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2021
Conference Paper
Titel
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)
Project(s)
ExamAI - KI Testing and Auditing
Funder
Bundesministerium für Arbeit und Soziales BMAS (Deutschland)