Measuring Discrimination in Socially-Sensitive Decision Records.

Discrimination in social sense (e.g., against minorities and disadvantaged groups) is the subject of many laws worldwide, and it has been extensively studied in the social and economic sciences. We tackle the problem of determining, given a dataset of historical decision records, a precise measure of the degree of discrimination suffered by a given group (e.g., an etnic minority) in a given context (e.g., a geographic area) with respect to the decision (e.g. credit denial). In our approach, this problem is rephrased in a classification rule based setting, and a collection of quantitative measures of discrimination is introduced, on the basis of existing norms and regulations. The measures are defined as functions of the contingency table of a classification rule, and their statistical significance is assessed, relying on a large body of statistical inference methods for proportions. Based on this basic method, we are then able to address the more general problems of: (1) unveilin...

• Type: Conference
• Year: 2009
• Where: SDM
• Authors: Dino Pedreschi, Franco Turini, Salvatore Ruggieri
• Keywords: Computer Science, Discrimination Analysis, Discriminatory Decision Patterns, SDM 2009, Unveiling Discrimination