GAM Coach: Towards Interactive and User-centered Algorithmic Recourse

Machine learning (ML) recourse techniques are increasingly used in high-stakes domains, providing end users with actions to alter ML predictions, but they assume ML developers understand what input variables can be changed. However, a recourse plan's actionability is subjective and unlikely to...

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Veröffentlicht in:	arXiv.org 2023-03
Hauptverfasser:	Wang, Zijie J, Jennifer Wortman Vaughan, Caruana, Rich, Duen Horng Chau
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Computer Science - Artificial Intelligence Computer Science - Human-Computer Interaction Computer Science - Learning Empirical analysis End users Integer programming Linear programming Machine learning User satisfaction
Online-Zugang:	Volltext
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