
This report examines the Trustworthy and Ethical Assurance of Digital Twins (TEA-DT) project, a collaborative initiative aimed at operationalising the Gemini Principles to ensure digital twins (DTs) are designed, developed, and deployed in a trustworthy and ethical manner. Digital twins, dynamic virtual representations of systems, are increasingly employed in critical sectors such as healthcare, infrastructure, and environmental monitoring. However, challenges related to assuring key properties (e.g. interoperability, fairness, safety) persist due to the complexity and novelty of these of these data-driven technologies. Key contributions of this report include: Introduction to the TEA Platform: An open-source tool for creating argument-based assurance cases, enabling structured justification of DT properties with auditable evidence. Methodology for Assuring the Gemini Principles: These principles provide a shared framework for aligning DT development with purpose, trust, and function, but require participatory approaches for practical application. Participatory Design Approach: Workshops and surveys engaged stakeholders from diverse sectors to co-design assurance cases and identify domain-specific goals (e.g., explainability in healthcare, accuracy in environmental modelling, safety in infrastructure). Community Insights and Challenges: Findings from a community survey reveal barriers in data governance, interoperability, and practical implementation of assurance principles, alongside opportunities for improving trust and collaboration. The report concludes by proposing a scalable framework for participatory assurance, leveraging community resources and the TEA platform to address open challenges. Future directions include expanding use cases in healthcare and fostering a robust assurance ecosystem through collaborative programmes like the Gemini Firebox.
artifical intelligence, assurance, Gemini Principles, digital twin, data ethics, AI safety, interoperability, digital healthcare
artifical intelligence, assurance, Gemini Principles, digital twin, data ethics, AI safety, interoperability, digital healthcare
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