the structure of this book, containing chapters on the opportunities of data mining and profiling, possible discrimination and privacy issues, practical applications and solutions in code, law, norms and the market.
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Custers, B. (2013). Data Dilemmas in the Information Society: Introduction and Overview. In: Custers, B., Calders, T., Schermer, B., Zarsky, T. (eds) Discrimination and Privacy in the Information Society. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 3. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30487-3_1
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