Preventing discrimination in the automated targeting of job advertisements

摘要

On the background of the increasing amount of discriminatory challenges facing artificial intelligence applications, this paper examines the requirements that are needed to comply with European non-discrimination law to prevent discrimination in the automated online job advertising business. This paper explains under which circumstance the automated targeting of job advertisements can amount to direct or indirect discrimination. The paper concludes with technical recommendations to dismantle the dangers of automated job advertising. Various options like influencing the pre-processing of big data and altering the algorithmic models are evaluated. This paper also examines the possibilities of using techniques like data mining and machine learning to actively battle direct and indirect discrimination. The European non-discrimination directives 2000/43/EC, 2000/78/EC, and 2006/54/EC which prohibit direct and indirect discrimination in the field of employment on the grounds of race or ethnic origin, sex, sexual orientation, religious belief, age and disability are used as a legal framework. (C) 2017 David Jacobus Dalenberg. Published by Elsevier Ltd. All rights reserved.