Joseph Giovanelli
Data Curator
Matteo Magnini
Data Curator
Liam James
Data Curator
Giovanni Ciatto
Data Curator
S. Angel Marrero
Data Manager
Andrea Borghesi
Data Curator
Gustavo A. Marrero
Data Manager
Roberta Calegari
Data Manager
Valerio Di Zio
University of Bologna
This is the repository for the code and dataset of the paper intitled “Unfair Inequality in Education: A Benchmark for AI-Fairness Research” submitted to the DEMO track of the 27TH European Conference on Artificial Intelligence (ECAI).
This paper proposes a novel benchmark specifically designed for AI fairness research in education. It can be used for challenging tasks aimed at improving students’ performance and reducing dropout rates which are also discussed in the paper to emphasize significant research directions. By prioritizing fairness, this benchmark aims to foster the development of bias-free AI solutions, promoting equal educational access and outcomes for all students.
Access here to know more.
Joseph Giovanelli
Data Curator
Matteo Magnini
Data Curator
Liam James
Data Curator
Giovanni Ciatto
Data Curator
S. Angel Marrero
Data Manager
Andrea Borghesi
Data Curator
Gustavo A. Marrero
Data Manager
Roberta Calegari
Data Manager
Valerio Di Zio
University of Bologna