The Way Forward - Discrimination and Privacy in the Information Society - page 327

Chapter 19
The Way Forward
Bart Custers, Toon Calders, Tal Zarsky, and Bart Schermer *
Abstract. The growing use of data mining practices by both government and
commercial entities leads to both great promises and challenges. They hold the
promise of facilitating an information environment which is fair, accurate
and efficient. At the same time, they might lead to practices which are both
invasive and discriminatory, yet in ways the law has yet to grasp. This point is
demonstrated by showing how the common measures for mitigating privacy
concerns, such as a priori limiting measures (particularly access controls,
anonymity and purpose specification) are mechanisms that are increasingly failing
solutions against privacy and discrimination issues in this novel context.
Instead, a focus on (a posteriori) accountability and transparency may be more
useful. This requires improved detection of discrimination and privacy violations
as well as designing and implementing techniques that are discrimination-free and
privacy-preserving. This requires further (technological) research.
But even with further technological research, there may be new situations and
new mechanisms through which privacy violations or discrimination may take
place. Novel predictive models can prove to be no more than sophisticated tools to
mask the "classic" forms of discrimination, by hiding discrimination behind new
proxies. Also, discrimination might be transferred to new forms of population
segments, dispersed throughout society and only connected by some attributes
they have in common. Such groups will lack political force to defend their
interests. They might not even know what is happening.
With regard to privacy, the adequacy of the envisaged European legal
framework is discussed in the light of data mining and profiling. The European