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 …

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 …

With the widespread use of artificial intelligence (AI) systems and applications in our
everyday lives, accounting for fairness has gained significant importance in designing and …

We present a systematic approach for achieving fairness in a binary classification setting.
While we focus on two well-known quantitative definitions of fairness, our approach …

Deep neural networks (DNNs) are an indispensable machine learning tool despite the
difficulty of diagnosing what aspects of a model's input drive its decisions. In countless real …

In the past few decades, artificial intelligence (AI) technology has experienced swift
developments, changing everyone's daily life and profoundly altering the course of human …

Unintended bias in Machine Learning can manifest as systemic differences in performance
for different demographic groups, potentially compounding existing challenges to fairness in …

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 …

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 …

We address the problem of algorithmic fairness: ensuring that sensitive information does not
unfairly influence the outcome of a classifier. We present an approach based on empirical …