FairAIED: Navigating Fairness, Bias, and Ethics in Educational AI
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FairAIED: Navigating Fairness, Bias, and Ethics in Educational AI Applications

26 July 2024

Sribala Vidyadhari Chinta

Matthew Gonzalez

Wenbin Zhang

Papers citing "FairAIED: Navigating Fairness, Bias, and Ethics in Educational AI Applications"

6 / 6 papers shown

Title
Fairness in Large Language Models: A Taxonomic Survey Zhibo Chu Zichong Wang Wenbin Zhang AILaw 33 31 0 31 Mar 2024
Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrences Thomas Guyet Wenbin Zhang Albert Bifet AI4TS 34 8 0 27 Jan 2022
Interpretable Visual Understanding with Cognitive Attention Network Xuejiao Tang Wenbin Zhang Yi Yu Kea Turner Tyler Derr Mengyu Wang Eirini Ntoutsi 42 12 0 06 Aug 2021
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 192 730 0 13 Dec 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 185 2,079 0 24 Oct 2016
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 154 25,150 0 09 Jun 2011