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 …
Bias and unfairness in machine learning models: a systematic review on datasets, tools, fairness metrics, and identification and mitigation methods
TP Pagano, RB Loureiro, FVN Lisboa… - Big data and cognitive …, 2023 - mdpi.com
One of the difficulties of artificial intelligence is to ensure that model decisions are fair and
free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and …
free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and …
Making it possible for the auditing of ai: A systematic review of ai audits and ai auditability
Artificial intelligence (AI) technologies have become the key driver of innovation in society.
However, numerous vulnerabilities of AI systems can lead to negative consequences for …
However, numerous vulnerabilities of AI systems can lead to negative consequences for …
Bias and unfairness in machine learning models: a systematic literature review
TP Pagano, RB Loureiro, FVN Lisboa… - arXiv preprint arXiv …, 2022 - arxiv.org
One of the difficulties of artificial intelligence is to ensure that model decisions are fair and
free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and …
free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and …
Surviving in Diverse Biases: Unbiased Dataset Acquisition in Online Data Market for Fair Model Training
The online data markets have emerged as a valuable source of diverse datasets for training
machine learning (ML) models. However, datasets from different data providers may exhibit …
machine learning (ML) models. However, datasets from different data providers may exhibit …
Fairness challenges in artificial intelligence
S Chakrobartty, OF El-Gayar - Encyclopedia of Data Science and …, 2023 - igi-global.com
Fairness is a highly desirable human value in day-to-day decisions that affect human life. In
recent years many successful applications of AI systems have been developed, and …
recent years many successful applications of AI systems have been developed, and …
ProxiMix: Enhancing Fairness with Proximity Samples in Subgroups
Many bias mitigation methods have been developed for addressing fairness issues in
machine learning. We found that using linear mixup alone, a data augmentation technique …
machine learning. We found that using linear mixup alone, a data augmentation technique …
Investigating trade-offs for fair machine learning systems
M Hort - 2023 - discovery.ucl.ac.uk
Fairness in software systems aims to provide algorithms that operate in a nondiscriminatory
manner, with respect to protected attributes such as gender, race, or age. Ensuring fairness …
manner, with respect to protected attributes such as gender, race, or age. Ensuring fairness …
[PDF][PDF] BIAS AND UNFAIRNESS IN MACHINE LEARNING MODELS: A SYSTEMATIC LITERATURE REVIEW
TPPRB Loureiro, FVN Lisboa, GOR Cruz… - arXiv preprint arXiv …, 2022 - researchgate.net
One of the difficulties of artificial intelligence is to ensure that model decisions are fair and
free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and …
free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and …