LiFT: A Scalable Framework for Measuring Fairness in ML Applications

Many internet applications are powered by machine learned models, which are usually trained on labeled datasets obtained through either implicit / explicit user feedback signals or human judgments. Since societal biases may be present in the generation of such datasets, it is possible for the traine...

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Veröffentlicht in:	arXiv.org 2020-08
Hauptverfasser:	Vasudevan, Sriram, Kenthapadi, Krishnaram
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Computers and Society Computer Science - Learning Computer Science - Software Engineering Datasets Toolkits
Online-Zugang:	Volltext
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