Explainability for Human-Robot Collaboration

Elmira Yadollahi, Marta Romeo, Fethiye Irmak Dogan, Wafa Johal, Maartje De Graaf, Shelly Levy-Tzedek, Iolanda Leite

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In human-robot collaboration, explainability bridges the communication gap between complex machine functionalities and humans. An active area of investigation in robotics and AI is understanding and generating explanations that can enhance collaboration and mutual understanding between humans and machines. A key to achieving such seamless collaborations is understanding end-users, whether naive or expert, and tailoring explanation features that are intuitive, user-centred, and contextually relevant. Advancing on the topic not only includes modelling humans' expectations for generating the explanations but also requires the development of metrics to evaluate generated explanations and assess how effectively autonomous systems communicate their intentions, actions, and decision-making rationale. This workshop is designed to tackle the nuanced role of explainability in enhancing the efficiency, safety, and trust in human-robot collaboration. It aims to initiate discussions on the importance of generating and evaluating explainability features developed in autonomous agents. Simultaneously, it addresses various challenges, including bias in explainability and downsides of explainability and deception in human-robot interaction.

Original languageEnglish
Title of host publicationHRI '24: Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction
PublisherAssociation for Computing Machinery
Number of pages3
ISBN (Electronic)9798400703232
Publication statusPublished - 11 Mar 2024
Event19th Annual ACM/IEEE International Conference on Human-Robot Interaction 2024 - Boulder, United States
Duration: 11 Mar 202415 Mar 2024


Conference19th Annual ACM/IEEE International Conference on Human-Robot Interaction 2024
Abbreviated titleHRI 2024
Country/TerritoryUnited States


  • Explainable Robotics
  • Human-Centered Robot Explanations
  • XAI

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Electrical and Electronic Engineering


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