A review on fairness in machine learning

D Pessach, E Shmueli - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
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 …

Trustworthy artificial intelligence: a review

D Kaur, S Uslu, KJ Rittichier, A Durresi - ACM computing surveys (CSUR …, 2022 - dl.acm.org
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 …

Six human-centered artificial intelligence grand challenges

O Ozmen Garibay, B Winslow, S Andolina… - … Journal of Human …, 2023 - Taylor & Francis
Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the
human condition in ways that are not yet well understood. Negative unintended …

A survey on datasets for fairness‐aware machine learning

T Le Quy, A Roy, V Iosifidis, W Zhang… - … Reviews: Data Mining …, 2022 - Wiley Online Library
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 …

Fairness in machine learning: A survey

S Caton, C Haas - ACM Computing Surveys, 2024 - dl.acm.org
When Machine Learning technologies are used in contexts that affect citizens, companies as
well as researchers need to be confident that there will not be any unexpected social …

Bias mitigation for machine learning classifiers: A comprehensive survey

M Hort, Z Chen, JM Zhang, M Harman… - ACM Journal on …, 2024 - dl.acm.org
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 …

A call to action on assessing and mitigating bias in artificial intelligence applications for mental health

AC Timmons, JB Duong, N Simo Fiallo… - Perspectives on …, 2023 - journals.sagepub.com
Advances in computer science and data-analytic methods are driving a new era in mental
health research and application. Artificial intelligence (AI) technologies hold the potential to …

Bias in machine learning software: Why? how? what to do?

J Chakraborty, S Majumder, T Menzies - … of the 29th ACM joint meeting …, 2021 - dl.acm.org
Increasingly, software is making autonomous decisions in case of criminal sentencing,
approving credit cards, hiring employees, and so on. Some of these decisions show bias …

Bias in data‐driven artificial intelligence systems—An introductory survey

E Ntoutsi, P Fafalios, U Gadiraju… - … : Data Mining and …, 2020 - Wiley Online Library
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 …

The relationship between trust in AI and trustworthy machine learning technologies

E Toreini, M Aitken, K Coopamootoo, K Elliott… - Proceedings of the …, 2020 - dl.acm.org
To design and develop AI-based systems that users and the larger public can justifiably
trust, one needs to understand how machine learning technologies impact trust. To guide …