Database Reference
In-Depth Information
Chapter 1
Data Dilemmas in the Information Society:
Introduction and Overview
Bart Custers
1
Abstract.
This chapter provides and introduction to this topic and an overview of
all chapters. First, it is pointed out what this topic 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 topic 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
topic, 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.
1.1 The Information Society
Vast amounts of data are nowadays collected, stored and processed. These data are
used for making a variety of administrative and governmental decisions. This may
considerably improve the speed, effectiveness and quality of decisions. However,
at the same time, it is common knowledge that most databases contain errors. Data
may not be collected properly, data may be corrupted or missing, and data may be
biased or contain noise. In addition, the process of analyzing the data might
include biases and flaws of its own. This may lead to discrimination. For instance,
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