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  4. Assuring Fairness of Algorithmic Decision Making
 
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2021
Conference Paper
Title

Assuring Fairness of Algorithmic Decision Making

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.
Author(s)
Hauer, Marc P.
Adler, Rasmus  
Fraunhofer-Institut für Experimentelles Software Engineering IESE  
Zweig, Katharina
Mainwork
IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2021. Proceedings  
Project(s)
ExamAI - KI Testing and Auditing
Funder
Bundesministerium für Arbeit und Soziales  
Conference
International Conference on Software Testing, Verification and Validation Workshops (ICSTW) 2021  
DOI
10.1109/ICSTW52544.2021.00029
Language
English
Fraunhofer-Institut für Experimentelles Software Engineering IESE  
Keyword(s)
  • ATTD

  • Assurance Case

  • Fairness

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