Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

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Z-Inspection

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Tool package

Z-Inspection

Z-Inspection® is a general inspection process for Ethical AI which can be applied to a variety of domains such as business, healthcare, public sector, among many others.

It uses applied ethics to assess Trustworthy AI in practice.

The Z-Inspection® process has the potential to play a key role in the context of the new EU Artificial Intelligence (AI) regulation.

The work is distributed under the terms and conditions of the Creative Commons (Attribution-NonCommercial-ShareAlike CC BY-NC-SA) license.

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Use Cases

Assessing the trustworthiness of the use of machine learning as a supportive tool to recognize cardiac arrest in emergency calls

Assessing the trustworthiness of the use of machine learning as a supportive tool to recognize cardiac arrest in emergency calls

Excerpt of: Frontiers | On Assessing Trustworthy AI in Healthcare. Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls (frontiersin.org)This is a self-assessment conducted jointly by a team of independent experts...
Jan 3, 2023

Assessing the ethical, technical and legal implications of using Deep Learning in the context of skin tumour classification

Assessing the ethical, technical and legal implications of using Deep Learning in the context of skin tumour classification

Excerpt of: Frontiers | Co-Design of a Trustworthy AI System in Healthcare: Deep Learning Based Skin Lesion Classifier (frontiersin.org)This use case documents how an ethically aligned co-design methodology ensures trustworthiness in the early d...
Jan 3, 2023

Assessing Trustworthy AI in times of COVID-19. Deep Learning for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients

Assessing Trustworthy AI in times of COVID-19. Deep Learning for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients

The BS-Net system is an end-to-end AI system that is able to estimate the severity of damage in a COVID-19 patient’s lung by assigning the corresponding Brixia score to a CXR image. The system is composed of multiple task-driven deep neural networks ...
Mar 2, 2023

Assessment for Responsible Artificial Intelligence.

Assessment for Responsible Artificial Intelligence.

Z-Inspection®  is a process to assess Trustworthy AI.During this six-month pilot, the practical application of a deep learning algorithm from the province of Fryslân has been investigated and assessed. The algorithm maps heathland grassland...
Aug 14, 2023

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.