Trustworthy AI is becoming ever more important in both machine learning and legal
domains. One important consequence is that decision makers must seek to guarantee a'fair' …

Trustworthy AI becomes ever more important, both in machine learning and in the law. One
important consequence is that decision makers must seek to guarantee afair', ie, non …

Algorithms learned from data are increasingly used for deciding many aspects in our life:
from movies we see, to prices we pay, or medicine we get. Yet there is growing evidence …

AI-driven decision-making can lead to discrimination against certain individuals or social
groups based on protected characteristics/attributes such as race, gender, or age. The …

Machine learning and access to big data are revolutionizing the way many industries
operate, providing analytics and automation to many aspects of real-world practical tasks …

The problem of fair machine learning has drawn much attention over the last few years and
the bulk of offered solutions are, in principle, empirical. However, algorithmic fairness also …

Fairness in Artificial Intelligence rightfully receives a lot of attention these days. Many life-
impacting decisions are being partially automated, including health-care resource planning …

Increasingly, discrimination by algorithms is perceived as a societal and legal problem. As a
response, a number of criteria for implementing algorithmic fairness in machine learning …

Abstract Machine learning algorithms can now identify patterns and correlations in (big)
datasets and predict outcomes based on the identified patterns and correlations. They can …

Using machine learning algorithms in social environments and systems requires stricter and
more detailed control. More specifically, the cost of error in such systems is much higher …