Automated Data Cleaning can Hurt Fairness in Machine Learning-Based Decision Making

In this paper, we interrogate whether data quality issues track demographic group membership (based on sex, race and age) and whether automated data cleaning - of the kind commonly used in production ML systems - impacts the fairness of predictions made by these systems. To the best of our knowledge...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering 2024-12, Vol.36 (12), p.7368-7379
Hauptverfasser:	Guha, Shubha, Khan, Falaah Arif, Stoyanovich, Julia, Schelter, Sebastian
Format:	Artikel
Sprache:	eng
Schlagworte:	Cleaning data cleaning Data integrity Data models data preparation Decision making fairness in machine learning Medical services Production Responsible data management Task analysis
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