TY - JOUR
T1 - Legal perspective on possible fairness measures – A legal discussion using the example of hiring decisions
AU - Hauer, Marc P.
AU - Kevekordes, Johannes
AU - Haeri, Maryam Amir
N1 - Funding Information:
Moreover, the research has also been conducted within the project “Fairand Good ADM” (16ITA203) funded by the Federal Ministryof Education and Research (BMBF) of Germany.
Funding Information:
The research was performed within the project GOAL “Governance of and by algorithms” (Funding code 01IS19020; https://goal-projekt.de/en/ ) which is funded by the German Federal Ministry of Education and Research . The content of this paper is the sole responsibility of its authors.
Publisher Copyright:
© 2021 Marc P. Hauer, Johannes Kevekordes, Maryam Amir Haeri
PY - 2021/9
Y1 - 2021/9
N2 - With the increasing use of AI in algorithmic decision making (e.g. based on neural networks), the question arises how bias can be excluded or mitigated. There are some promising approaches, but many of them are based on a ”fair” ground truth, others are based on a subjective goal to be reached, which leads to the usual problem of how to define and compute ”fairness”. The different functioning of algorithmic decision making in contrast to human decision making leads to a shift from a process-oriented to a result-oriented discrimination assessment. We argue that with such a shift society needs to determine which kind of fairness is the right one to choose for which certain scenario. To understand the implications of such a determination we explain the different kinds of fairness concepts that might be applicable for the specific application of hiring decisions, analyze their pros and cons with regard to the respective fairness interpretation and evaluate them from a legal perspective (based on EU law).
AB - With the increasing use of AI in algorithmic decision making (e.g. based on neural networks), the question arises how bias can be excluded or mitigated. There are some promising approaches, but many of them are based on a ”fair” ground truth, others are based on a subjective goal to be reached, which leads to the usual problem of how to define and compute ”fairness”. The different functioning of algorithmic decision making in contrast to human decision making leads to a shift from a process-oriented to a result-oriented discrimination assessment. We argue that with such a shift society needs to determine which kind of fairness is the right one to choose for which certain scenario. To understand the implications of such a determination we explain the different kinds of fairness concepts that might be applicable for the specific application of hiring decisions, analyze their pros and cons with regard to the respective fairness interpretation and evaluate them from a legal perspective (based on EU law).
KW - Fairness measures
KW - Human resources
UR - http://www.scopus.com/inward/record.url?scp=85112558955&partnerID=8YFLogxK
U2 - 10.1016/j.clsr.2021.105583
DO - 10.1016/j.clsr.2021.105583
M3 - Article
AN - SCOPUS:85112558955
VL - 42
JO - Computer law & security review
JF - Computer law & security review
SN - 0267-3649
M1 - 105583
ER -