Discrimination Data Analysis: A Multi-disciplinary Bibliography - Discrimination and Privacy in the Information Society - page 118

This issue has been observed in (Pope & Sydnor, 2007; Ruggieri et al., 2010a).
We categorize three non mutually-exclusive strategies toward discrimination pre-
vention: (i) a controlled distortion of the training set (a pre-processing approach)
(Kamiran & Calders, 2009; Zliobaite et al., 2011; Luong et al., 2011; Hajian et al.,
2011); (ii) a modification of the classification learning algorithm (an in-processing
approach), by integrating anti-discrimination criteria within it (Calders & Verwer,
2010; Kamiran et al., 2010; Kamishima et al., 2011); (iii) a post-processing of the
classification model, once it has been extracted, to correct its decision criteria (Pe-
dreschi et al., 2009; Calders & Verwer, 2010).

6.7 Conclusions

The collection and analysis of observational and experimental data is the main
tool for assessing the presence, the extent, the nature, and the trend of discrimi-
nation phenomena. In this chapter, we provided an annotated bibliography of the
main references and of recent works on discrimination data analysis from a multi-
disciplinary perspective. Our intended objective was to provide a guidance through
the abundant literature to researchers and anti-discrimination analysts that are faced
with data analysis problems. Substantively, the reader is referred to works on so-
ciological causes, legal norms, economic models, empirical studies, data collection
approaches, profiling methods, discrimination discovery techniques, and discrimi-
nation prevention algorithms in data mining. The bibliography section includes 262
references, half of which appeared in the last five years (2007-2011). This demon-
strates a never-ending interest on the topic of discrimination data analysis.

References

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