Bias analysis of AI models for undergraduate student admissions

Bias detection and mitigation is an active area of research in machine learning. This work extends previous research done by the authors Van Busum and Fang (Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023) to provide a rigorous and more complete analysis of the bias found in...

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Veröffentlicht in:	Neural computing & applications Jg. 37; H. 12; S. 7785 - 7795
Hauptverfasser:	Van Busum, Kelly, Fang, Shiaofen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.04.2025 Springer Nature B.V
Schlagworte:	Artificial Intelligence Bias Colleges & universities Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Decisions Demographics Image Processing and Computer Vision Machine learning Prediction models Probability and Statistics in Computer Science Research facilities S.I.: From Theory to Practice: Real-World Applications of AI in Data Science Special Issue on From Theory to Practice: Real-World Applications of AI in Data Science Undergraduate study Urban research Test-optional Bias College admissions Machine learning Predictive model
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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