Project Webinar | Explainability Techniques for Human-AI Collaboration: From Concept to Practical Demonstration
Year: 2026
Type: article
Abstract: This webinar, “Explainability Techniques for Human-AI Collaboration: From Concept to Practical Demonstration,” was organised within the framework of the EU-funded HumAIne project and held online on 15 January 2026. The session introduced HumAIne’s Explainability component, presenting its development, functionality and role within the broader HumAIne architecture. It explored how Explainable AI (XAI) techniques can support Human-AI collaboration by making AI-generated outputs and recommendations more understandable and transparent to human users. The webinar combined the conceptual and technical background of the Explainability component with a practical demonstration based on the Smart Energy Use Case, illustrating how explainability techniques can be applied in a real-world decision-support environment. The demonstration provided concrete insight into the integration and use of the component within HumAIne and its contribution to supporting human interaction with AI-assisted decision-making. The session also considered the potential application of HumAIne’s explainability methods beyond the project, discussing opportunities for their adoption in other sectors and use cases. The webinar concluded with a Q&A session.
Author: Mavrepis, Philip
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: European Commission
OpenAlex ID: W7214626558