A review on fairness in machine learning
An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …
Algorithmic fairness
An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence (AI) and machine learning (ML) algorithms in spheres …
controlled by artificial intelligence (AI) and machine learning (ML) algorithms in spheres …
A brief review on algorithmic fairness
Abstract Machine learning algorithms are widely used in management systems in different
fields, such as employee recruitment, loan provision, disease diagnosis, etc., and even in …
fields, such as employee recruitment, loan provision, disease diagnosis, etc., and even in …
A snapshot of the frontiers of fairness in machine learning
A Chouldechova, A Roth - Communications of the ACM, 2020 - dl.acm.org
A snapshot of the frontiers of fairness in machine learning Page 1 82 COMMUNICATIONS OF
THE ACM | MAY 2020 | VOL. 63 | NO. 5 review articles ILL US TRA TION B Y JUS TIN METZ …
THE ACM | MAY 2020 | VOL. 63 | NO. 5 review articles ILL US TRA TION B Y JUS TIN METZ …
A comparative study of fairness-enhancing interventions in machine learning
SA Friedler, C Scheidegger… - Proceedings of the …, 2019 - dl.acm.org
Computers are increasingly used to make decisions that have significant impact on people's
lives. Often, these predictions can affect different population subgroups disproportionately …
lives. Often, these predictions can affect different population subgroups disproportionately …
Putting fairness principles into practice: Challenges, metrics, and improvements
A Beutel, J Chen, T Doshi, H Qian, A Woodruff… - Proceedings of the …, 2019 - dl.acm.org
As more researchers have become aware of and passionate about algorithmic fairness,
there has been an explosion in papers laying out new metrics, suggesting algorithms to …
there has been an explosion in papers laying out new metrics, suggesting algorithms to …
A confidence-based approach for balancing fairness and accuracy
We study three classical machine learning algorithms in the context of algorithmic fairness:
adaptive boosting, support vector machines, and logistic regression. Our goal is to maintain …
adaptive boosting, support vector machines, and logistic regression. Our goal is to maintain …
Mathematical notions vs. human perception of fairness: A descriptive approach to fairness for machine learning
Fairness for Machine Learning has received considerable attention, recently. Various
mathematical formulations of fairness have been proposed, and it has been shown that it is …
mathematical formulations of fairness have been proposed, and it has been shown that it is …
The frontiers of fairness in machine learning
A Chouldechova, A Roth - arXiv preprint arXiv:1810.08810, 2018 - arxiv.org
The last few years have seen an explosion of academic and popular interest in algorithmic
fairness. Despite this interest and the volume and velocity of work that has been produced …
fairness. Despite this interest and the volume and velocity of work that has been produced …
Ensuring fairness beyond the training data
We initiate the study of fair classifiers that are robust to perturbations in the training
distribution. Despite recent progress, the literature on fairness has largely ignored the …
distribution. Despite recent progress, the literature on fairness has largely ignored the …