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.

Top 10 Principles for Ethical AI



Top 10 Principles for Ethical AI

As Artificial intelligence (AI), robotics, data and machine learning enter our workplaces across the world displacing and disrupting workers and jobs, unions must get involved. This document provides unions, shop stewards and workers with a set of concrete demands to the transparency, and application of AI. It will inform AI designers and management of the importance of worker inclusion. There is a definite urgency of now. Action is required to safeguard workers’ interests and maintain a healthy balance of power in workplaces. The 10 principles provided in this document are developed by UNI Global Union for this purpose.

This document operationalises UNI Global Union’s key demand: Artificial intelligence must put people and planet first. This is why ethical AI discussions on a global scale are essential. A global convention on ethical AI that encompasses all is the most viable guarantee for human survival.

The following offers 10 principles and specific points of action, which unions, shop stewards and global alliances must implement in collective agreements, global framework agreements and multinational alliances. Taking this action will ensure workers’ rights and influence in the age of digitalisation.

Use Cases

There is no use cases for this tool yet.

Would you like to submit a use case for this tool?

If you have used this tool, we would love to know more about your experience.

Add use case
catalogue Logos

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.