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 …
Trustworthy artificial intelligence: a review
Artificial intelligence (AI) and algorithmic decision making are having a profound impact on
our daily lives. These systems are vastly used in different high-stakes applications like …
our daily lives. These systems are vastly used in different high-stakes applications like …
A survey on datasets for fairness‐aware machine learning
As decision‐making increasingly relies on machine learning (ML) and (big) data, the issue
of fairness in data‐driven artificial intelligence systems is receiving increasing attention from …
of fairness in data‐driven artificial intelligence systems is receiving increasing attention from …
Fairness without demographics through adversarially reweighted learning
Much of the previous machine learning (ML) fairness literature assumes that protected
features such as race and sex are present in the dataset, and relies upon them to mitigate …
features such as race and sex are present in the dataset, and relies upon them to mitigate …
Bias in data‐driven artificial intelligence systems—An introductory survey
Artificial Intelligence (AI)‐based systems are widely employed nowadays to make decisions
that have far‐reaching impact on individuals and society. Their decisions might affect …
that have far‐reaching impact on individuals and society. Their decisions might affect …
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 …
Fairness constraints: A flexible approach for fair classification
Algorithmic decision making is employed in an increasing number of real-world applications
to aid human decision making. While it has shown considerable promise in terms of …
to aid human decision making. While it has shown considerable promise in terms of …
Fairness-aware ranking in search & recommendation systems with application to linkedin talent search
SC Geyik, S Ambler, K Kenthapadi - Proceedings of the 25th acm sigkdd …, 2019 - dl.acm.org
We present a framework for quantifying and mitigating algorithmic bias in mechanisms
designed for ranking individuals, typically used as part of web-scale search and …
designed for ranking individuals, typically used as part of web-scale search and …
Bias mitigation for machine learning classifiers: A comprehensive survey
This article provides a comprehensive survey of bias mitigation methods for achieving
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …