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Assuring Fairness of Algorithmic Decision Making

 
: Hauer, Marc P.; Adler, Rasmus; Zweig, Katharina

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IEEE Computer Society:
IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2021. Proceedings : 12-16 April 2021, Porto de Galinhas, Brazil
Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2021
ISBN: 978-1-6654-4456-9
S.110-113
International Conference on Software Testing, Verification and Validation Workshops (ICSTW) <14, 2021, Online>
Bundesministerium für Arbeit und Soziales (BMAS)
DKI.00.0002 3.20; ExamAI - KI Testing and Auditing
Englisch
Konferenzbeitrag
Fraunhofer IESE ()
ATTD; Assurance Case; Fairness

Abstract
Assuring fairness of an algorithmic decision making (ADM) system is a challenging task involving different and possibly conflicting views on fairness as expressed by multiple fairness measures. We argue that a combination of the agile development framework Acceptance Test-Driven Development (ATDD) and the concept of Assurance Cases from safety engineering is a pragmatic way to assure fairness levels that are adequate for a predefined application. The approach supports examinations by regulating bodies or related auditing processes by providing a structured argument explaining the achieved level of fairness and its sufficiency for the application.

: http://publica.fraunhofer.de/dokumente/N-637958.html