Algorithmic fairness (AF) has been framed as a newly emerging technology that mitigates
systemic discrimination in automated decision‐making, providing opportunities to improve …

Artificial intelligence (AI) and machine learning (ML) are quickly becoming pervasive in ways
that impact the lives of all humans across the globe. In an effort to make otherwise” black …

The unique role that AI plays in making decisions that affect human lives creates a need to
foster improved public understanding of AI systems. Informal learning spaces are particularly …

The related literature and industry press suggest that artificial intelligence (AI)-based
decision-making systems may be biased towards gender, which in turn impacts individuals …

The growth of technologies promising to infer emotions raises political and ethical concerns,
including concerns regarding their accuracy and transparency. A marginalized perspective …

Despite being the fastest-growing field because of its ability to enhance competitive
advantage, there are concerns about the inherent fairness in Artificial Intelligence (AI) …

This paper studies how counterfactual explanations can be used to assess the fairness of a
model. Using machine learning for high-stakes decisions is a threat to fairness as these …

In this critical survey, we analyze typical claims on the relationship between explainable AI
(XAI) and fairness to disentangle the multidimensional relationship between these two …

Artificial intelligence (AI) tools and methods allow researchers and educators to assess
complex patterns and relations among diverse variables (eg, learner backgrounds …

Counterfactual Analysis has shown to be a powerful tool in the burgeoning field of
Explainable Artificial Intelligence. In Supervised Classification, this means associating with …