FairLay-ML: Intuitive Debugging of Fairness in Data-Driven Social-Critical Software

Data-driven software solutions have significantly been used in critical domains with significant socio-economic, legal, and ethical implications. The rapid adoptions of data-driven solutions, however, pose major threats to the trustworthiness of automated decision-support software. A diminished unde...

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Veröffentlicht in:	Proceedings (IEEE/ACM International Conference on Software Engineering Companion. Online) S. 25 - 28
Hauptverfasser:	Yu, Normen, Carreon, Luciana, Tan, Gang, Tizpaz-Niari, Saeid
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 27.04.2025
Schlagworte:	ai fairness Data models Data visualization Debugging Ethics fairness mitigation Law Logic Socioeconomics Software Software engineering Surveys toolkit
ISSN:	2574-1934
Online-Zugang:	Volltext
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