Recently human–robot collaboration (HRC) has emerged as a promising paradigm for mass
personalization in manufacturing owing to the potential to fully exploit the strength of human …

Humans are increasingly relying on complex systems that heavily adopts Artificial
Intelligence (AI) techniques. Such systems are employed in a growing number of domains …

Interpretability in machine learning (ML) is crucial for high stakes decisions and
troubleshooting. In this work, we provide fundamental principles for interpretable ML, and …

Abstract Current developments in Artificial Intelligence (AI) led to a resurgence of
Explainable AI (XAI). New methods are being researched to obtain information from AI …

The automotive industry has witnessed an increasing level of development in the past
decades; from manufacturing manually operated vehicles to manufacturing vehicles with a …

Abstract Explainable Artificial Intelligence (XAI), ie, the development of more transparent and
interpretable AI models, has gained increased traction over the last few years. This is due to …

There has been a recent resurgence in the area of explainable artificial intelligence as
researchers and practitioners seek to provide more transparency to their algorithms. Much of …

Collaborative robots (cobots) have been increasingly adopted in industries to facilitate
human–robot collaboration. Despite this, it is challenging to program cobots for collaborative …

Research into Explainable Artificial Intelligence (XAI) has been increasing in recent years as
a response to the need for increased transparency and trust in AI. This is particularly …

As more non-AI experts use complex AI systems for daily tasks, there has been an
increasing effort to develop methods that produce explanations of AI decision making that …