A Survey On The Approaches For Discrimination Prevention In Data Mining
Data mining is an important technology for extracting useful patterns from large amount of data. But there are
negative social perceptions about data mining, the most important ones being potential privacy invasion and potential
discrimination. In data mining, discrimination is a very important issue when considering the legal and ethical aspects of
privacy preservation. Most people do not have a wish to be discriminated on the basis of their race, nationality, religion, age
and so on. The problem of discrimination mainly arises when these kind of attributes are used for making decisions such as
giving them a job and loan. For this very reason, discovering such attributes and eliminating them from the training data
without affecting their decision-making utility is essential. Beyond discrimination discovery, a more challenging issue is to
prevent knowledge-based decision support systems from making discriminatory decisions. The approaches for antidiscrimination
techniques are studied in this paper.
Keywords—Data Mining; Discrimination Prevention; Direct and Indirect Discrimination; Anti-Discrimination.