An introduction to the intellectual foundations and practical utility of the recent work on fairness and machine learning. Fairness and Machine Learning introduces advanced …
S Mitchell, E Potash, S Barocas… - Annual review of …, 2021 - annualreviews.org
A recent wave of research has attempted to define fairness quantitatively. In particular, this work has explored what fairness might mean in the context of decisions based on the …
T Scantamburlo - Ethics and Information Technology, 2021 - Springer
The problem of fair machine learning has drawn much attention over the last few years and the bulk of offered solutions are, in principle, empirical. However, algorithmic fairness also …
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 …
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 …
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 …
I Valera - Fundamental Questions, 2021 - nomos-elibrary.de
As automated data analysis supplements, and even replaces, human supervision in decision making, there are growing societal concerns about potential unfairness of these …
TD Jui, P Rivas - International Journal of Machine Learning and …, 2024 - Springer
With the increasing influence of machine learning algorithms in decision-making processes, concerns about fairness have gained significant attention. This area now offers significant …
Machine Learning (ML) based predictive systems are increasingly used to support decisions with a critical impact on individuals' lives such as college admission, job hiring, child …