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 …

A recent wave of research has attempted to define fairness quantitatively. In particular, this
work has explored what fairness might mean in the context of decisions based on the …

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 rapid development of Artificial Intelligence (AI) technology has enabled the deployment
of various systems based on it. However, many current AI systems are found vulnerable to …

This paper provides a comprehensive survey of techniques for testing machine learning
systems; Machine Learning Testing (ML testing) research. It covers 144 papers on testing …

Fairness is an increasingly important concern as machine learning models are used to
support decision making in high-stakes applications such as mortgage lending, hiring, and …

The potential for machine learning (ML) systems to amplify social inequities and unfairness
is receiving increasing popular and academic attention. A surge of recent work has focused …

Algorithm fairness has started to attract the attention of researchers in AI, Software
Engineering and Law communities, with more than twenty different notions of fairness …

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 …

Computers are increasingly used to make decisions that have significant impact on people's
lives. Often, these predictions can affect different population subgroups disproportionately …