Algorithmic Discrimination - A LOEWE-SAFE Project

Algorithmic Discrimination

Algorithms are a central part of today’s modern life. These man-made programmed tools are subject to prejudice, as described in the research work of Sweeney on search engines (2013).

A special challenge for politics consists in the regulation of algorithmic discrimination (AD), which could be observed exemplarily in the verdict of the european court of justice (EuGH) of the year 2011. As a result of the binding gender neutrality in the collection of data for health insurances, a price increase was induced for male customers. This again resulted in a general decrease of societal welfare.

Furthermore, a lack of transparency of the market structures and the price-setting processes hinder the comprehensibility for consumers on online platforms.

This leads to the following problem for political decision-makers if and to what extent a market intervention may be useful to enable efficient price-setting processes in the sense of society. The goal of this research undertaking is a data-driven analysis of algorithmic discrimination to derive meaningful and suitable recommendations for action for politics and business.

Against this background, the research group “Algorithmic Discrimination”, which includes Benjamin Abdel-Karim and Nicolas Pfeuffer, faces the following research questions:

·        Is AD recognizable for the end-user?

·        Can AD be automatically detected by certain indicators?

·        Does the price-shift take place at the intermediary or the supplier?

·        Which factors influence the price-setting process?

The research methodology includes data acquisition, methods of simulation, as well as the analysis of the collected data through empirical research methods from econometrics, statistics and machine learning to answer the posed research questions and to derive recommendations for action for politics and business.