Generative AI technologies are growing in power, utility, and use. As generative
technologies are being incorporated into mainstream applications, there is a need for …

Explainable AI (XAI) is increasingly being used in the healthcare domain. In health
management, clinicians and patients are critical stakeholders, requiring tailored XAI …

Recent advancements in machine learning have spurred an increased integration of AI in
critical sectors such as healthcare and criminal justice. The ethical and legal concerns …

In this era of complex software systems and artificial intelligence (AI), software in both
personal and professional spaces has become more opaque and difficult to use. Research …

Artificial intelligence (AI) is becoming integral to many areas of life, yet many—if not most—
AI systems are opaque black boxes. This lack of transparency is a major source of concern …

In this work, we performed a user study in which participants had to solve a human-robot
teaming decision-making task (the Connect 4 game) with an explainable vs non-explainable …

Over the past decade explainable artificial intelligence has evolved from a predominantly
technical discipline into a field that is deeply intertwined with social sciences. Insights such …

A key potential advantage of modern training technologies relates to the ability to use them
to automate aspects of training. Although in the early stages of adoption within the aviation …

The increasing integration of Machine Learning (ML) into decision-making across various
sectors has raised concerns about ethics, legality, explainability, and safety, highlighting the …

Abstract The eXplainable Artificial Intelligence (XAI) research agenda is constantly
expanding. From a mainly technical topic, it has now developed into a multidisciplinary area …