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 …

Explainable AI provides insights to users into the why for model predictions, offering
potential for users to better understand and trust a model, and to recognize and correct AI …

Explainable artificial intelligence and interpretable machine learning are research domains
growing in importance. Yet, the underlying concepts remain somewhat elusive and lack …

Biases in Artificial Intelligence (AI) systems or their results are one important issue that
demands AI explainability. Despite the prevalence of AI applications, the general public are …

Biases in artificial intelligence (AI), a pressing issue in human-AI interaction, can be
exacerbated by AI systems' opaqueness. This paper reports on our development of a user …

The rapid evolution of AI technologies has reshaped our daily lives. As AI systems become
increasingly prevalent, AI literacy, the ability to comprehend and engage with these …

Despite the progress of Artificial Intelligence (AI) and its contribution to the advancement of
human society, the prioritization of ethical principles from the viewpoint of its users has not …

Despite the progress of Artificial Intelligence (AI) and its contribution to the advancement of
human society, the prioritization of ethical principles from the viewpoint of its users has not …