Automating decision systems has led to hidden biases in the use of artificial intelligence (AI).
Consequently, explaining these decisions and identifying responsibilities has become a …

With the increasing influence of machine learning algorithms in decision-making processes,
concerns about fairness have gained significant attention. This area now offers significant …

The widespread use of artificial intelligence (AI) systems across various domains is
increasingly highlighting issues related to algorithmic fairness, especially in high-stakes …

Artificial intelligence (AI) has rapidly become one of the technologies used for competitive
advantage. However, there are also growing concerns about bias in AI models as AI …

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 …

A key insight from research on organizational justice is that fairness is in the eye of the
beholder. With increasing discussions–especially among computer scientists and …

This article provides a comprehensive overview of the fairness issues in artificial intelligence
(AI) systems, delving into its background, definition, and development process. The article …

The advent of artificial intelligence (AI) and machine learning algorithms has led to
opportunities as well as challenges in their use. In this overview paper, we begin with a …

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 …

Fairlearn is an open source project to help practitioners assess and improve fairness of
artificial intelligence (AI) systems. The associated Python library, also named fairlearn …