Titlebook: Discrimination and Privacy in the Information Society; Data Mining and Prof Bart Custers,Toon Calders,Tal Zarsky Book 2013 Springer-Verlag

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The Discovery of Discriminationon records.We discuss the challenging problems in discrimination discovery, and present, in a unified form, a framework based on classification rules extraction and filtering on the basis of legally-grounded interestingness measures. The framework is implemented in the publicly available DCUBE tool.

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Risks of Profiling and the Limits of Data Protection Lawlude discrimination, de-individualisation and stereotyping. To mitigate these risks, the right to privacy is traditionally invoked. However, given the rapid technological developments in the area of profiling, it is questionable whether the right to informational privacy and data protection law prov

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Explainable and Non-explainable Discrimination in Classificationssifiers) premised on historical data. If the historical data was discriminating towards socially and legally protected groups, a model learnt over this data will make discriminatory decisions in the future. As a solution, most of the discrimination free modeling techniques force the treatment of th

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Combining and Analyzing Judicial Databasesed. Combined data from different organizations may then be analyzed, for instance, to investigate how specific groups of suspects move through the system. Such insight is useful for several reasons, for example, to define an effective and coherent safety policy. To integrate or relate judicial data

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Privacy-Preserving Data Mining Techniques: Survey and Challenges tentative taxonomy of PPDM as a field. The main axes of this taxonomy specify what kind of data is being protected, and what is the ownership of the data (centralized or distributed). We comment on the relationship between PPDM and preventing discriminatory use of data mining techniques. We round u