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 …

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 …

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 …

The debate about the ethical implications of Artificial Intelligence dates from the 1960s
(Samuel in Science, 132 (3429): 741–742, 1960. https://doi. org/10.1126/science. 132.3429 …

As machine learning is increasingly used to inform consequential decision-making (eg, pre-
trial bail and loan approval), it becomes important to explain how the system arrived at its …

Counterfactuals about what could have happened are increasingly used in an array of
Artificial Intelligence (AI) applications, and especially in explainable AI (XAI) …

In reaction to concerns about a broad range of potential ethical issues, dozens of proposals
for addressing ethical aspects of artificial intelligence (AI) have been published. However …

An introduction to the intellectual foundations and practical utility of the recent work on
fairness and machine learning. Fairness and Machine Learning introduces advanced …

Abstract Machine learning can impact people with legal or ethical consequences when it is
used to automate decisions in areas such as insurance, lending, hiring, and predictive …

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 …