Artificial Intelligence (AI) has made its way into various scientific fields, providing astonishing
improvements over existing algorithms for a wide variety of tasks. In recent years, there have …

Ethical AI has become increasingly important, and it has been attracting attention from
academia and industry, due to its increased popularity in real-world applications with …

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 …

Privacy and fairness are two crucial pillars of responsible Artificial Intelligence (AI) and
trustworthy Machine Learning (ML). Each objective has been independently studied in the …

The definition and implementation of fairness in automated decisions has been extensively
studied by the research community. Yet, there hides fallacious reasoning, misleading …

Algorithmic discrimination is one of the significant concerns in applying machine learning
models to a real-world system. Many researchers have focused on developing fair machine …

In the current era, people and society have grown increasingly reliant on artificial
intelligence (AI) technologies. AI has the potential to drive us towards a future in which all of …

Concerns about the societal impact of AI-based services and systems has encouraged
governments and other organisations around the world to propose AI policy frameworks to …

Data practices shape research and practice on fairness in machine learning (fair ML).
Critical data studies offer important reflections and critiques for the responsible …

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 …