Ireland’s Centre For AI
CeADAR Z-Inspection® Trustworthy AI Lab
Leverage a competitive edge in regulatory compliance, business growth, and robustness by adopting trustworthy AI solutions provided by the CeADAR Trustworthy AI Lab, enabling companies to excel in an increasingly complex and dynamic marketplace.
Built upon a foundation of collaboration with industrial partners and the invaluable expertise gained from multiple real-world projects in numerous domains, this initiative empowers companies with practical, industry-tested advice tailored to their needs.
The CeADAR Trustworthy AI Lab is affiliated with the Z-inspection® initiative.
Z-Inspection® is a holistic process used to evaluate the trustworthiness of AI-based technologies at different stages of the AI lifecycle. It focuses, in particular, on the identification and discussion of ethical issues and tensions through the elaboration of socio-technical scenarios. It uses the general European Union’s High-Level Expert Group’s (EU HLEG) guidelines for trustworthy AI. Z-Inspection® is listed in the new OECD Catalogue of AI Tools & Metrics. The process is published in IEEE Transactions on Technology and Society.
Z-Inspection® is distributed under the terms and conditions of the Creative Commons (Attribution-Non Commercial-Share Alike CC BY-NC-SA) license.
Contact Us
For more information on the CeADAR Trustworthy AI Lab and how to apply Z-Inspection® in your projects and services, please get in touch with our team:
UPCAST: AI Assessment of a set of universal, trustworthy, transparent and user-friendly data market plugins for the automation of data sharing and processing agreements between businesses, public administrations and citizens. Applications: Biomedicine and Genomics, Public Administration Sustainability, Health and Fitness, Digital Marketing.
MANOLO (start date 01/1/2024): Trustworthy Efficient AI for Cloud-Edge Computing. Complete stack of trustworthy algorithms and tools to help AI systems reach better efficiency and seamless optimisation in their operations, resources and data required to train, deploy and run high-quality and lighter AI models in both centralised and cloud-edge distributed environments. Applications: Robotics, IT networks, Healthcare and Human Performance.