Robots powered by AI and machine learning are increasingly capable of collaboration and social interaction with humans, leading to a demand to develop new approaches to ensure their transparency and explainable behaviour. 

As explainable AI (XAI) seeks to clarify AI decisions, its integration into physical robots often creates an illusion of explainability—raising questions about whether current approaches truly enhance understanding. 

The 3rd Workshop on Explainability in Human-Robot Collaboration aims to address the real-world concerns associated with developing explainable and transparent robots through a focused, multi-faceted panel discussion and a series of paper presentations.

In this workshop, we will focus on refining when and how explanations should be provided, integrating human communication principles to enhance trust and transparency in human-robot collaboration through both technical and user-centred solutions.